AI Engineering in 16 Weeks
Hands-on AI Engineering for software engineers to master LLMs, fine-tuning, RAG and agents, and ship them to production.
28th February → 14th June
9 PM - 10:30 PM IST, Sat & Sun
290 Enrolled
Gaurav Sen
Founder AIEngg.dev | Ex-Uber, Directi
Trusted by 600+ engineers across US, India and rest of the world
Cohort Syllabus
Your instructor is Gaurav Sen.
- Neural networks: Parameters, Backpropagation, Loss, Activation functions
- Supervised, Self-supervised, Contrastive Learning, Reinforcement Learning
- Scaling Laws in LLMs
- Coding Assignment: MNIST
neural networkslearningscaling lawsLLMs
- Tokenisation
- Vectorization
- Positional Encodings
- Attention Mechanism
tokensvectorsattentionLLMs
- Q, K, V Matrices
- Cross Attention
- Multi-head Attention
- FFNNs
1 more item
transformerLLM internalsAttention
- Causal masked attention
- Model Training
- Auto-regressive models
- Coding Assignment: Transformer Internals
transformer codecausal attentiontransformer trainingautoregressive
- End-to-end LLM lifecycle
- Pre-training
- Post-training
- Model evaluation
llmsystem designdata processingevaluation
- KV cache
- Quantization - FP16, attention optimizations
- Fine Tuning - LoRA/QLoRA
- Dataset prep → training → evaluation
LLM optimizationsquantizationLORAfine-tuning
- RAG: chunking strategies, data ingestion, reranker, indexer
- Vector Embeddings, Vector Databases
- Search Algorithms: ANN algorithms (HNSW, IVF)
RAGVector DBVector Search
- Reranking strategies, Query rewriting, HyDE
- Input and output guardrails
- Safety: Prompt injection, Intent classification
- Coding Assignment: Build a RAG chatbot using API calls
RAGsafetyguardrailscoding
- LLM vs Agent vs Multiple Agents
- ReAct pattern
- Prompt Chaining, Orchestration, Routing
- Coding Assignment: Customer support agent
agentsreActorchestrationcoding
- Context Engineering
- Memory in Agents
- MCP, A2A
- Multi-Agents
1 more item
agentic memorymcpcontext engineeringmemory systems
- Evals: How to avoid hallucinations with Evals
- LLM as a Judge
- Tradeoffs and design decisions
- Fine-tuning vs Prompting vs RAG
1 more item
EvalsLLM as JudgehallucinationsAI in practice
- Reasoning models
- RLHF
- Chain of Thought
- How to prompt a reasoning model
reasoningchain of thoughtRLHF
- GANs
- Multimodal models
- CLIP
- Video Models
clipmultimodalLLMsimages
- Diffusion architecture
- Text-based diffusion
- Image and video generation
- Diffusion models vs LLMs
DiffusionImagesVideosFlow
Instructor
Your Cohort Instructor
Gaurav Sen
Founder AIEngg.dev | Ex-Uber, Directi
Gaurav Sen is a Software Engineer with experience designing and building AI systems at InterviewReady. He has also worked with companies like Docker and NeonDB in explaining how to build reliable AI systems. Gaurav has previously spoken at the University of Houston-Texas, IIT Gandhinagar, and BITS Hyderabad.
