Production LLM & Agentic AI Engineering Master Program

120+ ()

Programming & AI Foundations (4 hours)

• Python syntax, OOP & async concurrency
• Git, venv, Poetry & dependency management
• REST APIs & project engineering
• Python engineering checkpoint

Transformers & LLM Fundamentals (6 hours)

• Transformer architecture internals
• KV cache & advanced attention mechanisms
• Programmatic LLMs & structured outputs
• Tokenization & context window management

LLM Fine-Tuning & PEFT (8 hours)

• QLoRA 4-bit fine-tuning with Unsloth
• DPO alignment & reward modeling
• Mixture of Experts & reasoning models
• Knowledge distillation for SLMs

Computer Vision & Multimodal AI (6 hours)

• ViT, CLIP, SigLIP & DINOv2
• LLaVA & Qwen-2-VL vision-language models
• ColPali vision RAG pipelines
• Speech AI & conversational audio systems

Production RAG & Vector Systems (8 hours)

• Embedding systems & vector databases
• Hybrid BM25 + HNSW retrieval with Qdrant
• GraphRAG & multimodal retrieval
• RAG evaluation with RAGAS & score-gated deployment

Agentic AI & Multi-Agent Systems (10 hours)

• LangGraph stateful swarms & checkpointing
• MCP & A2A protocol integration
• n8n workflow automation & FastMCP nodes
• Human-in-the-loop agent orchestration

LLMOps, Security & Cloud Deployment (10 hours)

• LangSmith, Langfuse & production observability
• NeMo guardrails, RBAC & prompt injection defense
• Docker, Kubernetes & vLLM model serving
• Multi-cloud deployment on AWS, GCP & Azure