Machine Learning Model Deployment
Databricks
Last updated June 30, 2026
Machine Learning Model Deployment is a free, two-hour, hands-on course on the step that turns a trained model into something people can actually use. It walks through three core deployment strategies and shows how to implement each on the Databricks platform — so you can match the right approach to how a model will be called in practice. It assumes Python and a working grasp of machine learning models, and it's aimed at the developer who has a model and now needs to serve it.
What you'll learn
- Why deployment is its own distinct skill, separate from training
- Three core strategies for deploying a machine learning model
- How to implement each strategy in practice
- Matching a deployment approach to how a model will be used
- Carrying it out on the Databricks platform
Frequently asked questions about Machine Learning Model Deployment
Who is Machine Learning Model Deployment for?
Developers who can train a machine learning model and want hands-on practice deploying one using the right strategy for the job.
Is Machine Learning Model Deployment free?
Yes — Machine Learning Model Deployment is completely free to take.
What are the prerequisites for Machine Learning Model Deployment?
Python; the basics of machine learning models; familiarity with Databricks. A free Databricks Academy account is required to start.
Do you need to code for Machine Learning Model Deployment?
Yes — Machine Learning Model Deployment involves hands-on coding.
Why we suggest this course
Concentrates on a single high-value skill — serving a trained model three different ways — so a developer can pick the deployment approach that fits the job. One thing to know: each strategy is implemented on Databricks and needs a free Academy account, so the how-to is grounded in that platform.