Unlocks after Module 1The AI Engineering Program

Module 2: Python for AI

Python to a professional standard, ending in a working command-line capstone.

34guided hours

15lessons

2 of 13in the program

Lessons

15 lessons, in order. Each one unlocks when you finish the one before it.

2.1
Variables and data typesLab: Python foundations repoAssignment: Write typed variables for a small dataset
2.2
Operators and expressionsLab: Python foundations repoAssignment: Implement calculation functions
2.3
if/elif/elseLab: Rule-based classifierAssignment: Implement decision rules
2.4
for/while loopsLab: Batch processorAssignment: Process a list of records
2.5
Lists, tuples, sets, dictionariesLab: Dataset manipulation labAssignment: Transform nested records
2.6
Functions and scopeLab: Reusable feature libraryAssignment: Build reusable preprocessing functions
2.7
Modules and packagesLab: Mini Python packageAssignment: Split code into modules
2.8
Exceptions and error handlingLab: Robust data loaderAssignment: Handle malformed input
2.9
Classes and OOPLab: Dataset object modelAssignment: Create Dataset and Model classes
2.10
Iterators and generatorsLab: Streaming data readerAssignment: Process records without loading all data
2.11
Virtual environmentsLab: Reproducible projectAssignment: Create isolated environment and requirements file
2.12
NumPy arraysLab: Numerical computing notebookAssignment: Implement vector/matrix operations
2.13
Pandas dataframesLab: Data cleaning pipelineAssignment: Clean, join and aggregate a dataset
2.14
Matplotlib visualizationLab: EDA reportAssignment: Create five decision-useful charts
2.15
Python mini-capstoneLab: Sales analytics CLIAssignment: Build an end-to-end Python data-analysis CLI

Module project

It goes in your portfolio, with a README a recruiter can read in a minute.

AI vs ML vs DL vs GenAI: deep notes, a hands-on lab and a quiz. No card. No catch.