Build, Deploy, and Master AI Systems — From Code to Agent
Our courses are designed to equip individuals and teams with hands-on skills in modern AI development, focusing on real-world tools and deployable systems.
View Full SyllabusAI Coding Foundations
Learn the programming essentials needed for modern AI workflows:
- Python for data processing and automation
- Pandas, NumPy, and basic ML pipelines
- Intro to LLMs (OpenAI, Claude, etc.) and vector databases
- Git, APIs, and debugging best practices
Outcome: Be able to read, write, and extend AI workflows and scripts.
Retrieval-Augmented Generation (RAG) Systems
Master how to build intelligent knowledge assistants and search-augmented applications:
- Architecture of RAG: chunking, embedding, vector search, prompt injection
- Tools: LangChain, LlamaIndex, Pinecone, ChromaDB
- Use cases in VC (pitch retrieval), finance (document Q&A), and education (policy search)
- Deploying RAG on cloud or local stack
Outcome: Build your own GenAI-powered assistant with custom document retrieval.
AI Agent Development
Build and orchestrate autonomous or multi-step AI agents for decision-making and task automation:
- Planning + tool use: ReAct, CoT, LangGraph, CrewAI
- Integrating APIs, databases, and browser actions
- Use cases: sourcing agents for VCs, copilots for analysts, tutoring agents for education
- Evaluation and reliability strategies
Outcome: Deploy AI agents that take actions, reason over time, and complete useful tasks.