beginner Level Self-Paced Track Certificate Included

Python Mastery & Linear Algebra for AI

Master Python programming from fundamentals to advanced CPython memory internals, object-oriented design, vectorized computing with NumPy & Pandas, and geometric linear algebra for modern machine learning.

9h 21m total content

21 lessons & projects

Instructor: Atul Jha

Course Overview

About this Course

Master the essential programming and mathematical foundations required for modern artificial intelligence, deep learning, and data science.

Key Competencies You'll Build

Mathematical foundations written from pure first principles

Clean, reproducible PyTorch / Python code without black boxes

Production deployment and low-latency inference patterns

Hands-on capstone portfolio piece ready for GitHub

Course Curriculum

2 chapters • 21 total lessons & checkpoints

VideoGoogle Colaboratory & Basic Data Types

22 minStart →

VideoGoogle Drive & Colab Integration with Python Debugger

25 minStart →

VideoPython Data Structures: Lists, Tuples, Sets & Dictionaries

30 minStart →

VideoPackages, Modules & File Handling

25 minStart →

VideoObject-Oriented Programming & Classes

28 minStart →

VideoNumPy Fundamentals for AI

35 minStart →

VideoData Wrangling with Pandas

34 minStart →

VideoData Visualization & Plotting with Matplotlib

24 minStart →

VideoWhy Do We Care About Matrices in Machine Learning?

20 minStart →

VideoIntroduction to Matrices & Linear Transformations

26 minStart →

VideoMatrix Multiplication: Vector-Matrix, Matrix-Matrix & Alternate Views

38 minStart →

VideoVectors: Geometric Intuition, Dot Products & Unit Vectors

32 minStart →

VideoVector Arithmetic & Geometric Plotting in Python

28 minStart →

VideoVector Dot Products & Projections in Code