5 Lessons
Staff AI Infrastructure Engineer
★ 4.97
(2,800+ Engineers Enrolled)
AI Infrastructure, GPU Serving & MLOps (CUDA, Triton, TGI)
GPU Acceleration (CUDA), Triton Inference Server, MLflow Registry & NeMo Guardrails
⏱️ 35 Hours
📖 6 Modules
⚡ 18 Interactive Lessons
🏆 Free Verified Certificate
Complete Track Curriculum & Modules
Step-by-step interactive lessons with live browser compilers & coding assignments.
18 Lessons
1
3 Lessons
Module 1: GPU Architecture, CUDA Internals & Hardware Hierarchy
01. NVIDIA GPU Architecture: Streaming Multiprocessors (SMs), Tensor Cores, CUDA Cores & HBM3 Memory Bandwidth
⏱️ 45 mins
•
⚡ Interactive Sandbox
02. GPU Memory Hierarchy: Registers, Shared Memory (SRAM), L1/L2 Caches & High-Bandwidth VRAM
⏱️ 45 mins
•
⚡ Interactive Sandbox
03. CUDA Programming Basics: Writing Custom GPU Kernels in C++/CUDA & Triton Python DSL
⏱️ 55 mins
•
⚡ Interactive Sandbox
2
0 Lessons
Part 1: GPU Acceleration, Serving & Production Guardrails
3
4 Lessons
Module 2: High-Performance LLM Serving Engines (vLLM, TGI, Triton)
04. The KV Cache Bottleneck: Memory Footprint Calculations & PagedAttention Virtual Memory Architecture
⏱️ 50 mins
•
⚡ Interactive Sandbox
05. Dynamic & Continuous Batching (Iteration-Level Scheduling) vs Static Batching in LLM Serving
⏱️ 45 mins
•
⚡ Interactive Sandbox
06. Production Benchmark: vLLM vs HuggingFace TGI (Text Generation Inference) vs NVIDIA Triton Inference Server
⏱️ 50 mins
•
⚡ Interactive Sandbox
07. Speculative Decoding & Medusa Multi-Head Decoding for 2-3x Faster Token Generation
⏱️ 50 mins
•
⚡ Interactive Sandbox
4
3 Lessons
Module 3: Multi-GPU & Distributed Inference: Tensor & Pipeline Parallelism
08. Distributed AI Parallelism Paradigms: Data Parallelism (DP), Tensor Parallelism (TP), Pipeline Parallelism (PP)
⏱️ 50 mins
•
⚡ Interactive Sandbox
09. Tensor Parallelism in Action: Megatron-LM Matrix Splitting across NVLink & NVSwitch Networks
⏱️ 55 mins
•
⚡ Interactive Sandbox
10. DeepSpeed & PyTorch FSDP (Fully Sharded Data Parallel): Zero Redundancy Optimizer (ZeRO-1, ZeRO-2, ZeRO-3)
⏱️ 55 mins
•
⚡ Interactive Sandbox
5
3 Lessons
Module 4: MLOps Pipelines: Model Registry, Experiment Tracking (MLflow/W&B)
11. MLOps Foundations: Model Versioning, Artifact Registries & Lineage Tracking with MLflow and Weights & Biases
⏱️ 45 mins
•
⚡ Interactive Sandbox
12. Automated Continuous Training Pipelines with Kubeflow Pipelines & GitHub Actions CI/CD for AI Models
⏱️ 50 mins
•
⚡ Interactive Sandbox
13. Feature Stores in Production (Feast): Real-Time Online Feature Retrieval vs Offline Batch Processing
⏱️ 45 mins
•
⚡ Interactive Sandbox
6
5 Lessons
Module 5: Kubernetes GPU Orchestration, Auto-Scaling & Continuous Observability
14. Kubernetes for AI Workloads: NVIDIA GPU Operator, Device Plugins & Time-Slicing vs Multi-Instance GPU (MIG)
⏱️ 50 mins
•
⚡ Interactive Sandbox
15. Horizontal Pod Auto-Scaling (HPA) for LLM Services based on TTFT (Time to First Token) & Queue Depth
⏱️ 50 mins
•
⚡ Interactive Sandbox
16. Serverless GPU Architecture: Ray Serve, Modal & RunPod for Auto-Scaling AI APIs with Zero Cold Starts
⏱️ 50 mins
•
⚡ Interactive Sandbox
17. Observability for GenAI: OpenLLMetry, Arize Phoenix, Langfuse & Prometheus GPU Utilization Metrics
⏱️ 45 mins
•
⚡ Interactive Sandbox
18. Enterprise Cloud Cost Optimization: Spot GPU Instances, Multi-Cloud Orchestration & Slicing VRAM Costs
⏱️ 45 mins
•
⚡ Interactive Sandbox
Target Big Tech Roles
Google / Meta SDE-2
Senior Full-Stack Architect
Lead Backend Engineer
Skills You Will Master
- Production-Grade Clean Architecture
- V8 Internals, Memory Profiling & Leaks
- Time & Space Complexity Optimization
- Big Tech Behavioral & System Design Edge
Verified Digital Certificate
Complete all 18 lessons to earn a verifiable certificate with unique validation hash for LinkedIn.
Sign In to Unlock Certificate →
⚡
Live Interactive Sandbox
Test real-time code without installing Node, Python or C++ locally. Instant output in browser!
Launch Code Sandbox (8-in-1)