AIFundamentals

This repository contains code and resources for the AI Fundamentals course. The course covers the basics of artificial intelligence, including machine learning, deep learning, and natural language processing.

Course Content

• Introduction to AI
• Types of Learning
• Understanding the Machine Learning Process
• Neural Networks and Generative AI
• Prompt Engineering and AI Agents
• Using AI as a Competitive Edge

Codespaces Setup

This repository includes Codespaces-ready configuration:

• VS Code extension recommendations in .vscode/extensions.json for Python, Jupyter, and Markdown WYSIWYG preview.
• Dev container config in .devcontainer/devcontainer.json that installs notebook kernel support (jupyterlab, notebook, ipykernel) after creation.
• Compatibility kernel aliases are created in Codespaces with the legacy names training-env and det-env so existing notebooks work without edits.
• Automatic MLflow startup on container start (postStartCommand) at port 8885, matching the exercises.
• A manual fallback task in .vscode/tasks.json to start MLflow UI on port 8885.

Simple Browser

Simple Browser is built into VS Code (no extra extension install required).

To open MLflow from Codespaces:

1. MLflow starts automatically when the Codespace starts.
2. Open command palette and run: Simple Browser: Show.
3. Enter URL: http://127.0.0.1:8885.

If MLflow does not come up automatically, check logs at /tmp/mlflow.log and run task Start MLflow UI (port 8885).