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MLOps: Deploying Machine Learning & Deep Learning Models

MLOps Capstone

One model, from notebook to a monitored cloud service — every part of this track in one project.

Level
Intermediate
Lessons
2
Total time
1h 14m
Simulations
1
Included in MLOps: Deploying Machine Learning & Deep Learning Models · $9
Tools you'll use
  • Python
  • Docker
  • FastAPI
  • Kubernetes
  • GitHub
Skills
  • Cloud deployment
  • End-to-end ML systems

What you will be able to do

  • Release and monitor a real model in the cloud

Before you start

A suggestion, never a lock — you can start here.

  • monitoring-and-retraining
Modules that help first

Syllabus

2 lessons · 1h 14m

Every lesson's title and summary is public. The lessons themselves open once you own the track.

Every lesson in MLOps: Deploying Machine Learning & Deep Learning Models

  1. Choosing Cloud Infrastructure

    14 min

    Serverless, managed containers or VMs — chosen from three numbers you must know first: request volume, latency budget, and whether a GPU is involved.

    Included with the track

  2. Capstone: Deploy and Monitor

    1h

    One real model, from a tracked training pipeline to a containerised API, CI, a nightly drift job and a runbook — every part of this track in one repo someone else could run.

    Included with the track Simulation
Lifetime access
$9
Buy the track
More in MLOps: Deploying Machine Learning & Deep Learning Models
Module · Intermediate

ML Systems in Production

Why models degrade after launch, how batch and online inference differ, and what to monitor.

  • 4 lessons
  • 1h 4m
  • 4 simulations
Included in MLOps: Deploying Machine Learning & Deep Learning Models· $9
Module · Intermediate

Packaging and Serving Models

From notebook to service: saving models, an API with FastAPI, and reproducible Docker containers.

  • 3 lessons
  • 48 min
Included in MLOps: Deploying Machine Learning & Deep Learning Models· $9
Module · Intermediate

Serving Deep Learning Models and LLMs

GPUs, batching, quantisation and formats like ONNX — making large models fast enough and cheap enough.

  • 4 lessons
  • 1h 6m
Included in MLOps: Deploying Machine Learning & Deep Learning Models· $9
Module · Intermediate

ML Pipelines and CI/CD

Experiment tracking, model registries, and automated pipelines from raw data to a released model.

  • 3 lessons
  • 47 min
  • 2 simulations
Included in MLOps: Deploying Machine Learning & Deep Learning Models· $9