AI Engineering — Specialty

What you'll learn

Course modules

1. 01

   AI engineering vs ML engineering — the new role

   AI Engineer emerged as a distinct role in 2024-2026 alongside the LLM revolution. This module covers what changed, how AI engineering differs from traditional ML engineering, the skills needed, and why this is one of the fastest-growing careers in tech.

   ~750min
2. 02

   Working with LLMs — APIs, models, systematic prompt engineering

   Production LLM work requires fluency with APIs, model selection, and systematic prompt engineering. This module covers the major LLM APIs, model selection criteria, prompt engineering as discipline, and the patterns senior AI engineers know.

   ~750min
3. 03

   RAG systems — vector DBs, embeddings, retrieval, reranking

   Retrieval-Augmented Generation grounds LLMs in your data. This module covers RAG architecture, embedding models, vector databases, chunking strategies, retrieval methods, reranking, and the production patterns senior AI engineers know.

   ~750min
4. 04

   Fine-tuning and customization — LoRA, RLHF, when it helps

   Fine-tuning customizes models on your data. This module covers when fine-tuning helps vs hurts, fine-tuning approaches (full, LoRA, QLoRA), instruction tuning, RLHF basics, and the senior decision framework for customization.

   ~750min
5. 05

   Agents and tool use — function calling, agent loops, frameworks

   AI agents take actions, not just generate text. This module covers function calling, agent architectures, common frameworks (LangChain, LlamaIndex, custom), patterns for reliable agents, and the senior production guardrails.

   ~750min
6. 06

   Production LLM apps — latency, cost, evaluation, reliability

   Building LLM apps in production requires solving real engineering problems: latency optimization, cost management, evaluation, reliability, monitoring. This module covers the production patterns that turn prototypes into reliable products.

   ~750min
7. 07

   Safety and reliability — prompt injection, hallucinations, content filtering

   Production LLM apps face attack vectors and quality issues that traditional software doesn't. This module covers prompt injection defenses, hallucination mitigation, content filtering, output validation, and the safety patterns senior AI engineers must know.

   ~750min
8. 08

   Careers, startups, and the future of AI engineering

   AI engineering is among the fastest-growing careers. This module covers AI engineering roles, paths to top companies, founding AI startups, the open vs closed model debate, the future trajectory, and how to position yourself.

   ~750min