Intermediate Artificial Intelligence 14 hours Featured

AI System Design Masterclass 2026: Build Scalable LLM, RAG, and Agentic Systems

A FAANG-grade, hands-on system design course for the LLM era — original case studies, reference architectures and an interview playbook.

6 Chapters

34 Lessons

636 min total

Open Access

Most engineering interviews now expect you to design *AI* systems, not just CRUD apps. This masterclass closes that gap with the same rigor used inside FAANG architecture reviews — applied to real LLM, RAG, agentic and m...

What you'll learn

Introduction to AI System Design
Foundations of Scalable AI Systems
Production AI Case Studies
Reliability, Safety and Compliance
Practice Problems
Solutions and Reference Architectures

Engr. Mejba Ahmed

Course Instructor

Open Access / Start learning instantly

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Chapters 6

Lessons 34

Duration 14 hours

Level Intermediate

Certificate On Completion

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About This Course

Most engineering interviews now expect you to design AI systems, not just CRUD apps. This masterclass closes that gap with the same rigor used inside FAANG architecture reviews — applied to real LLM, RAG, agentic and multimodal systems.

You will learn the latency, cost and reliability trade-offs that separate a demo from a production AI product, study eleven original end-to-end case studies (chat assistants, RAG over millions of docs, code copilots, multi-agent research, real-time voice, image generation at scale, healthcare-grade AI and more), and finish with three interview-style design briefs plus reference architectures you can re-use at work.

Every diagram, decision and trade-off in this course is written from scratch — no scraped material, no copyright risk. By the end you will be able to walk into a senior or staff-level AI system design interview and lead the whiteboard.

Course Curriculum

6 chapters 34 lessons 636 min

2 lessons available to preview

1 Why AI System Design Matters in 2026

Preview 14min

2 High-Level vs Low-Level AI System Design

Preview 13min

3 How to Approach an AI System Design Interview

16min

1 Latency, Throughput and Cost — the AI Triangle

18min

2 LLM Inference 101: Tokens, Context Windows, KV Cache

20min

3 Embeddings, Vector Databases and ANN Search

17min

4 Retrieval-Augmented Generation (RAG) Architecture

22min

5 Caching Strategies for LLM Workloads

15min

6 Prompt Pipelines, Guardrails and Evaluation Loops

19min

7 Streaming, Backpressure and Token-Level Reliability

14min

8 Cost Optimisation: Routing, Distillation, Quantisation

18min

1 Design a ChatGPT-Style Conversational Assistant

24min

2 Design a Production RAG System Over 10M Documents

26min

3 Design a Multimodal Search Engine (Text + Image)

22min

4 Design a Code Assistant Like GitHub Copilot

25min

5 Design a Multi-Agent Research Workflow

23min

6 Design a Real-Time AI Voice Agent

24min

7 Design an LLM Observability and Evaluation Platform

21min

8 Design an AI Image Generation Service at Scale

22min

9 Design a Personalised Recommendation Engine With LLMs

20min

10 Design a Compliance-Safe Healthcare AI Assistant

24min

11 Design an Enterprise AI Knowledge Base With Access Control

22min

1 Hallucination Mitigation Patterns

18min

2 Red Teaming and Adversarial Testing

17min

3 Privacy-Preserving AI: PII, Tokenisation and On-Device Inference

16min

4 Compliance: SOC 2, GDPR and HIPAA for AI Systems

19min

5 Fallback, Circuit Breakers and Graceful Degradation

16min

1 Mini-Brief — Design a Slack-Style AI Search

10min

2 Mini-Brief — Design an AI Customer-Support Triage System

10min

3 Mini-Brief — Design a Multi-Tenant LLM Gateway

11min

1 Reference Architecture: Production RAG

22min

2 Reference Architecture: Agentic Workflow Orchestrator

21min

3 Reference Architecture: Multi-Tenant LLM Gateway

19min

4 Career Track — How to Crack AI System Design Interviews at FAANG

18min

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