Free text-first course
Generative AI Application Development with Python
A small AI assistant app with structured input, structured output, one safe tool, mock mode, tests, and a release checklist.
What you will be able to do
A small AI assistant app with structured input, structured output, one safe tool, mock mode, tests, and a release checklist.
Use a repeatable workflow instead of disconnected tips.
Check assumptions, evidence, output quality, and limitations before using results.
Create a capstone artifact that can be inspected, improved, and reviewed.
What you need before starting
Learners who know basic Python and want to build small generative AI applications responsibly.
Python Foundations for AI and AI Foundations for Everyone are recommended.
Static lessons, activities, knowledge checks, learner templates, and a downloadable text-first pack.
13-module course sequence
The sequence follows the approved detailed syllabus and is implemented as a complete text-first shell.
Module 01
What Makes an AI App Different from a Script
- Learn how What Makes an AI App Different from a Script fits into Python generative AI application development instead of treating it as an isolated topic.
- Practice by build or inspect a small app component using the module idea, then compare the result with the module review checklist.
- Produce an implementation note with inputs, outputs, checks, and safety boundaries before moving ahead in Generative AI Application Development with Python.
Module 02
API Keys, Environment Variables, Costs, and Safe Local Setup
- Learn how API Keys, Environment Variables, Costs, and Safe Local Setup fits into Python generative AI application development instead of treating it as an isolated topic.
- Practice by build or inspect a small app component using the module idea, then compare the result with the module review checklist.
- Produce an implementation note with inputs, outputs, checks, and safety boundaries before moving ahead in Generative AI Application Development with Python.
Module 03
Messages, Instructions, and Response Handling
- Learn how Messages, Instructions, and Response Handling fits into Python generative AI application development instead of treating it as an isolated topic.
- Practice by build or inspect a small app component using the module idea, then compare the result with the module review checklist.
- Produce an implementation note with inputs, outputs, checks, and safety boundaries before moving ahead in Generative AI Application Development with Python.
Module 04
Prompt Templates and Input Validation
- Learn how Prompt Templates and Input Validation fits into Python generative AI application development instead of treating it as an isolated topic.
- Practice by build or inspect a small app component using the module idea, then compare the result with the module review checklist.
- Produce an implementation note with inputs, outputs, checks, and safety boundaries before moving ahead in Generative AI Application Development with Python.
Module 05
Structured Outputs with Schemas
- Learn how Structured Outputs with Schemas fits into Python generative AI application development instead of treating it as an isolated topic.
- Practice by build or inspect a small app component using the module idea, then compare the result with the module review checklist.
- Produce an implementation note with inputs, outputs, checks, and safety boundaries before moving ahead in Generative AI Application Development with Python.
Module 06
Tool and Function Calling with External Actions
- Learn how Tool and Function Calling with External Actions fits into Python generative AI application development instead of treating it as an isolated topic.
- Practice by build or inspect a small app component using the module idea, then compare the result with the module review checklist.
- Produce an implementation note with inputs, outputs, checks, and safety boundaries before moving ahead in Generative AI Application Development with Python.
Module 07
Conversation State and Memory Boundaries
- Learn how Conversation State and Memory Boundaries fits into Python generative AI application development instead of treating it as an isolated topic.
- Practice by build or inspect a small app component using the module idea, then compare the result with the module review checklist.
- Produce an implementation note with inputs, outputs, checks, and safety boundaries before moving ahead in Generative AI Application Development with Python.
Module 08
File Input, Summarisation, and Extraction Workflows
- Learn how File Input, Summarisation, and Extraction Workflows fits into Python generative AI application development instead of treating it as an isolated topic.
- Practice by build or inspect a small app component using the module idea, then compare the result with the module review checklist.
- Produce an implementation note with inputs, outputs, checks, and safety boundaries before moving ahead in Generative AI Application Development with Python.
Module 09
Error Handling, Retries, Rate Limits, and Fallback Messages
- Learn how Error Handling, Retries, Rate Limits, and Fallback Messages fits into Python generative AI application development instead of treating it as an isolated topic.
- Practice by build or inspect a small app component using the module idea, then compare the result with the module review checklist.
- Produce an implementation note with inputs, outputs, checks, and safety boundaries before moving ahead in Generative AI Application Development with Python.
Module 10
Simple App UI with FastAPI or Streamlit
- Learn how Simple App UI with FastAPI or Streamlit fits into Python generative AI application development instead of treating it as an isolated topic.
- Practice by build or inspect a small app component using the module idea, then compare the result with the module review checklist.
- Produce an implementation note with inputs, outputs, checks, and safety boundaries before moving ahead in Generative AI Application Development with Python.
Module 11
Testing AI App Behavior with Deterministic Fixtures
- Learn how Testing AI App Behavior with Deterministic Fixtures fits into Python generative AI application development instead of treating it as an isolated topic.
- Practice by build or inspect a small app component using the module idea, then compare the result with the module review checklist.
- Produce an implementation note with inputs, outputs, checks, and safety boundaries before moving ahead in Generative AI Application Development with Python.
Module 12
Privacy, Logging, and Safe Deployment Boundaries
- Learn how Privacy, Logging, and Safe Deployment Boundaries fits into Python generative AI application development instead of treating it as an isolated topic.
- Practice by build or inspect a small app component using the module idea, then compare the result with the module review checklist.
- Produce an implementation note with inputs, outputs, checks, and safety boundaries before moving ahead in Generative AI Application Development with Python.
Module 13
Capstone: Useful AI Assistant with Evaluation Checklist
- Learn how Capstone: Useful AI Assistant with Evaluation Checklist fits into Python generative AI application development instead of treating it as an isolated topic.
- Practice by build or inspect a small app component using the module idea, then compare the result with the module review checklist.
- Produce an implementation note with inputs, outputs, checks, and safety boundaries before moving ahead in Generative AI Application Development with Python.
Course status: outline published, lessons in development
The full syllabus, module structure, activities, and download pack are published and free to use now. Detailed lesson writing is still in progress, so lesson pages currently give the shape of each topic rather than the final teaching depth. Per-module assessments, worked examples, instructional diagrams, and external specialist review are planned next.