• Day One: Dev Environment Setup

  VSCode configuration for Python, essential Python and AI VSCode plug-ins and installing AI-focused libraries; an introduction to Jupyter notebooks and embedding that into VSCode. ** NOTE: Even if you are an experienced developer, you will benefit from the VSCode and AI libraries details. SIDEBAR: Beginning with the End in Mind (Our ultimate goal) - Preview/screenshot(s) of the Capstone project.

• Day Three: AI Prompt Engineering

  Invoke a LLM using a chat-like prompt via its API. (Example: 'How would you go about designing a program that keeps itself updated as the underlying technology evolves.') This will be the outline we use to have AI help us build this. SIDEBAR: Local/open-source LLMs vs. commercial APIs. Things to think about for when we deploy (and need to pay for running) our AI applications in the real world.

• Day Two: First AI App

  Quick exercise to validate the functionality of the Python and AI libraries, then we will create 'Hello AI', our first program implementing AI. SIDEBAR: Quick tour of the current state-of-the-art of the AI tooling landscape.