Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/cnoret/ibm-data-analyst-professional

WIP Final project for the IBM Data Analyst Professional Certificate.
https://github.com/cnoret/ibm-data-analyst-professional

analyzing-data data-analysis data-analyst data-manipulation data-science data-visualization ibm-certificate ibm-data-analyst-professional ibm-datascience-certification pandas python

Last synced: 9 days ago
JSON representation

WIP Final project for the IBM Data Analyst Professional Certificate.

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.








---

[![View My Profile](https://img.shields.io/badge/View-My_Profile-green?logo=GitHub)](https://github.com/cnoret)