Gain practical, in-demand skills with hands-on GenAI training, guided by industry experts from basics to advanced applications.
Get personalized coaching and insights to accelerate your learning journey.
Work on real-world AI projects and build a standout professional portfolio.
Select modules tailored to your goals, with advisor support for maximum relevance.
Seamlessly join the best GenAI workshops—your upskilling journey made easy.
Receive ongoing feedback and prep support for interviews and certifications.
10 live, instructor-led engineering sessions designed to help teams master GenAI workflows with structured progression.
Experience real-world LLM, GenAI, and automation engineering through practical exercises and guided implementations.
Build an end-to-end AI system integrating GenAI, RAG, agents, tools, and deployment workflows using enterprise patterns.
Develop production-grade GenAI pipelines: embeddings, RAG, multi-agent systems, tool-calling, and deployment.
Google Colab notebooks, templates, datasets, starter code, AI toolkits, prompt libraries, and lifetime community access.
Week 1 — Foundations & Prompt Engineering: LLM basics, prompt patterns (zero/few-shot, CoT), embeddings, semantic similarity, and Vibe Coding (NL → Code workflows).
Week 2 — Vector DBs & RAG: FAISS/Pinecone/Chroma, indexing, semantic search and retrieval basics.
Week 3 — Building RAG Pipelines: LangChain workflows, document loaders, chunking, and embedding storage.
Week 4 — RAG on Cloud & Agentic AI Basics: Bedrock integration, agent basics, tools, memory fundamentals, and Intro to MCP (Model Context Protocol).
Week 5 — Agentic AI Workflows: Coordination systems (CrewAI, Agno), modular RAG, task assignment, A2A communication protocols, and tool interop.
Week 6 — Observability & Evaluation: Logging, LangSmith/LangWatch, prompt scoring, evaluation metrics, and agent trace visualization.
Week 7 — Deployment & Guardrails: Serving LLMs (FastAPI), CI/CD, safety guardrails, secure tool-calling, MCP server development, and production pipelines.
Week 8 — Capstone & Agent Kit: Build an end-to-end solution (Embed → RAG → A2A Agents → MCP Tools → Guardrails → Observability), plus deployment guide and real-world optimization.
Practical, hands-on labs using LangChain, Pinecone, Bedrock, LangFlow and agent frameworks. Ideal for building production-ready GenAI applications.
Program Fee: $799