https://github.com/cnoret/ibm-data-analyst-professional
Final project & Courses Notebooks
https://github.com/cnoret/ibm-data-analyst-professional
analyzing-data data-analysis data-analyst data-manipulation data-science data-visualization ibm ibm-certificate ibm-data-analyst-professional ibm-datascience-certification pandas python
Last synced: 24 days ago
JSON representation
Final project & Courses Notebooks
- Host: GitHub
- URL: https://github.com/cnoret/ibm-data-analyst-professional
- Owner: cnoret
- Created: 2024-10-13T19:23:34.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-03T14:52:38.000Z (over 1 year ago)
- Last Synced: 2025-05-30T23:21:34.439Z (about 1 year ago)
- Topics: analyzing-data, data-analysis, data-analyst, data-manipulation, data-science, data-visualization, ibm, ibm-certificate, ibm-data-analyst-professional, ibm-datascience-certification, pandas, python
- Language: Jupyter Notebook
- Homepage: https://lookerstudio.google.com/reporting/f3590499-4bec-426c-98a3-87702b88186c
- Size: 9.09 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
If my work has helped you, don't forget to click on the “ ⭐Star” button !
# IBM Data Analyst Professional (2024) 
## 📍 About the certificate
Prepare for a career as a data analyst. Build **job-ready skills** – and must-have **AI skills** – for an in-demand career.
In this program, you’ll learn in-demand skills like Python, Excel, and SQL to get job-ready in as little as 4 months, 10 hours a week.
---
## 🥇 Professional Certificate
---
## 📙 Course Structures
There are 11 Courses in this Professional Certificate Specialization are as follows:
- [x] [__Introduction to Data Analytics__](https://github.com/cnoret/IBM-data-analyst-professional/)
* Explain what Data Analytics is and the key steps in the Data Analytics process
* Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
* Describe the different types of data structures, file formats, and sources of data
* Describe the data analysis process involving collecting, wrangling, mining, and visualizing data
- [x] [__Excel Basics for Data Analysis__](https://github.com/cnoret/IBM-data-analyst-professional/)
* Display working knowledge of Excel for Data Analysis.
* Perform basic spreadsheet tasks including navigation, data entry, and using formulas.
* Employ data quality techniques to import and clean data in Excel.
* Analyze data in spreadsheets by using filter, sort, look-up functions, as well as pivot tables.
- [X] [__Data Visualization and Dashboards with Excel and Cognos__ ](https://github.com/cnoret/IBM-data-analyst-professional/)
* Create basic visualizations such as line graphs, bar graphs, and pie charts using Excel spreadsheets.
* Explain the important role charts play in telling a data-driven story.
* Construct advanced charts and visualizations such as Treemaps, Sparklines, Histogram, Scatter Plots, and Filled Map Charts.
* Build and share interactive dashboards using Excel and Cognos Analytics.
- [x] [__Python for Data Science, AI & Development__](https://github.com/cnoret/IBM-data-analyst-professional/)
* Learn Python - the most popular programming language and for Data Science and Software Development.
* Apply Python programming logic Variables, Data Structures, Branching, Loops, Functions, Objects & Classes.
* Demonstrate proficiency in using Python libraries such as Pandas & Numpy, and developing code using Jupyter Notebooks.
* Access and web scrape data using APIs and Python libraries like Beautiful Soup.
- [X] [__Python Project for Data Science__](https://github.com/cnoret/IBM-data-analyst-professional/)
* Play the role of a Data Scientist / Data Analyst working on a real project.
* Demonstrate your Skills in Python - the language of choice for Data Science and Data Analysis.
* Apply Python fundamentals, Python data structures, and working with data in Python.
* Build a dashboard using Python and libraries like Pandas, Beautiful Soup and Plotly using Jupyter notebook.
- [x] [__Databases and SQL for Data Science__](https://github.com/cnoret/IBM-data-analyst-professional/)
* Analyze data within a database using SQL and Python.
* Create a relational database and work with multiple tables using DDL commands.
* Construct basic to intermediate level SQL queries using DML commands.
* Compose more powerful queries with advanced SQL techniques like views, transactions, stored procedures, and joins.
- [x] [__Data Analysis with Python__](https://github.com/cnoret/IBM-data-analyst-professional/)
* Develop Python code for cleaning and preparing data for analysis - including handling missing values, formatting, normalizing, and binning data
* Perform exploratory data analysis and apply analytical techniques to real-word datasets using libraries such as Pandas, Numpy and Scipy
* Manipulate data using dataframes, summarize data, understand data distribution, perform correlation and create data pipelines
* Build and evaluate regression models using machine learning scikit-learn library and use them for prediction and decision making
- [x] [__Data Visualization with Python__](https://github.com/cnoret/IBM-data-analyst-professional/)
* Implement data visualization techniques and plots using Python libraries, such as Matplotlib, Seaborn, and Folium to tell a stimulating story
* Create different types of charts and plots such as line, area, histograms, bar, pie, box, scatter, and bubble
* Create advanced visualizations such as waffle charts, word clouds, regression plots, maps with markers, & choropleth maps
* Generate interactive dashboards containing scatter, line, bar, bubble, pie, and sunburst charts using the Dash framework and Plotly library
- [x] [__IBM Data Analyst Capstone Project__](https://github.com/cnoret/IBM-data-analyst-professional/)
* Apply different techniques to collect and wrangle data
* Showcase your Data Analysis and Visualization skills
* Create a data analysis report and a compelling presentation
* Demonstrate proficiency with various Python Libraries
- [x] [__Generative AI: Enhance your Data Analytics Career__](https://github.com/cnoret/IBM-data-analyst-professional/)
* Describe how you can use Generative AI tools and techniques in the context of data analytics across industries
* Implement various data analytic processes such as data preparation, analysis, visualization and storytelling using Generative AI tools
* Evaluate real-world case studies showcasing the successful application of Generative AI in deriving meaningful insights
* Analyze the ethical considerations and challenges associated with using Generative AI in data analytics
- [x] [__Data Analyst Career Guide and Interview Preparation__](https://github.com/cnoret/IBM-data-analyst-professional/)
* Describe the role of a data analyst and some career path options as well as the prospective opportunities in the field.
* Explain how to build a foundation for a job search, including researching job listings, writing a resume, and making a portfolio of work.
* Summarize what a candidate can expect during a typical job interview cycle, different types of interviews, and how to prepare for interviews.
* Explain how to give an effective interview, including techniques for answering questions and how to make a professional personal presentation.
---
[](https://github.com/cnoret)