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PY101 · 24 hrs · 10 modules
Python for Beginners
The 4-week prep guide for MIT, Stanford & university AI certificates — don't waste $2,000+ in tuition showing up unprepared.
Everything you need to know before tackling MIT Professional Education AI courses, MIT 6.S191, Stanford CS224N / CS229, or any university AI certificate. Ten gated modules (≥80% to advance) 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 final module project where you train an Iris classifier in PyTorch with autograd — exactly the foundation those programs assume you already have on day one. About 24 hours, paced as a 4-week prep guide. Launch pricing $29 (reg. $49), lifetime access, narrated modules, Course Coach AI tutor, and a verifiable certificate on completion.
14-day money-back guarantee
Meet your instructor · 2-min preview
From Module 1What you'll need (optional preview)▾
Beginner-friendly — everything is taught from scratch. This is just a heads-up on what helps.
Helpful to have
- Comfort with a computer — installing software, opening folders, saving files.
- Basic high-school math (variables, percentages, simple algebra). No calculus required.
- About 5–6 hours per week for 4 weeks to actually do the workbook exercises.
Nice to have (not required)
- Any prior brush with spreadsheets, scripting, or HTML — useful but not required.
- A laptop you can install Python on. Chromebooks and tablets work too via the free Google Colab path below.
No setup? Free path included:
If you can't or don't want to install Python locally, every exercise also runs in Google Colab (free, browser-only, zero install). Each module's workbook includes a one-click Colab link.
Honest comparison
Python for Beginners vs the market
A 4-week prep guide pitched against the leading Python intros.
| What you get | GACS $29 (list $49) | Udemy Python $15–$199 · depends on sale | Coursera Python for Everybody $49/mo · subscription | Codecademy Pro $24.99/mo · subscription |
|---|---|---|---|---|
| One-time price, lifetime access | ||||
| Aimed at MIT/Stanford AI-cert prep | ||||
| Module quizzes + final exam | varies | |||
| AI Teacher / 1:1 coach | ||||
| Public verifiable certificate | Udemy PDF | |||
| 14-day refund | 30d | 7d | 7d | |
| Cost over 6 months of study | $29 | $15–$199 | $294 | $150 |
Bottom line: Subscriptions cost 5–10× more over a single learning sprint. GACS gives a focused AI-cert on-ramp at a flat $29.
Competitor pricing and curriculum verified from public sources, June 2025. We update this table when the market moves.
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Your progress
0 of 10 modules passed · 0%Nothing passed yet — start with Module 1 below.
- 1
Welcome to Python
Module assessment · 10 questions · 80% to passWhat Python is, why it's the world's most loved beginner language, and how to set up your first development environment.
- 2
Variables, Numbers, and Strings
Module assessment · 10 questions · 80% to passHow Python stores information, the core data types, and how to combine them safely.
Pass Module 1 to unlock - 3
Decisions and Repetition
Module assessment · 10 questions · 80% to passif / elif / else, for and while loops, and the patterns that show up in every real program.
Pass Module 2 to unlock - 4
Lists, Dictionaries, and Collections
Module assessment · 10 questions · 80% to passHow to store many values, look them up by key, and pick the right collection for the job.
Pass Module 3 to unlock - 5
Functions and Reusable Code
Module assessment · 10 questions · 80% to passDefining your own functions, default arguments, return values, and importing from the standard library.
Pass Module 4 to unlock - 6
Files, Errors, and a Real Mini-Project
Module assessment · 10 questions · 80% to passReading and writing files, handling errors gracefully, and shipping a small CLI tool end to end.
Pass Module 5 to unlock - 7
NumPy and the Math Every AI Course Assumes
Module assessment · 10 questions · 80% to passVectors, 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
pandas and Real-World Data Wrangling
Module assessment · 10 questions · 80% to passLoading messy CSVs, cleaning them, grouping, merging, and producing the kind of clean DataFrame every ML assignment starts from.
Pass Module 7 to unlock - 9
Plotting and the Mental Models Behind Machine Learning
Module assessment · 10 questions · 80% to passmatplotlib 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
PyTorch: Tensors, Autograd, and Your First Neural Network
Module assessment · 10 questions · 80% to passThe 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
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Authoritative sources
Independent primary sources used to check and corroborate the guidance on this page.
NIST National Initiative for Cybersecurity Education (NICE)US national framework for cybersecurity work roles and competencies.
Financial Action Task Force (FATF)Global AML/CFT standards referenced by financial-crime curricula.
FBI Internet Crime Complaint Center — Annual ReportsPrimary loss and typology data used in fraud-investigation training.
US Federal Trade Commission — Consumer Sentinel Data BookOfficial complaint statistics for teaching fraud trend analysis.