AI Engineering Professional.
The flagship. Where Fundamentals stops, Professional starts: advanced RAG, fine-tuning, RAGAS evaluation, multimodal AI, LLMOps, cloud deployment, and AI safety. The natural next step after AI Engineering Fundamentals.
Modules
10
Hours of teaching
~33
Hands-on labs
~45
Portfolio projects
9
What you'll learn
The advanced bricks for production LLM systems.
Push RAG past naïve setups with hybrid search, rerankers, and graph retrieval.
Measure RAG quality the production way; faithfulness, relevance, regression dashboards.
Fine-tune open models with LoRA / QLoRA and align them with DPO; know when each is worth it.
Build multimodal systems that read, see, and listen using the same engineering discipline.
Run LLM workloads on real clouds with proper observability, performance budgets, and safety controls.
Module-by-module
Ten advanced modules. Zero overlap with Fundamentals.
Fundamentals taught you tokens, prompts, basic RAG, agents, evaluation, and a first FastAPI deployment. Professional picks up exactly where that ends; advanced retrieval, fine-tuning, multimodal, LLMOps, cloud at scale, and AI safety.
01Advanced RAG: Hybrid Search & Reranking+
BM25 + dense fusion, cross-encoder rerankers, HyDE, query expansion, parent-document retrieval; the techniques that take RAG from demo to production-grade.
02Knowledge-Graph & Agentic Retrieval+
GraphRAG, multi-hop question answering, recursive and agentic retrieval, hierarchical chunking; retrieval patterns for documents naïve RAG can't handle.
03RAG Evaluation with RAGAS+
Faithfulness, answer relevance, context precision and recall, synthetic ground truth, regression dashboards; eval-driven development for retrieval systems.
04Fine-Tuning: SFT, LoRA & QLoRA+
When to fine-tune vs. prompt, dataset curation, supervised fine-tuning, parameter-efficient methods (LoRA, QLoRA), evaluation; the practical fine-tuning loop.
05Preference Alignment: DPO & Reward Modeling+
Preference data collection, direct preference optimization, reward modeling, RLHF intuition; when each method beats plain SFT and how to evaluate alignment.
06Multimodal AI Systems+
Vision-language models, image embeddings, Whisper and TTS, document AI, multimodal RAG; building systems that read, see, and listen.
07Performance Engineering for LLMs+
Semantic and KV caching, request batching, streaming optimization, quantization, vLLM and TGI; meeting real latency and cost budgets.
08LLMOps & Observability at Scale+
Distributed tracing (LangSmith / Phoenix), prompt versioning, A/B testing, drift detection, evals as CI gates; the production discipline for shipping LLM systems.
09Cloud Deployment at Scale+
AWS Bedrock, Azure OpenAI, GCP Vertex, serverless GPU, autoscaling, multi-region failover, cost ops; deploying LLM workloads on the major clouds.
10AI Safety, Security & Governance+
Red-teaming at scale, content filtering, PII detection, GDPR / SOC2 alignment, model governance, audit logs; the enterprise-readiness layer.
Projects you'll add to your portfolio
Nine advanced castles. Senior-engineer evidence.
Not notebook tours. Production-grade systems you rebuild from scratch and can defend in a senior or staff-level interview.
- 01
Hybrid-Search + Reranking RAG (BM25 + dense + cross-encoder)
- 02
GraphRAG Multi-Hop Question Answering Engine
- 03
RAGAS Evaluation Dashboard with regression tracking
- 04
Domain-Specific LoRA Fine-Tune (full SFT pipeline)
- 05
DPO Preference Alignment on a small open model
- 06
Multimodal Document-QA System (vision + text + audio)
- 07
High-Throughput vLLM / TGI Inference Service
- 08
LLMOps Stack: tracing, prompt versioning, eval-CI
- 09
Multi-Region Cloud Deployment on Bedrock or Vertex
Built for
- • Engineers shipping AI features in production
- • ML / DL practitioners moving up the stack to LLM systems
- • Data scientists ready to build full products
- • Anyone who finished AI Engineering Fundamentals and wants more
Not built for
- • Total beginners (start with Fundamentals first)
- • “AI in 30 days” shortcut seekers
- • Framework collectors who don't want first principles
- • People who'd rather watch than build
The course is on its way
Be the first to know when it opens.
Drop your email and we'll send you the launch announcement, early-access pricing, and a free preview module; no spam, no fake countdown timers.
Free. Unsubscribe anytime. We don't do scarcity tricks.