wip/planned
| Course Name | Links |
|---|---|
| Learn Coding Basics | Python |
| Learn Linux | Bash/Zsh |
| Build a Bookbot | Python |
| Learn Git | Git |
| Learn Object Oriented Programming | Python |
| Build an Asteroids Game | Python |
| Learn Functional Programming | Python |
| Build an AI Agent | Python |
| Learn HTTP Clients | Python |
| Build a Web Scraper | Python |
| Personal Project 1 | Your choice |
| Learn LLMs | Python + PyTorch |
| Learn AI Coding | Python + OpenCode |
| Learn Prompt and Context Engineering | Python |
| Learn SQL | SQL |
| Learn HTTP Servers | Python |
| Learn Retrieval Augmented Generation | Python |
| Learn MCP | Python |
| Learn AI Evals | Python |
| Learn Multimodal AI | Python |
| Capstone Project | Your choice |
| Learn to Find a Job | Job Search |
- "Build a Model": The student builds a simple LLM using a small dataset with the goal of understanding how the training process works.
- "Learn AI Coding": The student learns how to effectively use an agent to write code.
- "Learn Prompt and Context Engineering": A deeper dive into prompt anatomy, tool calling, cache strategies, cost tradeoffs, compaction, memory, prompt chaining, zero-shot vs few-shot, separate judgment prompts, etc. Focus on prompt structure in production systems, not local coding.
- "Learn MCP": The student already knows how to use MCP. Focus on how the protocol actually works and how to build a server to expose to users.
- "Learn AI Evals": Learn how to build evaluation pipelines for LLMs and other AI models so you can tell if your model/prompt/settings/context changes are having a positive or negative effect on the overall system performance.
- "Learn Multimodal AI": Learn how to build systems that can handle multiple modalities (text, image, audio, video, etc.) and how to integrate them into a single AI system.