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PY101 · 24 hrs · 10 modules

Python for AI

The 4-week prep guide for MIT, Stanford & university AI certificates — don't waste $2,000+ in tuition showing up unprepared.

Ten gated modules (≥80% to advance) that take you from `print('hello')` to a working PyTorch neural network in four weeks. Weeks 1–2 cover Python from zero: syntax, data types, control flow, collections, functions, files, and a real end-to-end CLI project. Weeks 3–4 are pure AI-prep: NumPy and the linear algebra MIT 6.S191 assumes, pandas for the data wrangling Stanford CS229 assumes, plotting + ML mental models (train/val/test, overfitting, gradient descent), and a capstone where you train an Iris classifier in PyTorch with autograd. By the end you can walk into MIT 6.S191 Lab 1, MIT Professional Education AI, Stanford CS224N, or Andrew Ng's Deep Learning Specialization on day one and follow along instead of drowning in shape errors. About 24 hours, paced as a 4-week prep guide. $19.99, lifetime access, mirrored on Udemy. Step 1 of the GACS AI ladder → continue into Pre-MIT 6.S191 ($29) or Pre-Stanford CS224N ($19).

  1. 1

    Welcome to Python

    Quiz · 10Q · 80% to pass

    What Python is, why it's the world's most loved beginner language, and how to set up your first development environment.

    Open module
  2. 2

    Variables, Numbers, and Strings

    Quiz · 10Q · 80% to pass

    How Python stores information, the core data types, and how to combine them safely.

    Pass Module 1 to unlock
  3. 3

    Decisions and Repetition

    Quiz · 10Q · 80% to pass

    if / elif / else, for and while loops, and the patterns that show up in every real program.

    Pass Module 2 to unlock
  4. 4

    Lists, Dictionaries, and Collections

    Quiz · 10Q · 80% to pass

    How to store many values, look them up by key, and pick the right collection for the job.

    Pass Module 3 to unlock
  5. 5

    Functions and Reusable Code

    Quiz · 10Q · 80% to pass

    Defining your own functions, default arguments, return values, and importing from the standard library.

    Pass Module 4 to unlock
  6. 6

    Files, Errors, and a Real Mini-Project

    Quiz · 10Q · 80% to pass

    Reading and writing files, handling errors gracefully, and shipping a small CLI tool end to end.

    Pass Module 5 to unlock
  7. 7

    NumPy and the Math Every AI Course Assumes

    Quiz · 10Q · 80% to pass

    Vectors, matrices, broadcasting, and the 20 NumPy patterns that show up on day one of MIT 6.S191 and Stanford CS229.

    Pass Module 6 to unlock
  8. 8

    pandas and Real-World Data Wrangling

    Quiz · 10Q · 80% to pass

    Loading messy CSVs, cleaning them, grouping, merging, and producing the kind of clean DataFrame every ML assignment starts from.

    Pass Module 7 to unlock
  9. 9

    Plotting and the Mental Models Behind Machine Learning

    Quiz · 10Q · 80% to pass

    matplotlib basics, train/test splits, overfitting, and the vocabulary you need to follow an MIT or Stanford AI lecture without getting lost.

    Pass Module 8 to unlock
  10. 10

    PyTorch: Tensors, Autograd, and Your First Neural Network

    Quiz · 10Q · 80% to pass

    The minimum PyTorch you need to walk into MIT 6.S191 Lab 1 or Stanford CS224N PSet 2 and follow along: tensors, autograd, nn.Module, and a tiny end-to-end classifier.

    Pass Module 9 to unlock
Student Handbook →·Instructor Teaching Manual →