Your 12-Month Learning Roadmap
Four phases, 16 modules, and one incredible capstone project. Let's build something amazing.
Phase 1: Foundations
Learn how AI thinks and how to talk to it
What Is an LLM?
Discover how large language models work, what they can do, and where they fall short. You'll learn why AI sometimes makes mistakes and how to spot them.
Prompt Engineering 101
Learn the art of writing clear, structured instructions for AI. Turn vague requests into powerful prompts that get exactly the output you want.
Python Basics for AI
Get comfortable with Python — the language AI builders use. Learn variables, loops, and functions so you can start automating things.
Structured Outputs
Learn how to make AI give you organized, useful outputs — like tables, JSON, checklists, and outlines — instead of messy paragraphs.
Phase 2: Workflow Thinking
Chain prompts together to build multi-step AI processes
Prompt Chaining
Instead of one big prompt, learn to break tasks into a chain of smaller prompts where each step feeds into the next. This is how real AI workflows are built.
API Basics
Learn what an API is and how to use the OpenAI API in Python to send prompts and receive responses programmatically — no more copy-pasting!
AI Research Assistant
Build your first real multi-step AI tool: a research assistant that generates a plan, gathers information, summarizes it, and creates quiz questions.
Automation with Zapier
Discover no-code automation! Connect apps together so that when one thing happens, another thing automatically follows — without writing code.
Phase 3: Semi-Autonomous Systems
Build AI that plans, executes, and evaluates its own work
Planning Frameworks
Teach AI to think before it acts. Learn how to design prompts that make AI create a step-by-step plan before executing any task.
Self-Review Loops
Learn the most powerful agentic skill: making AI check its own work. Build prompts that evaluate output quality and suggest improvements automatically.
Memory & State
Real agents remember things! Learn how to give AI a memory using databases, so it can track what it has done and build on previous results.
Tool Calling
Level up your agents by giving them tools — like web search, calculators, or databases — that they can use to complete tasks more accurately.
Phase 4: Autonomous Workflows
Design full AI systems that run with minimal human supervision
Error Handling & Logging
Professional AI systems don't crash silently — they handle errors gracefully and log what happened. Learn to build resilient, debuggable workflows.
Evaluation Metrics
How do you know if your AI system is actually good? Learn to define metrics, measure output quality, and use data to improve your systems over time.
Version Control with GitHub
Real engineers use GitHub to track changes, collaborate, and build portfolios. Learn Git basics and publish your AI projects for the world to see.
Capstone: Autonomous Academic Agent
Put everything together! Build your final capstone project: a fully autonomous AI agent that accepts a learning goal, creates a study plan, tracks progress, and generates weekly reports.