Practical Python & AI-Assisted Coding

Master the art of directing AI to build real software — prompt patterns, agent workflows, and shipped projects that prove your skill.

5 hours 12 modules

The framework

Prompt-Plan-Program (PPP)

PPP is a three-stage loop: (1) Prompt — define the problem with precision; (2) Plan — architect the solution before writing a single line; (3) Program — direct AI tools to implement, then critically review and refine. The loop repeats at every level of abstraction.

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How you'll learn

Text-first. Practice-heavy. No video lectures.

15-minute text lessons

Short, dense reading you can finish between meetings — not hour-long video lectures.

Hands-on exercises

Apply the framework to a realistic scenario, right in the module where you learned it.

Quizzes & assessments

Check your judgment, not just your memory — most questions are situational.

Certificate on completion

Finish a course and get a shareable certificate, automatically.

About this course

Most Python courses teach you to memorise syntax. This course teaches you to think architecturally — to plan a solution, direct an AI coding tool to write the code, and critically evaluate the output. You will build a complete, deployable automation pipeline. Every concept is introduced only when the project demands it.

The project: Automated Data Extraction & Reporting Tool

Build a Python script that reads messy CSV data, cleans it, runs analysis, and auto-generates a formatted HTML report — all directed through AI prompting with your architectural oversight.

  1. 1

    The Prompt-Plan-Program Framework

    Learn the foundational framework for AI-assisted coding — how to think architecturally before writing a single line of code.

    25 min· Knowledge check· 📚 1 resource
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  2. 2

    Python Fundamentals — Variables, Types & Your First Script

    Understand variables, data types, and basic operations — the building blocks every Python program is made of.

    30 min· Knowledge check· Coding exercise
  3. 3

    Collections & Data Structures — The ACCESS Decision Framework

    Before you can choose the right data structure, you need to understand what each one does and when it shines.

    30 min· Knowledge check· Coding exercise
  4. 4

    Control Flow — Loops, Conditions & Pattern Matching

    Apply a systematic framework to select the optimal data structure for any problem — moving beyond memorisation to architectural thinking.

    25 min· Knowledge check
  5. 5

    Functions, Modules & Type Safety

    Master the logic structures that make programs make decisions and repeat actions — with real-world patterns, not textbook exercises.

    30 min· Knowledge check· Coding exercise
  6. 6

    AI-Assisted Coding in Practice ★ NEW

    Learn to write functions that are clear, testable, and reusable — the building blocks of professional Python code.

    25 min· Knowledge check· Coding exercise
  7. 7

    Reading & Writing Files — Practical File I/O

    Learn to read from and write to files — the foundation of data processing, report generation, and automation.

    25 min· Knowledge check· Coding exercise
  8. 8

    Working with APIs — Fetching Real-World Data

    Learn to call web APIs, handle responses, and integrate external data into your Python programs.

    30 min· Knowledge check· Coding exercise· 📚 1 resource
  9. 9

    Error Handling — Building Resilient Code

    Learn to anticipate, catch, and handle errors gracefully — so your programs fail safely instead of crashing silently.

    25 min· Knowledge check
  10. 10

    Data Analysis with Pandas

    Use the Pandas library to load, clean, transform, and analyse real-world datasets — the core skill of data-driven Python.

    35 min· Knowledge check· Coding exercise
  11. 11

    Automating Real-World Tasks

    Apply everything you have learned to automate repetitive tasks — from file processing to report generation to scheduled jobs.

    25 min· Knowledge check· 📚 2 resources
  12. 12

    Capstone — Automated Sales Intelligence Pipeline

    Build a complete automated data pipeline that fetches, cleans, analyses, and reports on real-world data — applying every concept from the course.

    40 min· Knowledge check· Coding exercise