Advanced Masterclass
AI Infrastructure Mastery
AI Infrastructure Mastery is a guided sequence designed to build your understanding step by step.
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11 Lessons
Production-Ready
Not just theory. Learn the patterns used at companies like Google, Meta, and Uber.
Interactive Progress
Save your progress, mark lessons as complete, and track your path to mastery.
Certification
Earn a verifiable certificate of completion to showcase on your professional profile.
Course Curriculum
Core Lessons
11 Lessons01Vector Embeddings: The Foundation of Modern AI Applications
11 min read
02Advanced RAG Architecture: Beyond Simple Vector Search
2 min read
03Fine-Tuning LLMs: When to Fine-Tune, When to Prompt
10 min read
04LLM Inference Optimization: Quantization, KV Cache, and High-Throughput Serving
14 min read
05Kubernetes for AI Inference: GPUs, Autoscaling, Queues, and Cost Control
12 min read
06AI Infrastructure on AWS: SageMaker, EKS GPU Scheduling, and Cost-Efficient Inference
15 min read
07LLM Evaluation at Scale: LLM-as-Judge, RAGAS, and Building Automated Eval Pipelines
11 min read
08LLM Observability in Production: Traces, Evals, Cost, Latency, and Failure Modes
11 min read
09System Design: Building a Feature Store for Real-Time Machine Learning
5 min read
10MCP for Backend Engineers: Tools, Agents, and Production Guardrails
14 min read
11AI Masterclass: Vector Database Selection (Pinecone vs. Milvus vs. Weaviate)
3 min read
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