25 narrated video lessons that teach through stories and real examples — progress tracking, auto-next, and one-click jump into the matching lab.
Build 8 real-world GenAI and Agentic AI projects in guided on-platform labs — copy-paste steps with expected outputs at every stage.
All 25 video lessons, PDF guides, labs and interview prep — plus every update released during your term. Learn at your own pace, from home.
Get job-ready with the built-in Resume Builder, 200 interview Q&As with model answers, and a Career Center that matches roles to your skills.
The complete engineering program — from LLM fundamentals to production multi-agent systems. 25 Modules | 5 Phases | 15+ Frameworks | 8 Real Projects
One enrolment covers the entire journey — from your first LLM API call to a job-ready portfolio, an interview-tested skillset and a professional resume.
Self-paced virtual training with real projects — 25 Modules · 5 Phases · 15+ Frameworks · 8 Real Projects. Watch, read, build, and get interview-ready without leaving the platform.
A full learning player: narrated video lessons with progress tracking, auto-next, and one-click jump to the lab, PDF and interview prep per lesson.
Start learning →Professional study guides with visual diagrams, formula spotlights, runnable code and step-by-step lab assistance. Read online or download.
Read & download →Complete every real-project lab right on the platform — copy-paste the code, follow the steps, check expected results, track your progress.
Start a lab →200 interview questions with model answers across all 25 topics — basic to advanced, with mastery tracking to make you job-ready.
Practise now →Finish the course to unlock skill-matched job roles with one-click searches on Naukri, Foundit, Indeed & LinkedIn, referral finder and salary guides.
See your progress →Build a professional AI-engineer resume in minutes — your course skills and the 8 real projects pre-loaded. Download as PDF and apply.
Build my resume →Intensive virtual hands-on sessions for advanced engineering topics — join from anywhere.
5 Detailed Phases covering everything from Foundations to Production Deployment
From ANI to frontier models — the state of play
Transformers, attention, tokenization & emergent intelligence
Zero-shot, few-shot, CoT, ToT & structured output techniques
Vision, audio, video & code — unified model architectures
LoRA, QLoRA, instruction tuning — customise any model
Pinecone, Weaviate, pgvector — Semantic search fundamentals
Naive RAG → Advanced RAG → Modular RAG pipelines
Self-RAG, Corrective RAG (CRAG), GraphRAG & hybrid search
Build production RAG apps with top orchestration libraries
Evaluation, monitoring & optimising RAG at scale
ReAct loop, tool calling, memory types & cognitive architectures
Build production agents with Swarm, handoffs & guardrails
Stateful graph-based agents with checkpointing & HITL
Role-playing agent teams, crews, flows & task orchestration
Resources, Tools, Prompts & Sampling — the new agent standard
Hierarchical, peer-to-peer & event-driven agent networks
Long-term persistent and structured episodic memory stores
Build agents that write, run code & control browsers
Benchmarking, red-teaming & responsible agentic AI
Observability, tracing, cost control & production reliability
Domain-specific assistants for coding, research & business
n8n, Zapier AI & no-code agentic automation pipelines
Design AI-native SaaS — APIs, streaming, caching & costs
AWS Bedrock, GCP Vertex, Azure AI — production deployment
Physical AI, agent economies, AGI timeline & roadmap
OpenAI SDK, LangGraph, CrewAI, MCP, RAGAS, Pinecone, FastAPI, Docker
Includes complete plan to transition into AI Engineering roles
Start your journey to becoming an AI expert — 100% online, self-paced, learn from home. Start anytime!