⚙️ Career path

MLOps & LLMOps Engineer

Ship models and LLMs to production: registry, serving, monitoring, and safe rollouts.

0 / 33 complete

26 labs · ~8.8h total

Master the systems side of machine learning and LLMs. Deploy model servers and quantize
them for CPU/RAM, version every model in a registry with stage promotions and instant
rollback, run A/B and shadow deployments, and monitor real-time inference latency and
drift - the operational discipline that turns a notebook model into a reliable service.

🐧 Linux Administration Foundation

4 labs · ~2.1h · Open path →

Prerequisite foundations — skip if you already know this.

  1. 1. Command Line & Filesystem 🧪 Lab · 7 steps ○
  2. 2. Users, Permissions, Processes & Automation 🧪 Lab · 7 steps ○
  3. 3. Partitioning, Filesystems & LVM 🧪 Lab · 5 steps ○
  4. 4. Networked Filesystems with NFS 🧪 Lab · 5 steps ○
  5. 5. Linux Administration - Knowledge Check ❓ Quiz ○

🐳 Docker Foundation

7 labs · ~2.6h · Open path →

Prerequisite foundations — skip if you already know this.

  1. 1. Your First Container 🧪 Lab · 3 steps ○
  2. 2. Working with Docker Images 🧪 Lab · 5 steps ○
  3. 3. The Container Lifecycle 🧪 Lab · 5 steps ○
  4. 4. Building Docker Images 🧪 Lab · 5 steps ○
  5. 5. Container Networking 🧪 Lab · 4 steps ○
  6. 6. Volumes & Persistent Storage 🧪 Lab · 4 steps ○
  7. 7. Real-World Container Apps 🧪 Lab · 4 steps ○
  8. 8. Docker - Knowledge Check ❓ Quiz ○

🐍 Python for AI Foundation

3 labs · ~50 min · Open path →

Prerequisite foundations — skip if you already know this.

  1. 1. Python for Data Engineering 🧪 Lab · 3 steps ○
  2. 2. Python for AI Engineering 🧪 Lab · 3 steps ○
  3. 3. Python for Agent Engineering 🧪 Lab · 3 steps ○
  4. 4. Python for AI - Knowledge Check ❓ Quiz ○

⚙️ Machine Learning Engineering

4 labs · ~1.1h · Open path →
  1. 1. Local Model Serving & Benchmarking 🧪 Lab · 3 steps ○
  2. 2. Model Quantization & Profiling 🧪 Lab · 3 steps ○
  3. 3. Embeddings & Similarity Search 🧪 Lab · 3 steps ○
  4. 4. Distributed Training 🧪 Lab · 3 steps ○
  5. 5. Machine Learning - Knowledge Check ❓ Quiz ○

📐 Vector Databases & Semantic Search

1 lab · ~20 min · Open path →
  1. 1. Vector Databases & pgvector 🧪 Lab · 3 steps ○
  2. 2. Vector Databases - Knowledge Check ❓ Quiz ○

🤖 MLOps & AI Infrastructure

6 labs · ~1.5h · Open path →
  1. 1. Deploying & Serving LLMs 🧪 Lab · 3 steps ○
  2. 2. Model Monitoring & Prometheus Metrics 🧪 Lab · 3 steps ○
  3. 3. Model Serving Architectures 🧪 Lab · 3 steps ○
  4. 4. Feature Stores & Real-time ML 🧪 Lab · 2 steps ○
  5. 5. A/B Testing & Shadow Deployments 🧪 Lab · 3 steps ○
  6. 6. Model Registry & Versioning 🧪 Lab · 3 steps ○
  7. 7. MLOps - Knowledge Check ❓ Quiz ○

🛤️ Capstone: End-to-End ML Pipeline

1 lab · ~20 min · Open path →
  1. 1. End-to-End ML Pipeline 🧪 Lab · 3 steps ○
  2. 2. MLOps Capstone - Knowledge Check ❓ Quiz ○