GenAI Engineer — Complete Syllabus + Resources
hari mohan
Course Content
A practical, interview-focused GenAI Engineer Cheatsheet covering everything you need to move from LLM fundamentals to production-grade AI systems.
You’ll get concise explanations, architectures, key concepts, interview questions, and production patterns covering Transformers, LLMs, Embeddings, RAG, Fine-Tuning, AI Agents, LangGraph, MCP, Multimodal AI, Evaluation, Security, LLMOps, AWS GenAI and System Design.
Course Content
Module 1 — GenAI Fundamentals
- AI vs ML vs DL vs GenAI
- LLM fundamentals
- Tokens, parameters, context window
- Temperature, Top-K, Top-P
Module 2 — Transformers
- Transformer architecture
- Attention
- Q/K/V
- MHA, MQA, GQA
- RoPE
- KV Cache
Module 3 — LLMs
- Pretraining
- Next-token prediction
- SFT
- RLHF
- DPO
- Inference & decoding
Module 4 — Prompt Engineering
- Zero-shot
- Few-shot
- Prompt patterns
- Structured output
- JSON/Pydantic validation
Module 5 — Embeddings & Vector DB
- Embeddings
- Cosine similarity
- Semantic search
- FAISS
- Qdrant
- Pinecone
- HNSW
- ANN
Module 6 — RAG
- Document ingestion
- Chunking
- Embeddings
- Retrieval
- BM25
- Hybrid search
- Reranking
- Advanced RAG
- RAG evaluation
Module 7 — Fine-Tuning
- SFT
- PEFT
- LoRA
- QLoRA
- Quantization
- Dataset preparation
- Evaluation
Module 8 — AI Agents
- Agent architecture
- Tool calling
- Function calling
- ReAct
- Planning
- Memory
- Multi-agent systems
Module 9 — LangGraph
- State
- Nodes
- Edges
- Routing
- Checkpointing
- Persistence
- Human-in-the-loop
Module 10 — MCP
- MCP architecture
- MCP Client
- MCP Server
- Tools
- Resources
- Prompts
- Security
Module 11 — Multimodal AI
- Vision
- OCR
- Document AI
- STT
- TTS
- Voice agents
- Multimodal LLMs
Module 12 — GenAI Evaluation
- RAG evaluation
- Faithfulness
- Relevance
- Recall
- Precision
- MRR
- NDCG
- LLM-as-a-Judge
Module 13 — GenAI Security
- Prompt injection
- Jailbreaking
- Data leakage
- PII
- Tool security
- Authorization
- Guardrails
Module 14 — LLMOps
- vLLM
- llama.cpp
- Quantization
- Batching
- KV Cache
- Streaming
- Observability
- Cost optimization
Module 15 — AWS GenAI
- Bedrock
- Lambda
- API Gateway
- S3
- DynamoDB
- SQS
- CloudWatch
- SageMaker
Module 16 — GenAI System Design
- Production RAG architecture
- Agent architecture
- Multi-agent architecture
- Scalability
- Reliability
- Security
- Cost optimization
Module 17 — Interview Cheatsheet
- Top GenAI interview questions
- Architecture questions
- RAG questions
- Agent questions
- Fine-tuning questions
- LLMOps questions
- System Design questions
Buyer Instructions
Download/access the course content and follow the modules sequentially. Use the cheatsheet alongside hands-on implementation and interview preparation.
Additional Questions
- What is your current experience level?
- Are you preparing for a GenAI/LLM interview?
- Which area do you want to focus on most: RAG, Agents, Fine-Tuning, LLMOps, or System Design?
Service Actions
What the buyer gets:
- Complete GenAI cheatsheet
- Architecture diagrams
- Interview preparation material
- RAG & Agent patterns
- Fine-tuning reference
- Production/LLMOps checklist
- System Design reference
Recommended positioning: Sell it as a rapid-reference + interview preparation guide, rather than a full beginner course. This makes the ₹499 price point feel attractive and focused.