GenAI Cloud Engineering
GenAI Cloud Engineer Program
Design, deploy, and govern production LLM systems — RAG, agentic orchestration, model routing, and trust architecture — capped by a real business-case capstone project.
Intermediate
Pro plan
Sign Up to Enroll
Curriculum
1. Foundations of Generative AI for Cloud Engineers
1.1 What a GenAI Cloud Engineer Actually Does
Free Preview
1.2 LLM Fundamentals an Engineer Actually Needs
🔒 Locked
1.3 The Production GenAI Stack, End to End
🔒 Locked
2. Retrieval-Augmented Generation (RAG) Architecture
2.1 Why RAG Exists
🔒 Locked
2.2 Chunking, Embeddings, and Vector Search
🔒 Locked
2.3 From Retrieved Chunks to a Grounded Prompt
🔒 Locked
3. Agentic Systems & Orchestration
3.1 What Makes a System "Agentic"
🔒 Locked
3.2 Multi-Agent Patterns: Separating Concerns
🔒 Locked
3.3 Event-Driven Pipelines vs. Polling
🔒 Locked
4. Cloud Deployment & Model Operations
4.1 Deploying LLM Workloads on Cloud Infrastructure
🔒 Locked
4.2 Tiered Model Routing for Cost Control
🔒 Locked
4.3 Observability & LLMOps
🔒 Locked
5. Trust, Safety & Governance
5.1 Guardrails and Content Safety
🔒 Locked
5.2 Citations, Verification, and Human-in-the-Loop
🔒 Locked
5.3 Identity, Security, and Compliance
🔒 Locked
6. Capstone: The Final Business-Case Assessment
6.1 How the Capstone Project Works
🔒 Locked
6.2 Example Submission: Lead Research Automation
🔒 Locked