Python for AI

A hands-on Python course built for artificial intelligence, machine learning and data science. It goes from Python basics to NumPy, Pandas, Matplotlib and regular expressions, and ends with a final project.

Instructor: Zahra Amini

Term: Online

Location: Online, Hobot Academy

Time: Self-paced video lectures

Course Overview

This course was designed and taught by me at Hobot Academy. It gives students a strong Python foundation for artificial intelligence, machine learning and data science. Students will:

  • Learn Python from the basics: variables, control flow, lists, loops, functions, tuples, dictionaries, sets and files
  • Use NumPy and Pandas for numerical computing and data manipulation
  • Visualize data with Matplotlib
  • Process text with regular expressions
  • Apply everything in a final project

Resources

How to Use the Materials

  1. Clone the repository: git clone https://github.com/hobotacademy/Python-for-AI.git
  2. Install Python, Jupyter Notebook, and the libraries used in the course (NumPy, Pandas, Matplotlib)
  3. Open the cloned folder, run jupyter notebook, and work through the notebooks in order

Schedule

Week Date Topic Materials
0 Homework and Practice

Assignments and practice problems to test your skills.

1 Python Basics

Variables, data types, and basic syntax.

2 Conditions

Control flow with if, elif, and else statements.

3 Lists

Working with Python lists and list comprehensions.

4 Loops and Functions

Iteration with for and while loops, and an introduction to functions.

5 Functions, Tuples and Dictionaries

Advanced functions, tuples, and dictionaries.

6 Sets and Files

Sets and file handling (reading and writing data).

7 NumPy

Introduction to NumPy for fast numerical computing.

8 NumPy and Pandas

Advanced NumPy and an introduction to Pandas for data manipulation.

9 Pandas and Matplotlib

Data analysis with Pandas and data visualization with Matplotlib.

10 Matplotlib and Regular Expressions

Advanced data plotting and the basics of regular expressions.

11 Regular Expressions

A deeper look at regular expressions for text processing.

12 Final Project

Final course projects that apply all the concepts learned.