Made With ML

Goku Mohandas connects machine-learning development with the software and operational practices needed to maintain it. The curriculum includes tracking, testing, serving, orchestration and CI/CD around an end-to-end system. Its technical examples suit learners ready to follow the code and investigate how individual components work together.

What you will learn

• Connect tracking and testing with model development.
• Serve and orchestrate an ML application.
• Organize continuous training and deployment workflows.

Who this suits

Developers and technical learners ready to work through Python-based machine-learning examples; review the setup instructions before beginning.

Before you enroll

Check the cloud-account, software and lab requirements before enrolling. Hosting, storage and GPU resources can incur separate charges. Use permitted sample data, record dependencies and test a rollback or failed pipeline step alongside the successful deployment.

The written curriculum and linked code are publicly accessible. Optional live-cohort arrangements are separate; check their current terms. This listing does not promise a completion certificate, and external compute can have separate costs.

Put it into practice

Follow a small permitted model through development and serving, then record which tests and versioned artifacts make its behavior reproducible.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

Level and duration filters are editorial estimates for completing the technical curriculum and project work; the provider allows self-paced study.

View the curriculum and current access options at Made With ML.

How YellowCourse describes and checks learning resources.