This repository serves as a way for me to document my experience with the IBM Data Science Professional Certificate program. The program proved to be a great introduction to the field of Applied Data Science. The program has a lot of hands-on activities and interactive labs, which is an effective medium for learning.
By taking the course, you will learn useful tools, like Jupyter Notebook and RStudio. You will also get experience with the libraries like Pandas, NumPy, Matplotlib, Seaborn, Folium, Scikit-Learn, and others. Most importantly, you will accomplish interesting projects like Random Album Generator, Predicting Housing Prices, and Building a Classifier Model.
There are 9 courses:
Sq. | Name | Directory Link | Credential |
---|---|---|---|
1 | What is Data Science? | Mostly Lectures & Reading | Credential |
2 | Tools for Data Science | Directory | Credential |
3 | Data Science Methodology | Mostly Lectures & Reading | Credential |
4 | Python for Data Science and AI | Directory | Credential |
5 | Databases and SQL for Data Science | Directory | Credential |
6 | Data Analysis with Python | Directory | Credential |
7 | Data Visualization with Python | Directory | Credential |
8 | Machine Learning with Python | Directory | Credential |
9 | Applied Data Science Capstone | Directory | Credential |