Master LLM applications, RAG, evaluation, and production-grade GenAI systems.
A flagship mentor-led journey covering advanced prompting, orchestration, retrieval pipelines, safety patterns, and deployment strategy for real-world GenAI products.
Updated regularly
Module 1: 2026 LLM Landscape - GPT-5.x, Claude Opus/Sonnet 4.x, Gemini 3, open-weight models
Module 2: Advanced Prompt Architecture - chain-of-thought, structured outputs, function calling
Module 3: Retrieval-Augmented Generation (RAG) - chunking, embeddings, vector databases
Module 4: Orchestration with LangChain and LangGraph
Module 5: LLM Evaluation - hallucination detection, golden datasets, automated grading
Module 6: Safety Patterns - guardrails, content filtering, prompt-injection defense
Module 7: Production Deployment - FastAPI services, cost optimization, observability/tracing
Module 8: Capstone - build and deploy a production-grade GenAI copilot
Prompt architecture
RAG implementation
LLM evaluation
Production integration
Enterprise support copilot
Document intelligence assistant
Is this course suitable for working professionals?
Yes. The builder journey is structured for both students and working professionals, with guided modules, assignment checkpoints, and mentor support.
Do I get certification preparation support?
Yes. This program includes structured guidance for Generative AI Master with revision plans and mock checkpoints.
Will I build practical projects in this course?
Yes. Every track includes project work so you can apply concepts in practical scenarios and build portfolio-ready outcomes.
