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[Master's Degree / Edx](#masters-degree--edx)\n - [Master's Degree / Coursera](#masters-degree--coursera)\n - [MicroMaster® Certificate / Edx - Computer Science](#edx--micromaster-certificate---computer-science)\n - [MicroMaster® Certificate / Edx - Data Science \u0026 Analytics](#edx--micromaster-certificate---data-science--analytics)\n - [MasterTrack® Certificate / Coursera](#coursera--mastertrack-certificate)\n\u003c/details\u003e\n\u003cdetails\u003e\n \u003csummary\u003eCoursera : Professional Certificate\u003c/summary\u003e\n\n - [General](#coursera--professional-certificate--general)\n - [Cloud - Azure](#coursera--professional-certificate--cloud---azure)\n - [Cloud - GCP (Beginner)](#coursera--professional-certificate--cloud---gcp-beginner)\n - [Cloud - GCP (Intermediate)](#coursera--professional-certificate--cloud---gcp-intermediate)\n - [Cloud - GCP (Data Science)](#coursera--professional-certificate--cloud---gcp-data-science)\n - [Data Science - SAS, R](#coursera--professional-certificate--data-science---sas-r)\n\u003c/details\u003e\n\u003cdetails\u003e\n \u003csummary\u003eCoursera : Specialization\u003c/summary\u003e\n\n - [Development - General](#coursera--specialization--development---general)\n - [Programming Language - C/C++](#coursera--specialization--programming-language---cc)\n - [Programming Language - Python](#coursera--specialization--programming-language---python)\n - [Data Structure \u0026 Algorithms](#coursera--specialization--data-structure--algorithms)\n - [Cloud - AWS](#coursera--specialization--cloud---aws)\n - [Cloud - Azure](#coursera--specialization--cloud---azure)\n - [Cloud - GCP](#coursera--specialization--cloud---gcp)\n - [Game Programming](#coursera--specialization--game-programming)\n - [Mathematics](#coursera--specialization--mathematics)\n - [Statistics](#coursera--specialization--statistics)\n - [Data Science - Python](#coursera--specialization--data-science---python)\n - [Data Science - R](#coursera--specialization--data-science---r)\n - [Data Science - SAS](#coursera--specialization--data-science---sas)\n - [Excel](#coursera--specialization--excel)\n - [RPA](#coursera--specialization--rpa)\n - [Electronic Engineering](#coursera--specialization--electronic-engineering)\n - [Investment](#coursera--specialization--investment)\n - [Investment - Python](#coursera--specialization--investment---python)\n - [Investment - ESG](#coursera--specialization--investment---esg)\n - [Blockchain](#coursera--specialization--blockchain)\n - [Blockchain - Fintech](#coursera--specialization--blockchain---fintech)\n - [Music (1) Beginner - Musicianship](#coursera--specialization--music-1-beginner---musicianship)\n - [Music (2) Beginner - Producing / Business](#coursera--specialization--music-2-beginner---producing--business)\n - [Music (3) Intermediate](#coursera--specialization--music-3-intermediate)\n - [English (1)](#coursera--specialization--english-1)\n - [English (2) Business English](#coursera--specialization--english-2-business-english)\n - [English (3) Writing](#coursera--specialization--english-3-writing)\n - [Others](#coursera--specialization--others)\n\u003c/details\u003e\n\u003cdetails\u003e\n \u003csummary\u003eCoursera : Course / Project\u003c/summary\u003e\n\n - [Course : Development (1) General](#coursera--course--development-1-general)\n - [Course : Development (2) Applications](#coursera--course--development-2-applications)\n - [Course : Development (3) Electronics](#coursera--course--development-3-electronics)\n - [Course : Music (1) Beginner, Itermedate](#coursera--course--music-1-beginner-itermedate)\n - [Course : Music (2) Mixed](#coursera--course--music-2-mixed)\n - [Course : Others](#coursera--course--others)\n - [Project : Dart \u0026 Flutter](#coursera--project--dart--flutter)\n - [Guided Project](#coursera--guided-project)\n\u003c/details\u003e\n\u003cdetails\u003e\n \u003csummary\u003eEdx\u003c/summary\u003e\n\n - [Professional Certificate](#edx--professional-certificate)\n - [Course](#edx--course)\n\u003c/details\u003e\n\u003cdetails\u003e\n \u003csummary\u003eOthers\u003c/summary\u003e\n\n - [Sololearn / Course](#sololearn--course)\n - [Naver Connect / BoostCourse](#naver-connect--boostcourse)\n - [Elice Academy / Free Course](#elice-academy--free-course)\n - [ETC](#etc)\n\u003c/details\u003e\n\n\n## [Master's Degree / Edx](#list)\n\n| Subject | Partner | Title | Tuition (USD) | Months | Credits* | GPA | TOEFL (IBT) |\n|:-:|:-:|:--|:-:|:-:|:-:|:-:|:-:|\n| Computer Science | University of Texas at Austin | [Master’s Degree in Computer Science](https://www.edx.org/masters/online-master-science-computer-science-utaustinx) | 10,000 | 18-36 | 30 | 3.0 | 79 |\n| | Georgia Tech | [Master of Science in Computer Science](https://omscs.gatech.edu/explore-oms-cs) | 9,900 | 12-36 | 36 | 3.0 | 100 |\n| Cybersecurity | Georgia Tech | [Master’s Degree in Cybersecurity](https://www.edx.org/masters/online-master-science-cybersecurity-georgia-tech) | 9,920 | 24-36 | 30 | 3.0 | 100 |\n| Data Science | University of Texas at Austin | [Master’s Degree in Data Science](https://www.edx.org/masters/online-master-data-science-utaustinx) | 10,000 | 18-36 | 30 | 3.0 | 79 |\n| Analytics | Georgia Tech | [Master’s Degree in Analytics](https://www.edx.org/masters/online-master-science-analytics-georgia-tech) | 9,900 | 12-36 | 36 | 3.0 | 100 |\n\n\\* Credits : It regarded as 3 credits per a course if there is no information.\n\n\n## [Master's Degree / Coursera](#list)\n\n| Subject | Partner | Title | Total Cost (USD) | Months | Credits* | GPA | TOEFL (IBT) |\n|:-:|:-:|:--|:-:|:-:|:-:|:-:|:-:|\n| Computer Science | Arizona State University | [Online Master of Computer Science](https://www.coursera.org/degrees/master-of-computer-science-asu) | 15,000 | 18-36 | 30 | 3.0 | 90 |\n| | University of Illinois | [Master of Computer Science (Featuring Data Science Track)](https://www.coursera.org/degrees/master-of-computer-science-illinois) | 21,440 | 12-36 | 32 | 3.2 | 103 |\n| | University of Pennsylvania | [Master of Computer and Information Technology](https://www.coursera.org/degrees/mcit-penn) | 32,140 | 16-40 | 30 | 3.0 | 100 |\n| Data Science | University of Colorado Boulder | [Master of Science in Data Science](https://www.coursera.org/degrees/master-of-science-data-science-boulder) | 20,010 | 24 | 30 | - | - |\n| | University of Michigan | [Master of Applied Data Science](https://www.coursera.org/degrees/master-of-applied-data-science-umich) | 43,894 | 12-36 | 34 | ? | 100 |\n| | Imperial College London | [Master of Science in Machine Learning and Data Science](https://www.coursera.org/degrees/msc-machine-learning-imperial) | 30,000 | 24 | 36 | 3.75 | IELTS 7.0 |\n| Electrical Engineering | University of Colorado Boulder | [Master of Science in Electrical Engineering](https://www.coursera.org/degrees/msee-boulder) | 20,010 | 24 | 30 | - | - |\n| Business Analytics | O.P. Jindal Global University | [MBA in Business Analytics](https://www.coursera.org/degrees/mba-business-analytics-jgu) | 7,050 | 24-36 | 80 | ? | ? |\n\n\\* Credits : It regarded as 3 credits per a course if there is no information.\n\n\n## [Edx / MicroMaster® Certificate - Computer Science](#list)\n\n| Subject | Partner | Course | Title | Payment($) \\* | Months | Related Degree |\n|:-:|:-:|:-:|:--|--:|:-:|:-:|\n| Computer Science | University of British Columbia | | [**Software Development**](https://www.edx.org/micromasters/ubcx-software-development) | 925 | 9 | [Master of Science in Professional Studies at Rochester Institute of Technology](https://www.rit.edu/online/pathways/ubcx-software-development),\u003cbr\u003e[Master of Science (Computer Science) at Curtin University](https://study.curtin.edu.au/offering/course-pg-computer-science-major-msc-science--mjrp-cmscmv1/) |\n| | | 1 | How to Code: Simple Data | | | |\n| | | 2 | How to Code: Complex Data | | | |\n| | | 3 | Software Construction: Data Abstraction | | | |\n| | | 4 | Software Construction: Object-Oriented Design | | | |\n| | | 5 | Software Engineering: Introduction | | | |\n| | | 6 | Software Development Capstone Project | | | |\n| | The University of California, San Diego | | [**Algorithms and Data Structures**](https://www.edx.org/micromasters/ucsandiegox-algorithms-and-data-structures) | 1,200 | 9 | [Master of Science in Professional Studies at Rochester Institute of Technology](https://www.rit.edu/online/pathways/ucsdx-algorithms-data-structure) |\n| | | 1 | Algorithmic Design and Techniques | | | |\n| | | 2 | Data Structures Fundamentals | | | |\n| | | 3 | Graph Algorithms | | | |\n| | | 4 | NP-Complete Problems | | | |\n| | | 5 | String Processing and Pattern Matching Algorithms | | | |\n| | | 6 | Dynamic Programming: Applications In Machine Learning and Genomics | | | |\n| | | 7 | Graph Algorithms in Genome Sequencing | | | |\n| | | 8 | Algorithms and Data Structures Capstone | | | |\n| | Rochester Institute of Technology | | [**Cybersecurity**](https://www.edx.org/micromasters/ritx-cybersecurity) | 1,596 | 10 | [Master of Science in Professional Studies at Rochester Institute of Technology](https://www.rit.edu/online/pathways/ritx-cybersecurity) |\n| | | 1 | Cybersecurity Fundamentals | | | |\n| | | 2 | Computer Forensics | | | |\n| | | 3 | Cybersecurity Risk Management | | | |\n| | | 4 | Network Security | | | |\n| | | 5 | Cybersecurity Capstone | | | |\n| | University of Maryland Global Campus | | [**Cloud Computing**](https://www.edx.org/micromasters/usmx-umgc-cloud-computing) | 1,196 | 8 | [Master of Science in Cloud Computing Systems](https://www.umgc.edu/online-degrees/masters/cloud-computing-systems) |\n| | | 1 | Cloud Computing for Enterprises | | | |\n| | | 2 | Cloud Computing Infrastructure | | | |\n| | | 3 | Cloud Computing Engineering and Management | | | |\n| | | 4 | Cloud Computing Security | | | |\n| | Purdue University | | [**Quantum Technology: Computing**](https://www.edx.org/micromasters/purduex-quantum-technology-computing) | 5,250 | 10 | [Master of Science in Electrical and Computer Engineering at Purdue University](https://engineering.purdue.edu/online/programs/masters-degrees/interdisciplinary-engineering/electrical-and-computer-engineering),\u003cbr\u003e[Master of Science in Professional Studies at Rochester Institute of Technology](https://www.rit.edu/online/pathways/purduex-quantum-technology-computing) |\n| | | 1 | Introduction to Quantum Science \u0026 Technology | | | |\n| | | 2 | Applied Quantum Computing I: Fundamentals | | | |\n| | | 3 | Applied Quantum Computing II: Hardware | | | |\n| | | 4 | Applied Quantum Computing III: Algorithm and Software | | | |\n| | | 5 | Quantum Detectors | | | |\n| | Purdue University | | [**Quantum Technology: Detectors and Networking**](https://www.edx.org/micromasters/purduex-quantum-technology-detectors-and-networking) | 5,250 | 10 | [Master of Science in Electrical and Computer Engineering at Purdue University](https://engineering.purdue.edu/online/programs/masters-degrees/interdisciplinary-engineering/electrical-and-computer-engineering),\u003cbr\u003e[Master of Science in Professional Studies at Rochester Institute of Technology](https://www.rit.edu/online/pathways/purduex-quantum-technology-detectors-and-networking) |\n| | | 1 | Quantum Networking | | | |\n| | | 2 | Quantum Detectors and Sensors | | | |\n| | | 3 | Applied Quantum Computing I: Fundamentals | | | |\n| | | 4 | Applied Quantum Computing II: Hardware | | | |\n| | | 5 | Applied Quantum Computing III: Algorithm and Software | | | |\n\n\\* They may be discounted.\n\n\n## [Edx / MicroMaster® Certificate - Data Science \u0026 Analytics](#list)\n\n| Subject | Partner | Course | Title | Payment($) \\* | Months | Related Degree |\n|:-:|:-:|:-:|:--|--:|:-:|:-:|\n| Data Science | The University of California, San Diego | | [**Data Science**](https://www.edx.org/micromasters/uc-san-diegox-data-science) | 1,400 | 10 | [Master of Science degree in Data Science at Rochester Institute of Technology](https://www.rit.edu/online/pathways/ucsdx-data-science) |\n| | | 1 | Python for Data Science | | | |\n| | | 2 | Probability and Statistics in Data Science using Python | | | |\n| | | 3 | Machine Learning Fundamentals | | | |\n| | | 4 | Machine Learning Fundamentals | | | |\n| | Massachusetts Institute of Technology | | [**Statistics and Data Science**](https://www.edx.org/micromasters/mitx-statistics-and-data-science) | 1,500 | 14 | [Refer to this link](https://www.edx.org/micromasters/mitx-statistics-and-data-science) |\n| | | 1 | Probability - The Science of Uncertainty and Data | | | |\n| | | 2 | Fundamentals of Statistics | | | |\n| | | 3 | Machine Learning with Python: from Linear Models to Deep Learning | | | |\n| | | 4 | Capstone Exam in Statistics and Data Science | | | |\n| | | 5 | (Select one) Data Analysis in Social Science—Assessing Your Knowledge | | | |\n| | | 5 | (Select one) Data Analysis: Statistical Modeling and Computation in Applications | | | |\n| | University of Adelaide | | [**Big Data**](https://www.edx.org/micromasters/adelaidex-big-data) | 985.5 | 12 | [Master of Data Science at the University of Adelaide](https://www.adelaide.edu.au/degree-finder/mdsci_mdatasci.html)\u003cbr\u003e[Master of Science in Professional Studies at Rochester Institute of Technology](https://www.rit.edu/online/pathways/adelaidex-big-data) |\n| | | 1 | Programming for Data Science | | | |\n| | | 2 | Computational Thinking and Big Data | | | |\n| | | 3 | Big Data Fundamentals | | | |\n| | | 4 | Big Data Analytics | | | |\n| | | 5 | Big Data Capstone Project | | | |\n| | The Hong Kong University of Science and Technology | | [**Big Data Technology**](https://www.edx.org/micromasters/hkustx-big-data-technology) | 1,450 | 9 | Master of Science programs in Big Data Technology (BDT) and Information Technology (IT) |\n| | | 1 | Foundations of Data Analytics | | | |\n| | | 2 | Data Mining and Knowledge Discovery | | | |\n| | | 3 | Big Data Computing with Spark | | | |\n| | | 4 | Mathematical Methods for Data Analysis | | | |\n| | | 5 | Big Data Technology Capstone Project | | | |\n| Analytics | The Georgia Institute of Technology | | [**Analytics: Essential Tools and Methods**](https://www.edx.org/micromasters/gtx-analytics-essential-tools-and-methods) | 2,475 | 12 | [Online Master of Science in Analytics](https://pe.gatech.edu/degrees/analytics)\u003cbr\u003e[Master of Science in Professional Studies at Rochester Institute of Technology](https://www.rit.edu/online/pathways/gtx-analytics-essential-tools-methods) |\n| | | 1 | Introduction to Analytics Modeling | | | |\n| | | 2 | Computing for Data Analysis | | | |\n| | | 3 | Data Analytics for Business | | | |\n\n\\* They may be discounted.\n\n\n## [Coursera / MasterTrack® Certificate](#list)\n\n| Subject | Partner | Course | Title | Payment($) | Months | Related Degree |\n|:-:|:-:|:-:|:--|--:|:-:|:-:|\n| IT | Arizona State University | | [**AI \u0026 Machine Learning**](https://www.coursera.org/mastertrack/ai-machine-learning-asu)\\* | 4,500 | 6-9 | Master of Computer Science |\n| | | 1 | Statistical Machine Learning | | | |\n| | | 2 | Artificial Intelligence | | | |\n| | | 3 | Knowledge Representation and Reasoning | | | |\n| | | 4 | Intro to Deep Learning in Visual Computing | | | |\n| | Arizona State University | | [**Big Data**](https://www.coursera.org/mastertrack/big-data-asu)\\* | 4,500 | 6-9 | Master of Computer Science |\n| | | 1 | Data Processing at Scale | | | |\n| | | 2 | Data Mining | | | |\n| | | 3 | Statistical Machine Learning | | | |\n| | | 4 | Data Visualization | | | |\n| | Arizona State University | | [**Cybersecurity**](https://www.coursera.org/mastertrack/cybersecurity-asu)\\* | 4,500 | 6-9 | Master of Computer Science |\n| | | 1 | Information Assurance and Security | | | |\n| | | 2 | Applied Cryptography | | | |\n| | | 3 | Software Security | | | |\n| | | 4 | Advanced Computer and Network Security | | | |\n| | | 5 | Distributed and Multiprocessor Operating Systems | | | |\n| | | 6 | Accelerated Applied Security | | | |\n| | Arizona State University | | [**Software Engineering**](https://www.coursera.org/mastertrack/software-engineering-asu)\\* | 4,500 | 6-9 | Master of Computer Science |\n| | | 1 | Software Verification, Validation, and Testing | | | |\n| | | 2 | Advanced Software Analysis and Design | | | |\n| | | 3 | Engineering Blockchain Applications | | | |\n| | | 4 | Mobile Computing | | | |\n| Analytics | The University of Chicago | | [**Machine Learning for Analytics**](https://www.coursera.org/mastertrack/machine-learning-analytics-chicago) | 4,000 | 5 | Master of Science in Analytics |\n| | | 1 | Statistical Thinking for Machine Learning | | | |\n| | | 2 | Advanced Statistical Thinking for Machine Learning | | | |\n| | | 3 | Introduction to Machine Learning | | | |\n| | | 4 | Advanced Applications | | | |\n| | Tufts University | | [**Business Analytics for Managers**](https://www.coursera.org/mastertrack/data-analytics-managers-tufts) | 3,000 | 6 | Master of Science in Engineering Management |\n| | | 1 | Analytics Techniques for Business Insight | | | |\n| | | 2 | Expanding Your Business Analytics Skills | | | |\n| | | 3 | Data Analytics In Product Development and Production | | | |\n| | | 4 | Marketing and Sales Data Decision Making | | | |\n| | | 5 | Data Analytics Applications Finance and Economics | | | |\n\n\\* Take 3 of the 4 courses listed to earn your certificate.\n\n\n## [Coursera / Professional Certificate : General](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| COBOL | [**IBM Mainframe Developer**](https://www.coursera.org/professional-certificates/ibm-mainframe-developer) | Bgn. | 101 | × | × | IBM |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Enterprise Computing](https://www.coursera.org/learn/introduction-enterprise-computing) | Bgn. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [IBM COBOL Basics](https://www.coursera.org/learn/ibm-cobol-basics) | Bgn. | 14 | | | |\n| | \u0026nbsp;\u0026nbsp;· [IBM COBOL Core](https://www.coursera.org/learn/ibm-cobol-core) | Bgn. | 11 | | | |\n| | \u0026nbsp;\u0026nbsp;· [IBM COBOL Software Development Practices](https://www.coursera.org/learn/software-development-practices) | Bgn. | 18 | | | |\n| | \u0026nbsp;\u0026nbsp;· [IBM COBOL Data and File Management](https://www.coursera.org/learn/cobol-data-file-management) | Bgn. | 17 | | | |\n| | \u0026nbsp;\u0026nbsp;· [IBM COBOL Basic Testing and Debugging](https://www.coursera.org/learn/cobol-testing-debugging) | Bgn. | 14 | | | |\n| | \u0026nbsp;\u0026nbsp;· [IBM COBOL Software Development Process](https://www.coursera.org/learn/software-development-proccess) | Bgn. | 17 | | | |\n| IT Automation\u003cbr\u003ePython | [**Google IT Automation with Python**](https://www.coursera.org/professional-certificates/google-it-automation) | Bgn. | 115 | ○ | △ | Google |\n| | \u0026nbsp;\u0026nbsp;· [Crash Course on Python](https://www.coursera.org/learn/python-crash-course) | Bgn. | 28 | | ○ | |\n| | \u0026nbsp;\u0026nbsp;· [Using Python to Interact with the Operating System](https://www.coursera.org/learn/python-operating-system) | Bgn. | 27 | | × | |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Git and GitHub](https://www.coursera.org/learn/introduction-git-github) | Bgn. | 16 | | × | |\n| | \u0026nbsp;\u0026nbsp;· [Troubleshooting and Debugging Techniques](https://www.coursera.org/learn/troubleshooting-debugging-techniques) | Bgn. | 16 | | × | |\n| | \u0026nbsp;\u0026nbsp;· [Configuration Management and the Cloud](https://www.coursera.org/learn/configuration-management-cloud) | Bgn. | 15 | | × | |\n| | \u0026nbsp;\u0026nbsp;· [Automating Real-World Tasks with Python](https://www.coursera.org/learn/automating-real-world-tasks-python) | Bgn. | 13 | | × | |\n| IT Support | [**Google IT Support**](https://www.coursera.org/professional-certificates/google-it-support) | Bgn. | 124 | ○ | × | Google |\n| | \u0026nbsp;\u0026nbsp;· [Technical Support Fundamentals](https://www.coursera.org/learn/technical-support-fundamentals) | Bgn. | 20 | | | |\n| | \u0026nbsp;\u0026nbsp;· [The Bits and Bytes of Computer Networking](https://www.coursera.org/learn/computer-networking) | Bgn. | 25 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Operating Systems and You: Becoming a Power User](https://www.coursera.org/learn/os-power-user) | Bgn. | 31 | | | |\n| | \u0026nbsp;\u0026nbsp;· [System Administration and IT Infrastructure Services](https://www.coursera.org/learn/system-administration-it-infrastructure-services) | Bgn. | 24 | | | |\n| | \u0026nbsp;\u0026nbsp;· [IT Security: Defense against the digital dark arts](https://www.coursera.org/learn/it-security) | Bgn. | 24 | | | |\n| IT Support | [**IBM Technical Support**](https://www.coursera.org/professional-certificates/ibm-technical-support) | Bgn. | 48+ | × | × | IBM |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Hardware and Operating Systems](https://www.coursera.org/learn/introduction-to-hardware-and-operating-systems) | Bgn. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Software, Programming, and Databases](https://www.coursera.org/learn/introduction-software-programming-and-databases) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Networking and Storage](https://www.coursera.org/learn/introduction-to-networking-and-storage) | Bgn. | 5 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Cybersecurity Essentials](https://www.coursera.org/learn/introduction-to-cybersecurity-essentials) | Bgn. | 5 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Cloud Computing](https://www.coursera.org/learn/introduction-to-cloud) | Bgn. | 13 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Technical Support](https://www.coursera.org/learn/introduction-to-technical-support) | Bgn. | 6 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Technical Support Case Studies and Project](https://www.coursera.org/learn/technical-support-case-studies) | Bgn. | - | | | |\n| Project Management | [**Google Project Management**](https://www.coursera.org/professional-certificates/google-project-management) | Bgn. | 155 | ○ | × | Google |\n| | \u0026nbsp;\u0026nbsp;· [Foundations of Project Management](https://www.coursera.org/learn/project-management-foundations) | Bgn. | 18 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Project Initiation: Starting a Successful Project](https://www.coursera.org/learn/project-initiation-google) | Bgn. | 22 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Project Planning: Putting It All Together](https://www.coursera.org/learn/project-planning-google) | Bgn. | 29 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Project Execution: Running the Project](https://www.coursera.org/learn/project-execution-google) | Bgn. | 26 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Agile Project Management](https://www.coursera.org/learn/agile-project-management) | Bgn. | 26 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Capstone: Applying Project Management in the Real World](https://www.coursera.org/learn/applying-project-management) | Bgn. | 34 | | | |\n\n\n## [Coursera / Professional Certificate : Cloud - Azure](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| Microsoft Azure | [**Microsoft Azure Developer Associate (AZ-204)**](https://www.coursera.org/professional-certificates/azure-developer-associate) | Itm. | 89 | ○ | × | Microsoft |\n| | \u0026nbsp;\u0026nbsp;· [Create Serverless Applications](https://www.coursera.org/learn/create-serverless-applications) | Itm. | 18 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Connect Your Services with Microsoft Azure Service Bus](https://www.coursera.org/learn/connect-your-services-with-microsoft-azure-service-bus) | Itm. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Storage in Microsoft Azure for Associate Developers](https://www.coursera.org/learn/data-storage-microsoft-azure-developers) | Itm. | 16 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Deploy a website with Azure Virtual Machines](https://www.coursera.org/learn/deploy-a-website-with-azure-virtual-machines) | Itm. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Manage Resources in Azure](https://www.coursera.org/learn/manage-resources-azure) | Itm. | 11 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Deploy a website to Azure with Azure App Service](https://www.coursera.org/learn/deploy-a-website-to-azure-with-azure-app-service) | Itm. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Secure your Cloud Data](https://www.coursera.org/learn/secure-your-cloud-data) | Itm. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Prepare for AZ-204: Developing Solutions for Microsoft Azure](https://www.coursera.org/learn/az-204-developing-solutions-for-microsoft-azure) | Itm. | 7 | | | |\n| Microsoft Azure | [**Microsoft Azure Data Engineering Associate (DP-203)**](https://www.coursera.org/professional-certificates/microsoft-azure-dp-203-data-engineering) | Itm. | 117 | ○ | × | Microsoft |\n| | \u0026nbsp;\u0026nbsp;· [Microsoft Azure for Data Engineering](https://www.coursera.org/learn/microsoft-azure-dp-203-data-engineering) | Itm. | 6 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Storage in Microsoft Azure](https://www.coursera.org/learn/data-storage-microsoft-azure) | Itm. | 16 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Integration with Microsoft Azure Data Factory](https://www.coursera.org/learn/azure-data-factory-data-integration) | Itm. | 16 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Microsoft Azure Synapse Analytics](https://www.coursera.org/learn/introduction-to-microsoft-azure-synapse-analytics) | Itm. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Warehousing with Microsoft Azure Synapse Analytics](https://www.coursera.org/learn/data-warehousing-with-microsoft-azure-synapse-analytics) | Itm. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Engineering with MS Azure Synapse Apache Spark Pools](https://www.coursera.org/learn/data-engineering-with-ms-azure-synapse-apache-spark-pools) | Itm. | 7 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Operational Analytics with Microsoft Azure Synapse Analytics](https://www.coursera.org/learn/operational-analytics-with-microsoft-azure-synapse-analytics) | Itm. | 12 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Microsoft Azure Databricks for Data Engineering](https://www.coursera.org/learn/microsoft-azure-databricks-for-data-engineering) | Itm. | 22 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Azure Data Lake Storage Gen2 and Data Streaming Solution](https://www.coursera.org/learn/azure-data-lake-storage-gen2-and-data-streaming-solution) | Itm. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Prepare for DP-203: Data Engineering on Microsoft Azure Exam](https://www.coursera.org/learn/microsoft-dp-203-practice-exam) | Itm. | 6 | | | |\n| Microsoft Azure\u003cbr\u003eMachine Learning | [**Microsoft Azure Data Scientist Associate (DP-100)**](https://www.coursera.org/professional-certificates/azure-data-scientist) | Itm. | 90 | ○ | × | Microsoft |\n| | \u0026nbsp;\u0026nbsp;· [Create Machine Learning Models in Microsoft Azure](https://www.coursera.org/learn/create-machine-learning-models-in-microsoft-azure) | Itm. | 13 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Microsoft Azure Machine Learning for Data Scientists](https://www.coursera.org/learn/microsoft-azure-machine-learning-for-data-scientist) | Itm. | 11 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Build and Operate Machine Learning Solutions with Azure](https://www.coursera.org/learn/build-and-operate-machine-learning-solutions-with-azure) | Itm. | 31 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Perform data science with Azure Databricks](https://www.coursera.org/learn/perform-data-science-with-azure-databricks) | Itm. | 26 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Prepare for DP-100: Data Science on Microsoft Azure Exam](https://www.coursera.org/learn/prepare-for-dp-100-design-a-data-science-solution-on-azure) | Itm. | 9 | | | |\n\n\n## [Coursera / Professional Certificate : Cloud - GCP (Beginner)](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| Google Cloud | [**Google Cloud Digital Leader Training**](https://www.coursera.org/professional-certificates/google-cloud-digital-leader-training) | Bgn. | 8 | ○ | × | Google Cloud |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Digital Transformation with Google Cloud](https://www.coursera.org/learn/digital-transformation-google-cloud) | Bgn. | 2 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Innovating with Data and Google Cloud](https://www.coursera.org/learn/innovating-with-data-google-cloud) | Bgn. | 2 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Infrastructure and Application Modernization with Google Cloud](https://www.coursera.org/learn/google-cloud-product-fundamentals) | Bgn. | 2 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Understanding Google Cloud Security and Operations](https://www.coursera.org/learn/understanding-google-cloud-security-and-operations) | Bgn. | 2 | | | |\n| Google Cloud | [**Preparing for Google Cloud Certification: Cloud DevOps Engineer**](https://www.coursera.org/professional-certificates/sre-devops-engineer-google-cloud) | Bgn. | 51 | ○ | × | Google Cloud |\n| | \u0026nbsp;\u0026nbsp;· [Google Cloud Fundamentals: Core Infrastructure](https://www.coursera.org/learn/gcp-fundamentals) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Developing a Google SRE Culture](https://www.coursera.org/learn/developing-a-google-sre-culture) | Bgn. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Reliable Google Cloud Infrastructure: Design and Process](https://www.coursera.org/learn/cloud-infrastructure-design-process) | Adv. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Logging, Monitoring and Observability in Google Cloud](https://www.coursera.org/learn/logging-monitoring-observability-google-cloud) | Bgn. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Getting Started with Google Kubernetes Engine](https://www.coursera.org/learn/google-kubernetes-engine) | Itm. | 11 | | | |\n\n\n## [Coursera / Professional Certificate : Cloud - GCP (Intermediate)](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| Google Cloud | [**Preparing for Google Cloud Certification: Cloud Engineer Professional**](https://www.coursera.org/professional-certificates/cloud-engineering-gcp) | Itm. | 44 | ○ | × | Google Cloud |\n| | \u0026nbsp;\u0026nbsp;· [Google Cloud Fundamentals: Core Infrastructure](https://www.coursera.org/learn/gcp-fundamentals) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Essential Google Cloud Infrastructure: Foundation](https://www.coursera.org/learn/gcp-infrastructure-foundation) | Itm. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Essential Google Cloud Infrastructure: Core Services](https://www.coursera.org/learn/gcp-infrastructure-core-services) | Itm. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Elastic Google Cloud Infrastructure: Scaling and Automation](https://www.coursera.org/learn/gcp-infrastructure-scaling-automation) | Itm. | 7 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Architecting with Google Kubernetes Engine: Foundations](https://www.coursera.org/learn/foundations-google-kubernetes-engine-gke) | Itm. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Preparing for Your Associate Cloud Engineer Journey](https://www.coursera.org/learn/preparing-cloud-associate-cloud-engineer-exam) | Itm. | 4 | | | |\n| Google Cloud | [**Preparing for Google Cloud Certification: Cloud Architect Professional**](https://www.coursera.org/professional-certificates/gcp-cloud-architect) | Itm. | 61 | ○ | × | Google Cloud |\n| | \u0026nbsp;\u0026nbsp;· [Google Cloud Fundamentals: Core Infrastructure](https://www.coursera.org/learn/gcp-fundamentals) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Essential Google Cloud Infrastructure: Foundation](https://www.coursera.org/learn/gcp-infrastructure-foundation) | Itm. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Essential Google Cloud Infrastructure: Core Services](https://www.coursera.org/learn/gcp-infrastructure-core-services) | Itm. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Elastic Google Cloud Infrastructure: Scaling and Automation](https://www.coursera.org/learn/gcp-infrastructure-scaling-automation) | Itm. | 7 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Reliable Google Cloud Infrastructure: Design and Process](https://www.coursera.org/learn/cloud-infrastructure-design-process) | Adv. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Architecting with Google Kubernetes Engine: Foundations](https://www.coursera.org/learn/foundations-google-kubernetes-engine-gke) | Itm. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Preparing for the Google Cloud Professional Cloud Architect Exam](https://www.coursera.org/learn/preparing-cloud-professional-cloud-architect-exam) | Adv. | 13 | | | |\n| Google Cloud | [**Preparing for Google Cloud Certification: Cloud Security Engineer Professional**](https://www.coursera.org/professional-certificates/google-cloud-security) | Itm. | 67 | ○ | × | Google Cloud |\n| | \u0026nbsp;\u0026nbsp;· [Preparing for Your Professional Cloud Security Engineer Journey](https://www.coursera.org/learn/preparing-for-your-professional-cloud-security-engineer-journey) | Bgn. | 7 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Google Cloud Fundamentals: Core Infrastructure](https://www.coursera.org/learn/gcp-fundamentals) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Networking in Google Cloud: Defining and Implementing Networks](https://www.coursera.org/learn/networking-gcp-defining-implementing-networks) | Itm. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Networking in Google Cloud: Hybrid Connectivity and Network Management](https://www.coursera.org/learn/networking-gcp-hybrid-connectivity-network-management) | Itm. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Managing Security in Google Cloud](https://www.coursera.org/learn/managing-security-in-google-cloud-platform) | Itm. | 7 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Security Best Practices in Google Cloud](https://www.coursera.org/learn/security-best-practices-in-google-cloud) | Itm. | 13 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Mitigating Security Vulnerabilities on Google Cloud](https://www.coursera.org/learn/mitigating-security-vulnerabilites-gcp) | Itm. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Hands-On Labs in Google Cloud for Security Engineers](https://www.coursera.org/learn/hands-on-labs-google-cloud-security-engineer) | Itm. | 5 | | | |\n| Google Cloud | [**Preparing for Google Cloud Certification: Cloud Network Engineer Professional**](https://www.coursera.org/professional-certificates/google-cloud-networking) | Itm. | 33 | ○ | × | Google Cloud |\n| | \u0026nbsp;\u0026nbsp;· [Google Cloud Fundamentals: Core Infrastructure](https://www.coursera.org/learn/gcp-fundamentals) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Networking in Google Cloud: Defining and Implementing Networks](https://www.coursera.org/learn/networking-gcp-defining-implementing-networks) | Itm. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Networking in Google Cloud: Hybrid Connectivity and Network Management](https://www.coursera.org/learn/networking-gcp-hybrid-connectivity-network-management) | Itm. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Hands-On Labs in Google Cloud for Networking Engineers](https://www.coursera.org/learn/hands-on-labs-google-cloud-networking-engineer) | Itm. | 6 | | | |\n\n\n## [Coursera / Professional Certificate : Cloud - GCP (Data Science)](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| Google Cloud | [**Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate**](https://www.coursera.org/professional-certificates/gcp-data-engineering) | Itm. | 58 | ○ | × | Google Cloud |\n| | \u0026nbsp;\u0026nbsp;· [Google Cloud Big Data and Machine Learning Fundamentals](https://www.coursera.org/learn/gcp-big-data-ml-fundamentals) | Bgn. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Modernizing Data Lakes and Data Warehouses with Google Cloud](https://www.coursera.org/learn/data-lakes-data-warehouses-gcp) | Itm. | 7 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Building Batch Data Pipelines on Google Cloud](https://www.coursera.org/learn/batch-data-pipelines-gcp) | Itm. | 17 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Building Resilient Streaming Analytics Systems on Google Cloud](https://www.coursera.org/learn/streaming-analytics-systems-gcp) | Itm. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Smart Analytics, Machine Learning, and AI on GCP](https://www.coursera.org/learn/smart-analytics-machine-learning-ai-gcp) | Itm. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Preparing for the Google Cloud Professional Data Engineer Exam](https://www.coursera.org/learn/preparing-cloud-professional-data-engineer-exam) | Adv. | 8 | | | |\n| Google Cloud\u003cbr\u003eMachine Learning | [**Preparing for Google Cloud Certification: Machine Learning Engineer**](https://www.coursera.org/professional-certificates/preparing-for-google-cloud-machine-learning-engineer-professional-certificate) | Itm. | 138 | ○ | × | Google Cloud |\n| | \u0026nbsp;\u0026nbsp;· [Google Cloud Big Data and Machine Learning Fundamentals](https://www.coursera.org/learn/gcp-big-data-ml-fundamentals) | Bgn. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [How Google does Machine Learning](https://www.coursera.org/learn/google-machine-learning) | Bgn. | 13 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Launching into Machine Learning](https://www.coursera.org/learn/launching-machine-learning) | Bgn. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [TensorFlow on Google Cloud](https://www.coursera.org/learn/intro-tensorflow) | Itm. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Feature Engineering](https://www.coursera.org/learn/feature-engineering) | Itm. | 14 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Machine Learning in the Enterprise](https://www.coursera.org/learn/art-science-ml) | Adv. | 24 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Production Machine Learning Systems](https://www.coursera.org/learn/gcp-production-ml-systems) | Adv. | 21 | | | |\n| | \u0026nbsp;\u0026nbsp;· [MLOps (Machine Learning Operations) Fundamentals](https://www.coursera.org/learn/mlops-fundamentals) | Itm. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [ML Pipelines on Google Cloud](https://www.coursera.org/learn/ml-pipelines-google-cloud) | Adv. | 11 | | | |\n\n\n## [Coursera / Professional Certificate : Data Science - SAS, R](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| SAS | [**SAS Programmer**](https://www.coursera.org/professional-certificates/sas-programming) | Bgn. | 74 | ○ | ○ | SAS |\n| | \u0026nbsp;\u0026nbsp;· [Getting Started with SAS Programming](https://www.coursera.org/learn/sas-programming-basics) | Bgn. | 24 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Doing More with SAS Programming](https://www.coursera.org/learn/sas-programming-advanced) | Itm. | 25 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Preparing for the SAS Programming Certification Exam](https://www.coursera.org/learn/preparing-sas-programming-certification) | Itm. | 16 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Practicing for the SAS Programming Certification Exam](https://www.coursera.org/learn/practicing-sas-programming-certification) | Itm. | 9 | | | |\n| SAS | [**SAS Advanced Programmer**](https://www.coursera.org/professional-certificates/sas-advanced-programmer) | Itm. | 63 | ○ | ○ | SAS |\n| | \u0026nbsp;\u0026nbsp;· [Structured Query Language (SQL) using SAS](https://www.coursera.org/learn/sas-sql) | - | 26 | | | |\n| | \u0026nbsp;\u0026nbsp;· [SAS Macro Language](https://www.coursera.org/learn/sas-macro-language) | Itm. | 20 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Advanced SAS Programming Techniques](https://www.coursera.org/learn/advanced-sas-programming-techniques) | Itm. | 17 | | | |\n| SAS | [**SAS Statistical Business Analyst**](https://www.coursera.org/professional-certificates/sas-statistical-business-analyst) | Itm. | 37 | ○ | ○ | SAS |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Statistical Analysis: Hypothesis Testing](https://www.coursera.org/learn/statistical-analysis-hypothesis-testing-sas) | Itm. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Regression Modeling Fundamentals](https://www.coursera.org/learn/regression-modeling-sas) | Itm. | 11 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Predictive Modeling with Logistic Regression using SAS](https://www.coursera.org/learn/sas-predictive-modeling-using-logistic-regression) | Itm. | 16 | | | |\n| SAS | [**SAS Visual Business Analytics**](https://www.coursera.org/professional-certificates/sas-visual-business-analytics) | Bgn. | 29 | ○ | ○ | SAS |\n| | \u0026nbsp;\u0026nbsp;· [Getting Started with SAS Visual Analytics](https://www.coursera.org/learn/preparing-data-sas-va) | Bgn. | 4 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Analysis and Reporting in SAS Visual Analytics](https://www.coursera.org/learn/data-analysis-reporting-sas-va) | - | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Using Data for Geographic Mapping and Forecasting in SAS Visual Analytics](https://www.coursera.org/learn/using-data-geographic-mapping-sas-va) | Itm. | 4 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Performing Network, Path, and Text Analyses in SAS Visual Analytics](https://www.coursera.org/learn/network-path-text-analyses-sas-va) | Itm. | 4 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Creating Advanced Reports with SAS Visual Analytics](https://www.coursera.org/learn/advanced-reports-sas-va) | Itm. | 8 | | | |\n| Excel\u003cbr\u003eR | [**IBM Data Analytics with Excel and R**](https://www.coursera.org/professional-certificates/ibm-data-analyst-r-excel) | Bgn. | 127 | ○ | ○ | IBM |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Data Analytics](https://www.coursera.org/learn/introduction-to-data-analytics) | Bgn. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Excel Basics for Data Analysis](https://www.coursera.org/learn/excel-basics-data-analysis-ibm) | Bgn. | 12 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Visualization and Dashboards with Excel and Cognos](https://www.coursera.org/learn/data-visualization-dashboards-excel-cognos) | Bgn. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Assessment for Data Analysis and Visualization Foundations](https://www.coursera.org/learn/data-analysis-visualization-foundations-assessment) | Bgn. | 1 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to R Programming for Data Science](https://www.coursera.org/learn/introducton-r-programming-data-science) | Bgn. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [SQL for Data Science with R](https://www.coursera.org/learn/sql-data-science-r) | Bgn. | 27 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Analysis with R](https://www.coursera.org/learn/data-analysis-with-r) | Itm. | 16 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Visualization with R](https://www.coursera.org/learn/data-visualization-r) | Bgn. | 12 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Science with R - Capstone Project](https://www.coursera.org/learn/data-science-with-r-capstone-project) | Itm. | 24 | | | |\n\n\n## [Coursera / Specialization : Development - General](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| Golang | [**Programming with Google Go**](https://www.coursera.org/specializations/google-golang) | Itm. | 28 | ○ | × | University of California, Irvine |\n| | \u0026nbsp;\u0026nbsp;· [Getting Started with Go](https://www.coursera.org/learn/golang-getting-started) | Itm. | 11 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Functions, Methods, and Interfaces in Go](https://www.coursera.org/learn/golang-functions-methods) | Itm. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Concurrency in Go](https://www.coursera.org/learn/golang-concurrency) | Itm. | 9 | | | |\n| Java | [**Java as a Second Language**](https://www.coursera.org/specializations/java-programming-language) | Itm. | 28 | ○ | × | LearnQuest |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Java as a Second Language](https://www.coursera.org/learn/intro-java-second-language) | Itm. | 7 | | | |\n| | \u0026nbsp;\u0026nbsp;· [The Java Language](https://www.coursera.org/learn/java-as-a-second-language-the-java-language) | Itm. | 7 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Writing Java Application Code](https://www.coursera.org/learn/writing-java-code-for-applications) | Itm. | 14 | | | |\n| Open Source Linux Git | [**Open Source Software Development, Linux and Git**](https://www.coursera.org/specializations/oss-development-linux-git) | Bgn. | 60 | ○ | × | The Linux Foundation |\n| | \u0026nbsp;\u0026nbsp;· [Open Source Software Development Methods](https://www.coursera.org/learn/open-source-software-development-methods) | Bgn. | 4 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Linux for Developers](https://www.coursera.org/learn/linux-for-developers) | Bgn. | 19 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Linux Tools for Developers](https://www.coursera.org/learn/linux-tools-for-developers) | Bgn. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Using Git for Distributed Development](https://www.coursera.org/learn/git-distributed-development) | Bgn. | 22 | | | |\n| Scala | [**Functional Programming in Scala**](https://www.coursera.org/specializations/scala) | Itm. | 184 | ○ | × | École Polytechnique Fédérale de Lausanne |\n| | \u0026nbsp;\u0026nbsp;· [Functional Programming Principles in Scala](https://www.coursera.org/learn/scala-functional-programming) | Itm. | 56 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Functional Program Design in Scala](https://www.coursera.org/learn/scala-functional-program-design) | Itm. | 35 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Parallel programming](https://www.coursera.org/learn/scala-parallel-programming) | Itm. | 33 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Big Data Analysis with Scala and Spark](https://www.coursera.org/learn/scala-spark-big-data) | Itm. | 28 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Functional Programming in Scala Capstone](https://www.coursera.org/learn/scala-capstone) | - | 32 | | | |\n| VB | [**Introduction to Computer Programming with Visual Basic**](https://www.coursera.org/specializations/visual-basic-computer-programming) | Bgn. | 95 | ○ | × | LearnQuest |\n| | \u0026nbsp;\u0026nbsp;· [Foundations of Computer Science](https://www.coursera.org/learn/computer-science-foundations) | Bgn. | 16 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Visual Basic Programming](https://www.coursera.org/learn/visual-basic-programming-introduction) | Bgn. | 28 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Visual Basic Programming: Classes and Collections](https://www.coursera.org/learn/visual-basic-classes-collections) | Itm. | 28 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Visual Basic Programming: Inheritance and Polymorphism](https://www.coursera.org/learn/visual-basic-inheritance-polymorphism) | Itm. | 23 | | | |\n\n\n## [Coursera / Specialization : Programming Language - C/C++](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| C | [**Introductory C Programming**](https://www.coursera.org/specializations/c-programming) | Bgn. | 82 | ○ | × | Duke University |\n| | \u0026nbsp;\u0026nbsp;· [Programming Fundamentals](https://www.coursera.org/learn/programming-fundamentals) | Bgn. | 18 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Writing, Running, and Fixing Code in C](https://www.coursera.org/learn/writing-running-fixing-code) | Bgn. | 20 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Pointers, Arrays, and Recursion](https://www.coursera.org/learn/pointers-arrays-recursion) | Bgn. | 21 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Interacting with the System and Managing Memory](https://www.coursera.org/learn/interacting-system-managing-memory) | Bgn. | 23 | | | |\n| C | [**Computational Thinking with Beginning C Programming**](https://www.coursera.org/specializations/computational-thinking-c-programming) | Bgn. | 54 | ○ | × | University of Colorado System |\n| | \u0026nbsp;\u0026nbsp;· [Algorithms, Data Collection, and Starting to Code](https://www.coursera.org/learn/algorithms-data-collection-code) | Bgn. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Analysis and Representation, Selection and Iteration](https://www.coursera.org/learn/data-analysis-representation-selection-iteration) | Bgn. | 11 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Abstraction, Problem Decomposition, and Functions](https://www.coursera.org/learn/abstraction-problem-decomposition-functions) | Bgn. | 17 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Simulation, Algorithm Analysis, and Pointers](https://www.coursera.org/learn/simulation-algorithm-analysis-pointers) | Bgn. | 11 | | | |\n| C++ | [**Programming in C++: A Hands-on Introduction**](https://www.coursera.org/specializations/hands-on-cpp) | Bgn. | 36 | ○ | × | Codio |\n| | \u0026nbsp;\u0026nbsp;· [C++ Basics: Selection and Iteration](https://www.coursera.org/learn/codio-cpp-basics) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [C++ Basic Structures: Vectors, Pointers, Strings, and Files](https://www.coursera.org/learn/cpp-basic-structures-vectors-pointers-strings-and-files) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [C++ Object Basics: Functions, Recursion, and Objects](https://www.coursera.org/learn/cpp-object-basics) | Itm. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Object-Oriented C++: Inheritance and Encapsulation](https://www.coursera.org/learn/object-oriented-cpp) | Itm. | 9 | | | |\n| C C++ | [**Coding for Everyone: C and C++**](https://www.coursera.org/specializations/coding-for-everyone) | Bgn. | 53 | ○ | × | University of California, Santa Cruz |\n| | \u0026nbsp;\u0026nbsp;· [C for Everyone: Programming Fundamentals](https://www.coursera.org/learn/c-for-everyone) | Bgn. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [C for Everyone: Structured Programming](https://www.coursera.org/learn/c-structured-programming) | Itm. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [C++ For C Programmers, Part A](https://www.coursera.org/learn/c-plus-plus-a) | - | 13 | | | |\n| | \u0026nbsp;\u0026nbsp;· [C++ For C Programmers, Part B](https://www.coursera.org/learn/c-plus-plus-b) | - | 15 | | | |\n\n\n## [Coursera / Specialization : Programming Language - Python](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| Python | [**Python for Everybody**](https://www.coursera.org/specializations/python) | Bgn. | 81 | ○ | ○ | University of Michigan |\n| | \u0026nbsp;\u0026nbsp;· [Programming for Everybody (Getting Started with Python)](https://www.coursera.org/learn/python) | - | 19 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Python Data Structures](https://www.coursera.org/learn/python-data) | - | 19 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Using Python to Access Web Data](https://www.coursera.org/learn/python-network-data) | - | 19 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Using Databases with Python](https://www.coursera.org/learn/python-databases) | - | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Capstone: Retrieving, Processing, and Visualizing Data with Python](https://www.coursera.org/learn/python-data-visualization) | - | 9 | | | |\n| Python | [**Python 3 Programming**](https://www.coursera.org/specializations/python-3-programming) | Bgn. | 121 | ○ | △ | University of Michigan |\n| | \u0026nbsp;\u0026nbsp;· [Python Basics](https://www.coursera.org/learn/python-basics) | Bgn. | 36 | | ○ | |\n| | \u0026nbsp;\u0026nbsp;· [Python Functions, Files, and Dictionaries](https://www.coursera.org/learn/python-functions-files-dictionaries) | Bgn. | 31 | | ○ | |\n| | \u0026nbsp;\u0026nbsp;· [Data Collection and Processing with Python](https://www.coursera.org/learn/data-collection-processing-python) | Itm. | 16 | | ○ | |\n| | \u0026nbsp;\u0026nbsp;· [Python Classes and Inheritance](https://www.coursera.org/learn/python-classes-inheritance) | Itm. | 18 | | × | |\n| | \u0026nbsp;\u0026nbsp;· [Python Project: pillow, tesseract, and opencv](https://www.coursera.org/learn/python-project) | Itm. | 20 | | × | |\n| Python | [**Programming in Python: A Hands-on Introduction**](https://www.coursera.org/specializations/hands-on-python) | Bgn. | 40 | ○ | × | Codio |\n| | \u0026nbsp;\u0026nbsp;· [Python Basics: Selection and Iteration](https://www.coursera.org/learn/codio-python-basics) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Python Basic Structures: Lists, Strings, and Files](https://www.coursera.org/learn/python-basic-structures-lists-strings-and-files) | Bgn. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Python Object Basics: Functions, Recursion, and Objects](https://www.coursera.org/learn/python-object-basics) | Itm. | 11 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Object-Oriented Python: Inheritance and Encapsulation](https://www.coursera.org/learn/object-oriented-python) | Itm. | 10 | | | |\n| Python AWS NoSQL | [**Modern Application Development with Python on AWS**](https://www.coursera.org/specializations/aws-python-serverless-development) | Bgn. | 51 | ○ | × | Amazon Web Services |\n| | \u0026nbsp;\u0026nbsp;· [AWS Cloud Technical Essentials](https://www.coursera.org/learn/aws-cloud-technical-essentials) | Bgn. | 16 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Building Modern Python Applications on AWS](https://www.coursera.org/learn/building-modern-python-applications-on-aws) | Itm. | 20 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Amazon DynamoDB: Building NoSQL Database-Driven Applications](https://www.coursera.org/learn/dynamodb-nosql-database-driven-apps) | Itm. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Improve Your Python Code Using Amazon CodeGuru](https://www.coursera.org/learn/aws-improve-python-code-amazon-codeguru) | Itm. | 5 | | | |\n| Python Bash SQL | [**Python, Bash and SQL Essentials for Data Engineering**](https://www.coursera.org/specializations/python-bash-sql-data-engineering-duke) | Bgn. | 94 | ○ | × | Duke University |\n| | \u0026nbsp;\u0026nbsp;· [Python and Pandas for Data Engineering](https://www.coursera.org/learn/python-and-pandas-for-data-engineering-duke) | Bgn. | 38 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Linux and Bash for Data Engineering](https://www.coursera.org/learn/linux-and-bash-for-data-engineering-duke) | Itm. | 22 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Scripting with Python and SQL for Data Engineering](https://www.coursera.org/learn/scripting-with-python-sql-for-data-engineering-duke) | Itm. | 19 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Web Applications and Command-Line Tools for Data Engineering](https://www.coursera.org/learn/web-app-command-line-tools-for-data-engineering-duke) | Itm. | 15 | | | |\n| Python DevOps | [**Python Scripting for DevOps**](https://www.coursera.org/specializations/python-scripting-devops) | Bgn. | 59 | ○ | × | LearnQuest |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Python Scripting for DevOps](https://www.coursera.org/learn/python-scripting-intro) | Bgn. | 18 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Python Scripting: Dates, Classes and Collections](https://www.coursera.org/learn/python-scripting-dates-classes-collections) | Bgn. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Python Scripting: Files, Inheritance, and Databases](https://www.coursera.org/learn/python-scripting-files-inheritance-databases) | Bgn. | 13 | | | |\n| | \u0026nbsp;\u0026nbsp;· [DevOps and Build Automation with Python](https://www.coursera.org/learn/devops-build-automation-python) | Bgn. | 13 | | | |\n| Python Django | [**Django for Everybody**](https://www.coursera.org/specializations/django) | Itm. | 63 | ○ | × | University of Michigan |\n| | \u0026nbsp;\u0026nbsp;· [Web Application Technologies and Django](https://www.coursera.org/learn/django-database-web-apps) | Itm. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Building Web Applications in Django](https://www.coursera.org/learn/django-build-web-apps) | Itm. | 13 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Django Features and Libraries](https://www.coursera.org/learn/django-features-libraries) | Itm. | 16 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Using JavaScript, JQuery, and JSON in Django](https://www.coursera.org/learn/django-javascript-jquery-json) | Itm. | 19 | | | |\n| Python Django | [**Advanced Django: Mastering Django and Django Rest Framework**](https://www.coursera.org/specializations/codio-advanced-django-and-django-rest-framework) | Adv. | 37 | ○ | × | Codio |\n| | \u0026nbsp;\u0026nbsp;· [Advanced Django: Building a Blog](https://www.coursera.org/learn/codio-advanced-django-building-blog) | Adv. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Advanced Django: Introduction to Django Rest Framework](https://www.coursera.org/learn/codio-advanced-django-intro-drf) | Adv. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Advanced Django: Advanced Django Rest Framework](https://www.coursera.org/learn/codio-advanced-django-advanced-drf) | Adv. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Advanced Django: External APIs and Task Queuing](https://www.coursera.org/learn/codio-advanced-django-external-apis-task-queuing) | Adv. | 9 | | | |\n\n\n## [Coursera / Specialization : Data Structure \u0026 Algorithms](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| Data Structure \u0026 Algorithms (Any Languages) | [**Data Structures and Algorithms**](https://www.coursera.org/specializations/data-structures-algorithms) | Itm. | 184 | ○ | × | University of California San Diego |\n| | \u0026nbsp;\u0026nbsp;· [Algorithmic Toolbox](https://www.coursera.org/learn/algorithmic-toolbox) | Itm. | 40 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Structures](https://www.coursera.org/learn/data-structures) | Itm. | 25 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Algorithms on Graphs](https://www.coursera.org/learn/algorithms-on-graphs) | Itm. | 55 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Algorithms on Strings](https://www.coursera.org/learn/algorithms-on-strings) | Itm. | 19 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Advanced Algorithms and Complexity](https://www.coursera.org/learn/advanced-algorithms-and-complexity) | Adv. | 27 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Genome Assembly Programming Challenge](https://www.coursera.org/learn/assembling-genomes) | Adv. | 18 | | | |\n| Data Structure \u0026 Algorithms (Any Languages) | [**Algorithms**](https://www.coursera.org/specializations/algorithms) | Itm. | 61 | × | × | Stanford University |\n| | \u0026nbsp;\u0026nbsp;· [Divide and Conquer, Sorting and Searching, and Randomized Algorithms](https://www.coursera.org/learn/algorithms-divide-conquer) | Itm. | 17 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Graph Search, Shortest Paths, and Data Structures](https://www.coursera.org/learn/algorithms-graphs-data-structures) | Itm. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming](https://www.coursera.org/learn/algorithms-greedy) | Itm. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Shortest Paths Revisited, NP-Complete Problems and What To Do About Them](https://www.coursera.org/learn/algorithms-npcomplete) | Itm. | 14 | | | |\n| Data Structure \u0026 Algorithms (Python) | [**Data Science Foundations: Data Structures and Algorithms**](https://www.coursera.org/specializations/boulder-data-structures-algorithms) | Adv. | 106 | ○ | × | University of Colorado Boulder |\n| | \u0026nbsp;\u0026nbsp;· [Algorithms for Searching, Sorting, and Indexing](https://www.coursera.org/learn/algorithms-searching-sorting-indexing) | Itm. | 34 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Trees and Graphs: Basics](https://www.coursera.org/learn/trees-graphs-basics) | Adv. | 34 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Dynamic Programming, Greedy Algorithms](https://www.coursera.org/learn/dynamic-programming-greedy-algorithms) | Adv. | 38 | | | |\n| Data Structure \u0026 Algorithms (Any Languages) | [**Data Structures and Algorithms**](https://www.coursera.org/specializations/data-structures-algorithms-tsinghua) | Itm. | 115 | ○ | × | Tsinghua University |\n| | \u0026nbsp;\u0026nbsp;· [Data Structures and Algorithms (I)](https://www.coursera.org/learn/data-structures-algorithms-1) | Itm. | 26 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Structures and Algorithms (II)](https://www.coursera.org/learn/data-structures-algorithms-2) | Itm. | 37 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Structures and Algorithms (III)](https://www.coursera.org/learn/data-structures-algorithms-3) | Itm. | 27 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Structures and Algorithms (IV)](https://www.coursera.org/learn/data-structures-algorithms-4) | Itm. | 25 | | | |\n\n\n## [Coursera / Specialization : Cloud - AWS](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| AWS | [**AWS Fundamentals**](https://www.coursera.org/specializations/aws-fundamentals) | Bgn. | 39 | ○ | △ | Amazon Web Services |\n| | \u0026nbsp;\u0026nbsp;· [AWS Cloud Technical Essentials](https://www.coursera.org/learn/aws-cloud-technical-essentials) | Bgn. | 16 | | × | |\n| | \u0026nbsp;\u0026nbsp;· [AWS Fundamentals: Addressing Security Risk](https://www.coursera.org/learn/aws-fundamentals-addressing-security-risk) | Bgn. | 7 | | × | |\n| | \u0026nbsp;\u0026nbsp;· [AWS Fundamentals: Migrating to the Cloud](https://www.coursera.org/learn/aws-fundamentals-cloud-migration) | Itm. | 4 | | ○ | |\n| | \u0026nbsp;\u0026nbsp;· [AWS Fundamentals: Building Serverless Applications](https://www.coursera.org/learn/aws-fundamentals-building-serverless-applications) | Bgn. | 12 | | ○ | |\n| AWS .NET | [**Modern Application Development with .NET on AWS**](https://www.coursera.org/specializations/aws-net-serverless-development) | Bgn. | 44 | ○ | × | Amazon Web Services |\n| | \u0026nbsp;\u0026nbsp;· [AWS Cloud Technical Essentials](https://www.coursera.org/learn/aws-cloud-technical-essentials) | Bgn. | 16 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Building Modern .NET Applications on AWS](https://www.coursera.org/learn/aws-building-modern-net-applications) | Itm. | 18 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Amazon DynamoDB: Building NoSQL Database-Driven Applications](https://www.coursera.org/learn/dynamodb-nosql-database-driven-apps) | Itm. | 10 | | | |\n| AWS Java | [**Modern Application Development with Java on AWS**](https://www.coursera.org/specializations/aws-java-serverless-development) | Bgn. | 51 | ○ | × | Amazon Web Services |\n| | \u0026nbsp;\u0026nbsp;· [AWS Cloud Technical Essentials](https://www.coursera.org/learn/aws-cloud-technical-essentials) | Bgn. | 16 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Building Modern Java Applications on AWS](https://www.coursera.org/learn/building-modern-java-applications-on-aws) | Itm. | 19 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Amazon DynamoDB: Building NoSQL Database-Driven Applications](https://www.coursera.org/learn/dynamodb-nosql-database-driven-apps) | Itm. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Improve Your Java Code Using Amazon CodeGuru](https://www.coursera.org/learn/aws-improve-java-code-amazon-codeguru) | Itm. | 6 | | | |\n| AWS Node.js | [**Modern Application Development with Node.js on AWS**](https://www.coursera.org/specializations/aws-nodejs-serverless-development) | Bgn. | 45 | ○ | × | Amazon Web Services |\n| | \u0026nbsp;\u0026nbsp;· [AWS Cloud Technical Essentials](https://www.coursera.org/learn/aws-cloud-technical-essentials) | Bgn. | 16 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Building Modern Node.js Applications on AWS](https://www.coursera.org/learn/building-modern-node-applications-on-aws) | Itm. | 19 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Amazon DynamoDB: Building NoSQL Database-Driven Applications](https://www.coursera.org/learn/dynamodb-nosql-database-driven-apps) | Itm. | 10 | | | |\n| AWS Python | [**Modern Application Development with Python on AWS**](https://www.coursera.org/specializations/aws-python-serverless-development) | Bgn. | 51 | ○ | × | Amazon Web Services |\n| | \u0026nbsp;\u0026nbsp;· [AWS Cloud Technical Essentials](https://www.coursera.org/learn/aws-cloud-technical-essentials) | Bgn. | 16 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Building Modern Python Applications on AWS](https://www.coursera.org/learn/building-modern-python-applications-on-aws) | Itm. | 20 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Amazon DynamoDB: Building NoSQL Database-Driven Applications](https://www.coursera.org/learn/dynamodb-nosql-database-driven-apps) | Itm. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Improve Your Python Code Using Amazon CodeGuru](https://www.coursera.org/learn/aws-improve-python-code-amazon-codeguru) | Itm. | 5 | | | |\n| AWS DevOps | [**DevOps on AWS**](https://www.coursera.org/specializations/aws-devops) | Itm. | 31 | ○ | × | Amazon Web Services |\n| | \u0026nbsp;\u0026nbsp;· [AWS Cloud Technical Essentials](https://www.coursera.org/learn/aws-cloud-technical-essentials) | Bgn. | 16 | | | |\n| | \u0026nbsp;\u0026nbsp;· [DevOps on AWS: Code, Build, and Test](https://www.coursera.org/learn/devops-aws-code-build-test) | Itm. | 5 | | | |\n| | \u0026nbsp;\u0026nbsp;· [DevOps on AWS: Release and Deploy](https://www.coursera.org/learn/devops-aws-release-deploy) | Itm. | 5 | | | |\n| | \u0026nbsp;\u0026nbsp;· [DevOps on AWS: Operate and Monitor](https://www.coursera.org/learn/devops-aws-operate-monitor) | Itm. | 5 | | | |\n| AWS\u003cbr\u003eData Science | [**Practical Data Science on the AWS Cloud**](https://www.coursera.org/specializations/practical-data-science) | Adv. | 47 | × | × | Amazon Web Services\u003cbr\u003eDeepLearning.AI |\n| | \u0026nbsp;\u0026nbsp;· [Analyze Datasets and Train ML Models using AutoML](https://www.coursera.org/learn/automl-datasets-ml-models) | Adv. | 19 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Build, Train, and Deploy ML Pipelines using BERT](https://www.coursera.org/learn/ml-pipelines-bert) | Adv. | 14 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Optimize ML Models and Deploy Human-in-the-Loop Pipelines](https://www.coursera.org/learn/ml-models-human-in-the-loop-pipelines) | Adv. | 14 | | | |\n\n\n## [Coursera / Specialization : Cloud - Azure](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| Microsoft Azure | [**Microsoft Azure Fundamentals AZ-900 Exam Prep**](https://www.coursera.org/specializations/microsoft-azure-fundamentals-az-900) | Bgn. | 32 | ○ | × | Microsoft |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Microsoft Azure Cloud Services](https://www.coursera.org/learn/microsoft-azure-cloud-services) | Bgn. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Microsoft Azure Management Tools and Security Solutions](https://www.coursera.org/learn/microsoft-azure-management-security) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Microsoft Azure Services and Lifecycles](https://www.coursera.org/learn/microsoft-azure-services-lifecycles) | Bgn. | 7 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Preparing for the AZ-900 Microsoft Azure Fundamentals Exam](https://www.coursera.org/learn/az-900-exam-prep) | Bgn. | 6 | | | |\n| Microsoft Azure | [**Microsoft Azure Data Fundamentals DP-900 Exam Prep**](https://www.coursera.org/specializations/microsoft-azure-dp-900-data-fundamentals) | Bgn. | 37 | ○ | × | Microsoft |\n| | \u0026nbsp;\u0026nbsp;· [Explore Core Data Concepts in Microsoft Azure](https://www.coursera.org/learn/explore-core-data-concepts-microsoft-azure) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Microsoft Azure SQL](https://www.coursera.org/learn/microsoft-azure-sql) | Bgn. | 7 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Microsoft Azure Cosmos DB](https://www.coursera.org/learn/microsoft-azure-cosmos-db) | Bgn. | 11 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Modern Data Warehouse Analytics in Microsoft Azure](https://www.coursera.org/learn/data-warehouse-analytics-microsoft-azure) | Bgn. | 4 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Preparing for DP-900: Microsoft Azure Data Fundamentals Exam](https://www.coursera.org/learn/microsoft-dp-900-exam-prep) | Bgn. | 6 | | | |\n| Microsoft Azure | [**Microsoft Azure AI Fundamentals AI-900 Exam Prep**](https://www.coursera.org/specializations/microsoft-azure-ai-900-ai-fundamentals) | Bgn. | 41 | ○ | × | Microsoft |\n| | \u0026nbsp;\u0026nbsp;· [Artificial Intelligence on Microsoft Azure](https://www.coursera.org/learn/artificial-intelligence-microsoft-azure) | Bgn. | 4 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Microsoft Azure Machine Learning](https://www.coursera.org/learn/microsoft-azure-machine-learning) | Bgn. | 11 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Computer Vision in Microsoft Azure](https://www.coursera.org/learn/computer-vision-microsoft-azure) | Bgn. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Natural Language Processing in Microsoft Azure](https://www.coursera.org/learn/nlp-microsoft-azure) | Bgn. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Preparing for AI-900: Microsoft Azure AI Fundamentals exam](https://www.coursera.org/learn/microsoft-ai-900-exam-prep) | Bgn. | 10 | | | |\n\n\n## [Coursera / Specialization : Cloud - GCP](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| GCP | [**Developing Applications with Google**](https://www.coursera.org/specializations/developing-apps-gcp) | Itm. | 51 | ○ | × | Google Cloud |\n| | \u0026nbsp;\u0026nbsp;· [Google Cloud Fundamentals: Core Infrastructure](https://www.coursera.org/learn/gcp-fundamentals) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Getting Started With Application Development](https://www.coursera.org/learn/getting-started-app-development) | Itm. | 18 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Securing and Integrating Components of your Application](https://www.coursera.org/learn/securing-integrating-components-app) | Itm. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [App Deployment, Debugging, and Performance](https://www.coursera.org/learn/app-deployment-debugging-performance) | Itm. | 9 | | | |\n| GCP | [**Data Engineering, Big Data, and Machine Learning on GCP**](https://www.coursera.org/specializations/gcp-data-machine-learning) | Itm. | 50 | ○ | × | Google Cloud |\n| | \u0026nbsp;\u0026nbsp;· [Google Cloud Big Data and Machine Learning Fundamentals](https://www.coursera.org/learn/gcp-big-data-ml-fundamentals) | Bgn. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Modernizing Data Lakes and Data Warehouses with Google Cloud](https://www.coursera.org/learn/data-lakes-data-warehouses-gcp) | Itm. | 7 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Building Batch Data Pipelines on GCP](https://www.coursera.org/learn/batch-data-pipelines-gcp) | Itm. | 17 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Building Resilient Streaming Analytics Systems on Google Cloud](https://www.coursera.org/learn/streaming-analytics-systems-gcp) | Itm. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Smart Analytics, Machine Learning, and AI on GCP](https://www.coursera.org/learn/smart-analytics-machine-learning-ai-gcp) | Itm. | 8 | | | |\n| GCP | [**Advanced Machine Learning on Google Cloud**](https://www.coursera.org/specializations/advanced-machine-learning-tensorflow-gcp) | Adv. | 74 | ○ | × | Google Cloud |\n| | \u0026nbsp;\u0026nbsp;· [End-to-End Machine Learning with TensorFlow on GCP](https://www.coursera.org/learn/end-to-end-ml-tensorflow-gcp) | Adv. | 13 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Production Machine Learning Systems](https://www.coursera.org/learn/gcp-production-ml-systems) | Adv. | 21 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Image Understanding with TensorFlow on GCP](https://www.coursera.org/learn/image-understanding-tensorflow-gcp) | Adv. | 12 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Sequence Models for Time Series and Natural Language Processing](https://www.coursera.org/learn/sequence-models-tensorflow-gcp) | Adv. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Recommendation Systems with TensorFlow on GCP](https://www.coursera.org/learn/recommendation-models-gcp) | Adv. | 13 | | | |\n| GCP | [**Developing APIs with Google Cloud's Apigee API Platform**](https://www.coursera.org/specializations/apigee-api-gcp) | Itm. | 31 | ○ | × | Google Cloud |\n| | \u0026nbsp;\u0026nbsp;· [API Design and Fundamentals of Google Cloud's Apigee API Platform](https://www.coursera.org/learn/api-design-apigee-gcp) | Bgn. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [API Security on Google Cloud's Apigee API Platform](https://www.coursera.org/learn/api-security-apigee-gcp) | Bgn. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [API Development on Google Cloud's Apigee API Platform](https://www.coursera.org/learn/api-development-apigee-gcp) | Bgn. | 15 | | | |\n\n\n## [Coursera / Specialization : Game Programming](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| Unity | [**C# Programming for Unity Game Development**](https://www.coursera.org/specializations/programming-unity-game-development) | Bgn. | 123 | ○ | × | University of Colorado System |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to C# Programming and Unity](https://www.coursera.org/learn/introduction-programming-unity) | Bgn. | 19 | | | |\n| | \u0026nbsp;\u0026nbsp;· [More C# Programming and Unity](https://www.coursera.org/learn/more-programming-unity) | Itm. | 22 | | | |\n| | \u0026nbsp;\u0026nbsp;· [C# Class Development](https://www.coursera.org/learn/csharp-class-development) | Itm. | 28 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Intermediate Object-Oriented Programming for Unity Games](https://www.coursera.org/learn/intermediate-object-oriented-programming-unity-games) | Itm. | 54 | | | |\n| Unity | [**Game Design and Development with Unity 2020**](https://www.coursera.org/specializations/game-design-and-development) | Bgn. | 71 | ○ | × | Michigan State University |\n| | \u0026nbsp;\u0026nbsp;· [Game Design and Development 1: 2D Shooter](https://www.coursera.org/learn/game-design-and-development-1) | Bgn. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Game Design and Development 2: 2D Platformer](https://www.coursera.org/learn/game-design-and-development-2) | Itm. | 12 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Game Design and Development 3: 3D Shooter](https://www.coursera.org/learn/game-design-and-development-3) | Itm. | 14 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Game Design and Development 4: 3D Platformer](https://www.coursera.org/learn/game-design-and-development-4) | Itm. | 13 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Game Design and Development 5: Capstone Project](https://www.coursera.org/learn/game-design-and-development-5) | Itm. | 17 | | | |\n| Unreal | [**C++ Programming for Unreal Game Development**](https://www.coursera.org/specializations/cplusplusunrealgamedevelopment) | Itm. | 72 | ○ | × | University of Colorado System |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to C++ Programming and Unreal](https://www.coursera.org/learn/introductionprogrammingunreal) | Itm. | 20 | | | |\n| | \u0026nbsp;\u0026nbsp;· [More C++ Programming and Unreal](https://www.coursera.org/learn/more-programming-unreal) | Itm. | 18 | | | |\n| | \u0026nbsp;\u0026nbsp;· [C++ Class Development](https://www.coursera.org/learn/cpp-class-development) | Itm. | 18 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Intermediate Object-Oriented Programming for Unreal Games](https://www.coursera.org/learn/intermediate-object-oriented-programming--unreal-games) | Itm. | 16 | | | |\n| Game Design | [**Game Design: Art and Concepts**](https://www.coursera.org/specializations/game-design) | Bgn. | 51 | ○ | × | California Institute of the Arts |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Game Design](https://www.coursera.org/learn/game-design) | Bgn. | 6 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Story and Narrative Development for Video Games](https://www.coursera.org/learn/video-game-story) | Bgn. | 12 | | | |\n| | \u0026nbsp;\u0026nbsp;· [World Design for Video Games](https://www.coursera.org/learn/video-game-world) | Bgn. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Character Design for Video Games](https://www.coursera.org/learn/game-character-design) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Game Design Document: Define the Art \u0026 Concepts](https://www.coursera.org/learn/game-design-document) | Itm. | 16 | | | |\n| Game Design | [**Art for Games**](https://www.coursera.org/specializations/art-for-games) | Bgn. | 47 | ○ | × | Michigan State University |\n| | \u0026nbsp;\u0026nbsp;· [Pixel Art for Video Games](https://www.coursera.org/learn/pixel-art-video-games) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Low Poly Art For Video Games](https://www.coursera.org/learn/low-poly-art-video-games) | Itm. | 17 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Current Gen 3D Game Prop Production](https://www.coursera.org/learn/3d-game-prop-production) | Itm. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Concept Art for Video Games](https://www.coursera.org/learn/concept-art-video-games) | - | 6 | | | |\n\n\n## [Coursera / Specialization : Mathematics](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| Math | [**Algebra: Elementary to Advanced**](https://www.coursera.org/specializations/algebra-elementary-to-advanced) | Bgn. | 25 | ○ | × | Johns Hopkins University |\n| | \u0026nbsp;\u0026nbsp;· [Algebra: Elementary to Advanced - Equations \u0026 Inequalities](https://www.coursera.org/learn/algebra-i) | Bgn. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Algebra: Elementary to Advanced - Functions \u0026 Applications](https://www.coursera.org/learn/algebra-ii) | Bgn. | 6 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Algebra: Elementary to Advanced - Polynomials and Roots](https://www.coursera.org/learn/polynomials-roots) | Bgn. | 9 | | | |\n| Math Python | [**Mathematics for Machine Learning**](https://www.coursera.org/specializations/mathematics-machine-learning) | Bgn. | 55 | ○ | × | Imperial College London |\n| | \u0026nbsp;\u0026nbsp;· [Mathematics for Machine Learning: Linear Algebra](https://www.coursera.org/learn/linear-algebra-machine-learning) | Bgn. | 19 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Mathematics for Machine Learning: Multivariate Calculus](https://www.coursera.org/learn/multivariate-calculus-machine-learning) | Bgn. | 18 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Mathematics for Machine Learning: PCA](https://www.coursera.org/learn/pca-machine-learning) | Itm. | 18 | | | |\n| Math | [**Expressway to Data Science: Essential Math**](https://www.coursera.org/specializations/expressway-to-data-science-essential-math)\u003cbr\u003e* [Associated with the Master of Science in Data Science degree](https://www.coursera.org/degrees/master-of-science-data-science-boulder) | Itm. | 20 | ○ | × | University of Colorado Boulder |\n| | \u0026nbsp;\u0026nbsp;· [Algebra and Differential Calculus for Data Science](https://www.coursera.org/learn/algebra-and-differential-calculus-for-data-science) | Itm. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Essential Linear Algebra for Data Science](https://www.coursera.org/learn/essential-linear-algebra-for-data-science) | Itm. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Integral Calculus and Numerical Analysis for Data Science](https://www.coursera.org/learn/integral-calculus-and-numerical-analysis-for-data-science) | Itm. | 4 | | | |\n| Math MATLAB | [**Mathematics for Engineers**](https://www.coursera.org/specializations/mathematics-engineers) | Bgn. | 127 | ○ | × | The Hong Kong University of Science and Technology |\n| | \u0026nbsp;\u0026nbsp;· [Matrix Algebra for Engineers](https://www.coursera.org/learn/matrix-algebra-engineers) | Bgn. | 20 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Differential Equations for Engineers](https://www.coursera.org/learn/differential-equations-engineers) | Bgn. | 27 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Vector Calculus for Engineers](https://www.coursera.org/learn/vector-calculus-engineers) | Bgn. | 28 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Numerical Methods for Engineers](https://www.coursera.org/learn/numerical-methods-engineers) | Itm. | 42 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Mathematics for Engineers: The Capstone Course](https://www.coursera.org/learn/mathematics-engineers-capstone) | Itm. | 10 | | | |\n| Math MATLAB | [**Practical Data Science with MATLAB**](https://www.coursera.org/specializations/practical-data-science-matlab) | Bgn. | 72 | ○ | × | MathWorks |\n| | \u0026nbsp;\u0026nbsp;· [Exploratory Data Analysis with MATLAB](https://www.coursera.org/learn/exploratory-data-analysis-matlab) | Bgn. | 19 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Processing and Feature Engineering with MATLAB](https://www.coursera.org/learn/feature-engineering-matlab) | Itm. | 18 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Predictive Modeling and Machine Learning with MATLAB](https://www.coursera.org/learn/predictive-modeling-machine-learning) | Itm. | 22 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Science Project: MATLAB for the Real World](https://www.coursera.org/learn/matlab-capstone) | Itm. | 13 | | | |\n\n\n## [Coursera / Specialization : Statistics](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| Excel | [**Business Statistics and Analysis**](https://www.coursera.org/specializations/business-statistics-analysis) | Bgn. | 101 | ○ | × | Rice University |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Data Analysis Using Excel](https://www.coursera.org/learn/excel-data-analysis) | - | 20 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions](https://www.coursera.org/learn/descriptive-statistics-statistical-distributions-business-application) | - | 21 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Business Applications of Hypothesis Testing and Confidence Interval Estimation](https://www.coursera.org/learn/hypothesis-testing-confidence-intervals) | - | 25 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Linear Regression for Business Statistics](https://www.coursera.org/learn/linear-regression-business-statistics) | - | 28 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Business Statistics and Analysis Capstone](https://www.coursera.org/learn/business-statistics-analysis-capstone) | - | 7 | | | |\n| Python | [**Statistics with Python**](https://www.coursera.org/specializations/statistics-with-python) | Bgn. | 55 | ○ | ○ | University of Michigan |\n| | \u0026nbsp;\u0026nbsp;· [Understanding and Visualizing Data with Python](https://www.coursera.org/learn/understanding-visualization-data) | Bgn. | 21 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Inferential Statistical Analysis with Python](https://www.coursera.org/learn/inferential-statistical-analysis-python) | Itm. | 19 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Fitting Statistical Models to Data with Python](https://www.coursera.org/learn/fitting-statistical-models-data-python) | Itm. | 15 | | | |\n| R | [**Data Science: Statistics and Machine Learning**](https://www.coursera.org/specializations/data-science-statistics-machine-learning) | Itm. | 133 | ○ | ○ | Johns Hopkins University |\n| | \u0026nbsp;\u0026nbsp;· [Statistical Inference](https://www.coursera.org/learn/statistical-inference) | - | 54 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Regression Models](https://www.coursera.org/learn/regression-models) | - | 54 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Practical Machine Learning](https://www.coursera.org/learn/practical-machine-learning) | - | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Developing Data Products](https://www.coursera.org/learn/data-products) | - | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Science Capstone](https://www.coursera.org/learn/data-science-project) | - | 6 | | | |\n| R | [**Bayesian Statistics Specialization**](https://www.coursera.org/specializations/bayesian-statistics) | Itm. | 98 | ○ | × | University of California, Santa Cruz |\n| | \u0026nbsp;\u0026nbsp;· [Bayesian Statistics: From Concept to Data Analysis](https://www.coursera.org/learn/bayesian-statistics) | Itm. | 12 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Bayesian Statistics: Techniques and Models](https://www.coursera.org/learn/mcmc-bayesian-statistics) | Itm. | 30 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Bayesian Statistics: Mixture Models](https://www.coursera.org/learn/mixture-models) | Itm. | 22 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Bayesian Statistics: Time Series Analysis](https://www.coursera.org/learn/bayesian-statistics-time-series-analysis) | Itm. | 22 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Bayesian Statistics: Capstone Project](https://www.coursera.org/learn/bayesian-statistics-capstone) | Adv. | 12 | | | |\n| R | [**Advanced Statistics for Data Science**](https://www.coursera.org/specializations/advanced-statistics-data-science) | Adv. | 39 | ○ | × | Johns Hopkins University |\n| | \u0026nbsp;\u0026nbsp;· [Mathematical Biostatistics Boot Camp 1](https://www.coursera.org/learn/biostatistics) | - | 13 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Mathematical Biostatistics Boot Camp 2](https://www.coursera.org/learn/biostatistics-2) | - | 12 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Advanced Linear Models for Data Science 1: Least Squares](https://www.coursera.org/learn/linear-models) | Adv. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Advanced Linear Models for Data Science 2: Statistical Linear Models](https://www.coursera.org/learn/linear-models-2) | Adv. | 6 | | | |\n\n\n## [Coursera / Specialization : Data Science - Python](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| Python | [**Applied Data Science with Python**](https://www.coursera.org/specializations/data-science-python) | Itm. | 143 | ○ | ○ | University of Michigan |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to Data Science in Python](https://www.coursera.org/learn/python-data-analysis) | Itm. | 31 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Applied Plotting, Charting \u0026 Data Representation in Python](https://www.coursera.org/learn/python-plotting) | Itm. | 20 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Applied Machine Learning in Python](https://www.coursera.org/learn/python-machine-learning) | Itm. | 34 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Applied Text Mining in Python](https://www.coursera.org/learn/python-text-mining) | Itm. | 29 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Applied Social Network Analysis in Python](https://www.coursera.org/learn/python-social-network-analysis) | Itm. | 29 | | | |\n| Python | [**Data Science Fundamentals with Python and SQL**](https://www.coursera.org/specializations/data-science-fundamentals-python-sql) | Bgn. | 101 | × | △ | IBM |\n| | \u0026nbsp;\u0026nbsp;· [Tools for Data Science](https://www.coursera.org/learn/open-source-tools-for-data-science) | Bgn. | 20 | | × | |\n| | \u0026nbsp;\u0026nbsp;· [Python for Data Science, AI \u0026 Development](https://www.coursera.org/learn/python-for-applied-data-science-ai) | Bgn. | 22 | | ○ | |\n| | \u0026nbsp;\u0026nbsp;· [Python Project for Data Science](https://www.coursera.org/learn/python-project-for-data-science) | Itm. | 8 | | × | |\n| | \u0026nbsp;\u0026nbsp;· [Statistics for Data Science with Python](https://www.coursera.org/learn/statistics-for-data-science-python) | - | 14 | | × | |\n| (SQL) | \u0026nbsp;\u0026nbsp;· [Databases and SQL for Data Science with Python](https://www.coursera.org/learn/sql-data-science) | Bgn. | 37 | | × | |\n| Python | [**Applied Data Science**](https://www.coursera.org/specializations/applied-data-science) | Bgn. | 69 | × | △ | IBM |\n| | \u0026nbsp;\u0026nbsp;· [Python for Data Science, AI \u0026 Development](https://www.coursera.org/learn/python-for-applied-data-science-ai) | Bgn. | 19 | | ○ | |\n| | \u0026nbsp;\u0026nbsp;· [Python Project for Data Science](https://www.coursera.org/learn/python-project-for-data-science) | Itm. | 7 | | ○ | |\n| | \u0026nbsp;\u0026nbsp;· [Data Analysis with Python](https://www.coursera.org/learn/data-analysis-with-python) | Bgn. | 15 | | × | |\n| | \u0026nbsp;\u0026nbsp;· [Data Visualization with Python](https://www.coursera.org/learn/python-for-data-visualization) | Itm. | 17 | | ○ | |\n| | \u0026nbsp;\u0026nbsp;· [Applied Data Science Capstone](https://www.coursera.org/learn/applied-data-science-capstone) | Itm. | 11 | | × | |\n\n\n## [Coursera / Specialization : Data Science - R](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| R | [**Data Science: Foundations using R**](https://www.coursera.org/specializations/data-science-foundations-r) | Bgn. | 158 | ○ | ○ | Johns Hopkins University |\n| (Git) | \u0026nbsp;\u0026nbsp;· [The Data Scientist’s Toolbox](https://www.coursera.org/learn/data-scientists-tools) | - | 18 | | | |\n| | \u0026nbsp;\u0026nbsp;· [R Programming](https://www.coursera.org/learn/r-programming) | Itm. | 57 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Getting and Cleaning Data](https://www.coursera.org/learn/data-cleaning) | - | 20 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Exploratory Data Analysis](https://www.coursera.org/learn/exploratory-data-analysis) | - | 55 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Reproducible Research](https://www.coursera.org/learn/reproducible-research) | - | 8 | | | |\n| R | [**Data Visualization \u0026 Dashboarding with R**](https://www.coursera.org/specializations/jhu-data-visualization-dashboarding-with-r) | Bgn. | 70 | ○ | × | Johns Hopkins University |\n| | \u0026nbsp;\u0026nbsp;· [Getting Started with Data Visualization in R](https://www.coursera.org/learn/jhu-getting-started-data-viz-r) | Bgn. | 12 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Visualization in R with ggplot2](https://www.coursera.org/learn/jhu-data-visualization-r) | Itm. | 13 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Advanced Data Visualization with R](https://www.coursera.org/learn/jhu-advanced-data-visualization-r) | - | 11 | | | |\n| (Shiny) | \u0026nbsp;\u0026nbsp;· [Publishing Visualizations in R with Shiny and flexdashboard](https://www.coursera.org/learn/data-viz-shiny-dashboards) | - | 12 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Visualization Capstone](https://www.coursera.org/learn/data-visualization-capstone) | - | 22 | | | |\n| R | [**Applied Data Science with R**](https://www.coursera.org/specializations/applied-data-science-r) | Bgn. | 69 | × | × | IBM |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to R Programming for Data Science](https://www.coursera.org/learn/introducton-r-programming-data-science) | Bgn. | 11 | | | |\n| (SQL) | \u0026nbsp;\u0026nbsp;· [SQL for Data Science with R](https://www.coursera.org/learn/sql-data-science-r) | Bgn. | 17 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Analysis with R](https://www.coursera.org/learn/data-analysis-with-r) | Itm. | 15 | | | |\n| (Shiny) | \u0026nbsp;\u0026nbsp;· [Data Visualization with R](https://www.coursera.org/learn/data-visualization-r) | Bgn. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Science with R - Capstone Project](https://www.coursera.org/learn/data-science-with-r-capstone-project) | Itm. | 16 | | | |\n\n\n## [Coursera / Specialization : Data Science - SAS](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| SAS | [**Machine Learning Rock Star – the End-to-End Practice**](https://www.coursera.org/specializations/machine-learning-for-everyone) | Bgn. | 44 | | × | SAS |\n| | \u0026nbsp;\u0026nbsp;· [The Power of Machine Learning: Boost Business, Accumulate Clicks, Fight Fraud, and Deny Deadbeats](https://www.coursera.org/learn/the-power-of-machine-learning) | Bgn. | 14 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Launching Machine Learning: Delivering Operational Success with Gold Standard ML Leadership](https://www.coursera.org/learn/launching-machine-learning-leadership) | Bgn. | 13 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Machine Learning Under the Hood: The Technical Tips, Tricks, and Pitfalls](https://www.coursera.org/learn/machine-learning-under-the-hood) | Bgn. | 17 | | | |\n| SAS | [**Analyzing Time Series and Sequential Data**](https://www.coursera.org/specializations/time-series-sequential-data) | Itm. | 27 | | × | SAS |\n| | \u0026nbsp;\u0026nbsp;· [Creating Features for Time Series Data](https://www.coursera.org/learn/time-series-features) | Itm. | 7 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Building a Large-Scale, Automated Forecasting System](https://www.coursera.org/learn/large-scale-forecasting-sas-viya) | Itm. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Modeling Time Series and Sequential Data](https://www.coursera.org/learn/modeling-time-series-and-sequential-data) | Itm. | 10 | | | |\n| SAS | [**Distributed Programming in SAS® Viya® for Data Analysts**](https://www.coursera.org/specializations/distributed-programming-sas-viya-for-data-analysts) | Adv. | 54 | | × | SAS |\n| | \u0026nbsp;\u0026nbsp;· [SAS® Programming for Distributed Computing in SAS® Viya®](https://www.coursera.org/learn/sas-viya-programming-distributed-computing) | Adv. | 13 | | | |\n| | \u0026nbsp;\u0026nbsp;· [CASL Programming for Distributed Computing in SAS® Viya®](https://www.coursera.org/learn/casl-programming-sas-viya-distributed-computing) | Adv. | 29 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Preparing for the SAS® Viya® Programming Certification Exam](https://www.coursera.org/learn/sas-viya-programming-certification-prep) | Adv. | 12 | | | |\n\n\n## [Coursera / Specialization : Excel](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| Excel | [**Excel Skills for Business**](https://www.coursera.org/specializations/excel) | Bgn. | 106 | ○ | ○ | Macquarie University |\n| | \u0026nbsp;\u0026nbsp;· [Excel Skills for Business: Essentials](https://www.coursera.org/learn/excel-essentials) | Bgn. | 26 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Excel Skills for Business: Intermediate I](https://www.coursera.org/learn/excel-intermediate-1) | Itm. | 27 | | | |\n| (VBA) | \u0026nbsp;\u0026nbsp;· [Excel Skills for Business: Intermediate II](https://www.coursera.org/learn/excel-intermediate-2) | Itm. | 28 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Excel Skills for Business: Advanced](https://www.coursera.org/learn/excel-advanced) | Itm. | 25 | | | |\n| Excel | [**Excel Skills for Data Analytics and Visualization**](https://www.coursera.org/specializations/excel-data-analytics-visualization) | Itm. | 47 | ○ | ○ | Macquarie University |\n| | \u0026nbsp;\u0026nbsp;· [Excel Fundamentals for Data Analysis](https://www.coursera.org/learn/excel-data-analysis-fundamentals) | Itm. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Visualization in Excel](https://www.coursera.org/learn/excel-data-visualization) | Itm. | 17 | | | |\n| (Power BI) | \u0026nbsp;\u0026nbsp;· [Excel Power Tools for Data Analysis](https://www.coursera.org/learn/excel-power-tools) | Itm. | 15 | | | |\n| Excel | [**Excel Skills for Business Forecasting**](https://www.coursera.org/specializations/excel-skills-for-business-forecasting) | Itm. | 30 | ○ | ○ | Macquarie University |\n| | \u0026nbsp;\u0026nbsp;· [Excel Time Series Models for Business Forecasting](https://www.coursera.org/learn/excel-business-forecasting-time-series) | Itm. | 11 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Excel Regression Models for Business Forecasting](https://www.coursera.org/learn/excel-business-forecasting-regression) | Itm. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Judgmental Business Forecasting in Excel](https://www.coursera.org/learn/judgmental-business-forecasting-in-excel) | Itm. | 10 | | | |\n| Excel | [**Everyday Excel**](https://www.coursera.org/specializations/everyday-excel) | Bgn. | 59 | ○ | ○ | University of Colorado Boulder |\n| | \u0026nbsp;\u0026nbsp;· [Everyday Excel, Part 1](https://www.coursera.org/learn/everyday-excel-part-1) | Bgn. | 23 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Everyday Excel, Part 2](https://www.coursera.org/learn/everyday-excel-part-2) | Itm. | 22 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Everyday Excel, Part 3 (Projects)](https://www.coursera.org/learn/everyday-excel-projects) | Adv. | 14 | | | |\n| Excel\u003cbr\u003eVBA | [**Excel/VBA for Creative Problem Solving**](https://www.coursera.org/specializations/excel-vba-creative-problem-solving) | Bgn. | 55 | ○ | ○ | University of Colorado Boulder |\n| | \u0026nbsp;\u0026nbsp;· [Excel/VBA for Creative Problem Solving, Part 1](https://www.coursera.org/learn/excel-vba-for-creative-problem-solving-part-1) | Bgn. | 19 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Excel/VBA for Creative Problem Solving, Part 2](https://www.coursera.org/learn/excel-vba-for-creative-problem-solving-part-2) | Itm. | 20 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Excel/VBA for Creative Problem Solving, Part 3 (Projects)](https://www.coursera.org/learn/excel-vba-for-creative-problem-solving-part-3-projects) | Adv. | 16 | | | |\n| Excel | [**Data Analysis and Presentation Skills: the PwC Approach**](https://www.coursera.org/specializations/pwc-analytics) | Bgn. | 64 | × | ○ | PwC |\n| | \u0026nbsp;\u0026nbsp;· [Data-driven Decision Making](https://www.coursera.org/learn/decision-making) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Problem Solving with Excel](https://www.coursera.org/learn/excel-analysis) | Bgn. | 20 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Visualization with Advanced Excel](https://www.coursera.org/learn/advanced-excel) | Bgn. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Effective Business Presentations with Powerpoint](https://www.coursera.org/learn/powerpoint-presentations) | Bgn. | 10 | | | |\n| (PowerPoint) | \u0026nbsp;\u0026nbsp;· [Data Analysis and Presentation Skills: the PwC Approach Final Project](https://www.coursera.org/learn/data-analysis-project-pwc) | Bgn. | 10 | | | |\n| Excel | [**Data Skills for Excel Professionals**](https://www.coursera.org/specializations/data-skills-for-excel) | Bgn. | 14 | ○ | × | Corporate Finance Institute |\n| | \u0026nbsp;\u0026nbsp;· [Fundamentals of Data Analysis in Excel](https://www.coursera.org/learn/excel-data-analysis-course) | Bgn. | 5 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Power Query Fundamentals](https://www.coursera.org/learn/power-query-fundamentals) | Bgn. | 5 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Power Pivot Fundamentals](https://www.coursera.org/learn/learn-power-pivot) | Bgn. | 4 | | | |\n\n\n## [Coursera / Specialization : RPA](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| UiPath | [**Robotic Process Automation (RPA)**](https://www.coursera.org/specializations/roboticprocessautomation) | Bgn. | 48 | ○ | ○ | UiPath |\n| | \u0026nbsp;\u0026nbsp;· [RPA Basics and Introduction to UiPath](https://www.coursera.org/learn/rpa-basics-and-introduction-to-uipath) | Bgn. | 6 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Data Manipulation in RPA](https://www.coursera.org/learn/data-manipulation-in-rpa) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [UI Automation and Selectors](https://www.coursera.org/learn/ui-automation-and-selectors) | Bgn. | 8 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Control Flow in RPA](https://www.coursera.org/learn/control-flow-in-rpa) | Bgn. | 10 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Automation Techniques in RPA](https://www.coursera.org/learn/automation-techniques-in-rpa) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [UiPath Orchestrator and Capstone Projects](https://www.coursera.org/learn/uipath-orchestrator-and-capstone-projects) | Bgn. | 6 | | | |\n| Automation Anywhere | [**Implementing RPA with Cognitive Automation and Analytics**](https://www.coursera.org/specializations/rpa-cognitive-analytics) | Bgn. | 23 | × | ○ | Automation Anywhere |\n| | \u0026nbsp;\u0026nbsp;· [RPA Lifecycle: Introduction, Discovery and Design](https://www.coursera.org/learn/rpa-introduction) | Bgn. | 4 | | | |\n| | \u0026nbsp;\u0026nbsp;· [RPA Lifecycle: Development and Testing](https://www.coursera.org/learn/rpa-development-testing) | Bgn. | 9 | | | |\n| | \u0026nbsp;\u0026nbsp;· [RPA Lifecycle: Deployment and Maintenance](https://www.coursera.org/learn/rpa-deployment-maintenance) | Bgn. | 6 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Cognitive Solutions and RPA Analytics](https://www.coursera.org/learn/cognitive-solutions-rpa-analytics) | Bgn. | 4 | | | |\n\n\n## [Coursera / Specialization : Electronic Engineering](#list)\n\n(Bgn.: Beginner / Itm.: Intermediate / Adv.: Advanced)\n\n| Subject | Title | Level | Hours | Plus | Korean | Partner |\n|:-:|:--|:-:|--:|:-:|:-:|:-:|\n| Electromagnetism | [**Electrodynamics**](https://www.coursera.org/specializations/electrodynamics) | Itm. | 55 | ○ | × | Korea Advanced Institute of Science and Technology |\n| | \u0026nbsp;\u0026nbsp;· [Electrodynamics: An Introduction](https://www.coursera.org/learn/electrodynamics-introduction) | Itm. | 13 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Electrodynamics: Analysis of Electric Fields](https://www.coursera.org/learn/electrodynamics-analysis-of-electric-fields) | Adv. | 11 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Electrodynamics: Electric and Magnetic Fields](https://www.coursera.org/learn/electrodynamics-electric-magnetic-fields) | Adv. | 12 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Electrodynamics: In-depth Solutions for Maxwell’s Equations](https://www.coursera.org/learn/electrodynamics-solutions-maxwells-equations) | Adv. | 19 | | | |\n| Electromagnetism | [**Introduction to Electricity and Magnetism**](https://www.coursera.org/specializations/introduction-to-electricity-magnetism) | Itm. | 88 | ○ | × | Rice University |\n| | \u0026nbsp;\u0026nbsp;· [Physics 102 - Electric Charges and Fields](https://www.coursera.org/learn/physics-102-electric-charges-fields) | Itm. | 22 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Physics 102 - Electric Potential and DC Circuits](https://www.coursera.org/learn/physics-102-electric-potential-and-dc-circuits) | Itm. | 22 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Physics 102 - Magnetic Fields and Faraday's Law](https://www.coursera.org/learn/physics-102-magnetic-fields-faradays-law) | Itm. | 26 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Physics 102 - AC Circuits and Maxwell's Equations](https://www.coursera.org/learn/physics-102-ac-circuits-maxwell-equations) | Itm. | 18 | | | |\n| Semiconductor | [**Semiconductor Devices**](https://www.coursera.org/specializations/semiconductor-devices) | Adv. | 43 | ○ | × | University of Colorado Boulder |\n| | \u0026nbsp;\u0026nbsp;· [Semiconductor Physics](https://www.coursera.org/learn/semiconductor-physics) | Adv. | 15 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Diode - pn Junction and Metal Semiconductor Contact](https://www.coursera.org/learn/diode-pn-junction-metal-semiconductor-contact) | Adv. | 16 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Transistor - Field Effect Transistor and Bipolar Junction Transistor](https://www.coursera.org/learn/transistor-field-effect-transistor-bipolar-junction-transistor) | Adv. | 12 | | | |\n| Semiconductor\u003cbr\u003eVHDL Verilog | [**FPGA Design for Embedded Systems**](https://www.coursera.org/specializations/fpga-design) | Itm. | 93 | ○ | × | University of Colorado Boulder |\n| | \u0026nbsp;\u0026nbsp;· [Introduction to FPGA Design for Embedded Systems](https://www.coursera.org/learn/intro-fpga-design-embedded-systems) | Itm. | 18 | | | |\n| | \u0026nbsp;\u0026nbsp;· [Hardware","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkimpro82%2Fmoocoke","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkimpro82%2Fmoocoke","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkimpro82%2Fmoocoke/lists"}