Module outcomes
- Design reliable AI systems using context engineering, RAG, and agent-based architectures.
- Build practical AI applications with LangChain, LangGraph, and workflow tools like n8n.
- Apply advanced context management techniques to improve accuracy, efficiency, and scalability.
- Evaluate and select AI platforms suited to real-world use cases and constraints.
Covered concepts
- Large Language Models (LLMs)
- Prompt Engineering Fundamentals
- Retrieval Augmented Generation (RAG)
- Agentic AI
- Context Engineering Principles
- LangChain
- Graph-Based Agent Design with LangGraph
- Context Management Techniques
- AI Platforms
- AI workflow with n8n
Module content
1
State of AI
Lesson (20 mins)
1
State of AI
Lesson (20 mins)
2
Context Engineering with LangChain
Lesson (26 mins)
2
Context Engineering with LangChain
Lesson (26 mins)