From the history of neural networks to building agentic workflows with Claude Code — understand how generative AI actually works, learn to communicate with it effectively, and master the tools that make it powerful.
Generative AI isn't just for engineers. It's the most significant shift in how humans interact with computers since the smartphone.
People who know how to use AI tools effectively get more done in an hour than others do in a day. This isn't hype — it's measurable.
AI hallucinates, has biases, and can't reason about novel problems the way you can. Knowing what AI can't do is as important as knowing what it can.
Whether you're a writer, doctor, engineer, or teacher — AI will reshape your workflow. The question isn't if but how well you adapt.
This isn't theory-only. By Module 4, you'll be using Claude Code to build software, automate tasks, and create agentic workflows.
GenAI raises real questions about accuracy, privacy, and intellectual property. Understanding the technology helps you use it ethically.
We start from zero. If you've ever used a search engine, you have enough technical background for this course.
8 modules from AI history to the landmark papers behind modern generative AI. Each module is a complete, self-contained slide deck.
Trace the path from early machine learning to today's generative AI. Understand the key breakthroughs — neural networks, supervised and unsupervised learning, the transformer architecture, and the attention mechanism that made it all possible.
How do Large Language Models actually work? Dive into tokenization, embeddings, the transformer architecture, and the training process. Understand hallucination, temperature, and why these models sometimes confidently say things that are completely wrong.
Master the art and science of communicating with AI models. Learn how context windows work, why iteration beats one-shot prompts, how to use system prompts and XML tags, and the techniques that consistently produce high-quality outputs.
Move beyond chat. Learn how agentic AI works — the loop of thinking, acting, and observing that allows AI to complete complex multi-step tasks. Get hands-on with Claude Code: tools, MCPs, bash commands, skills, and the basics of Claude itself (Claude 101).
Context is everything. Learn how to manage what the model knows, how different models affect your tools, and how Retrieval-Augmented Generation (RAG) lets you feed AI exactly the right information at the right time. Explore agentic search patterns.
Advanced Claude Code features that separate casual users from power users. Deep-dive into custom skills, MCP servers, slash commands, subagents, hooks, permission modes, using teams of agents in parallel, and best practices for complex workflows.
The landmark papers behind modern generative AI, each with its core idea and its impact: attention and the transformer, the GPT and BERT families, efficient fine-tuning with LoRA and PEFT, vision transformers, VAEs and GANs, diffusion models, and retrieval-augmented generation.
Where is GenAI heading? Explore emerging capabilities, current limitations and why they exist, multimodal models, open vs. closed source, AI safety and regulation, and how to position yourself to use these tools to your greatest advantage.
We believe in teaching the full picture. GenAI is powerful, but it has real limitations you need to understand.