KMNaim / Python-for-Data-Science

This is the repository for the course Python for Data Science covering Python Basics, Data Science Libraries (e.g., Pandas, Matplotlib, Sklearn).

Python for Data Science and AI

This is the repository, mainly to prepare students to get acquainted with Python, before actually learning machine learning. For those who are more interested in the advanced one, go to my other repository "Machine Learning"

Outline

The repo is structured into 2 big components:

1. Python Basics

Focus on getting started.

• Variables
• List
• Tuples, Dictionaries
• Functions
• Classes
• Exception

2. Data Science

• Numpy
• Pandas
• Matplotlib
• Sklearn

Reference books:

• [GERON] Geron, A. Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, 2019 (2nd edition) (https://github.com/ageron/handson-ml2)
• [VANDER] VanderPlas, J. Python Data Science Handbook: Essential Tools for Working with Data, 2016 (1st edition) (https://jakevdp.github.io/PythonDataScienceHandbook/)

Online resources:

• Python tutorials available online: https://docs.python.org/3/tutorial/
• Jupyter notebook tutorials available online: https://ipython.org/documentation.html
• Numpy tutorials available online:https://numpy.org/doc/stable/
• Pandas tutorials available online: https://pandas.pydata.org/docs/
• Matplotlib tutorials available online: https://matplotlib.org/contents.html
• Scikit-learn tutorials available online: https://scikit-learn.org/stable/user_guide.html