Python & Technical Foundations
Every AI engineer starts with the same foundation: strong Python fundamentals, version control and the command-line fluency to work like a professional developer. This module builds that base before any AI concept is introduced.
What You Will Learn
A detailed, industry-aligned breakdown of every topic covered in this module.
- Python programming fundamentals — syntax, data structures and control flow
- Functions and object-oriented programming in Python
- Error handling and writing resilient code
- Virtual environments and dependency management
- Git and GitHub version control workflows
- Linux and command-line interface fluency
- Working with JSON as a data-interchange format
- HTTP fundamentals and REST APIs
- Debugging techniques for Python applications
- Basic automated testing
- Writing clear technical documentation
Tools You Will Use
Hands-on time with the same tools used in professional AI engineering and production ML workflows.
Python
Core programming language used across every module, from scripting to AI model development.
VS Code
Primary code editor used for writing, debugging and testing Python and AI application code.
Git
Version control system used to track code changes throughout every project.
GitHub
Code hosting and collaboration platform used for version control, CI/CD and portfolio building.
Linux
Command-line environment used for development, deployment and server administration.
Postman
API testing tool used to build, test and debug REST API requests.
REST APIs
The standard interface pattern used to connect applications, services and AI models.
JSON
The standard data-interchange format used across APIs, configs and AI application payloads.
Hands-On Labs
Production-style AI engineering lab scenarios, built using the same stack real AI teams ship with.
Write Python programs using core data structures, functions and OOP principles.
Set up and manage isolated virtual environments for a multi-project workflow.
Track a project's history and collaborate using Git and GitHub.
Call and test REST APIs using Postman, and parse JSON responses in Python.
Debug and write basic automated tests for a small Python application.
Assessment
Knowledge Assessment
Quiz covering Python fundamentals, OOP concepts, Git workflows and REST/JSON basics.
Practical Evaluation
Students must build and document a small Python application that consumes a REST API and is version-controlled on GitHub.
Projects
Industry-style deliverables added directly to your project portfolio.
Python AI Application
Build Python applications using APIs, data processing pipelines and automation scripts.
Technical Documentation & Portfolio Setup
Set up a GitHub portfolio repository with clear documentation, ready to host every project in the program.
What This Module Builds
Students build a strong software foundation for AI development by writing Python applications, working with APIs, managing code with Git/GitHub, debugging applications and applying professional development practices.