This course is intended for learners who already understand model training and want to reason about the surrounding operational process.
Optional preparation: Free AI Fundamentals Course: Machine Learning Concepts.
About this course
Explore MLOps and Azure Machine Learning through a three-part technical series. The lessons are presented in numbered order to support a connected discussion of scaling machine learning work. This course is intended for learners who already understand model training and want to reason about the surrounding operational process.
What you can learn
- Connect machine learning work with operational workflows
- Review repeatable development and deployment practices
- Consider what changes as an ML practice grows
Course at a glance
| Provider | Microsoft |
|---|---|
| Platform | YouTube · Microsoft Developer |
| Access | Free Video |
| Level | Intermediate — WikiFree audience assessment |
| Language | English |
| Selected lessons | 3 |
| Video duration | 32m · allow extra time for reflection and practice |
| Details checked | 9 October 2026 |
Try this learning exercise
Draw a workflow from a versioned dataset to an evaluated model and a deployment decision. Mark which artifacts should be recorded, what approval evidence is needed, and where a failed model should stop.
How to follow the course
Choose a lesson from the list or search for a specific topic. Use Previous and Next to continue, and mark lessons complete as you go. Progress is saved in this browser without a WikiFree account.
The classroom follows the numbered lesson parts. The source playlist currently places some parts out of sequence.
Free access, tools and certificates
The selected public YouTube videos are free to watch. No paid subscription, payment card, examination, or software purchase is required for this video learning path. This listing does not include a Microsoft certification, assessed assignment, or instructor feedback.
The learning exercise above can be completed as a written plan without provisioning services. Reproducing demonstrations with Azure, hosted models, enterprise products, hardware, or optional software may require an account, separate access, or paid resources. Those activities are not required to complete the video course. Recorded interfaces and commands may differ from current versions.
Official Microsoft Developer playlist source ↗
Related courses for your next step
- Review a lower-level optionFree AI Fundamentals Course: Machine Learning Concepts
Focus: Understand the purpose of machine learning · Explore how a model learns from examples
Beginner - Compare another approachIntroduction to Machine Learning in Production: Free Course
Focus: ML lifecycle · Deployment planning
Intermediate - Compare another approachMLOps Getting Started: Free Google Course Instruction
Focus: ML lifecycle analysis · MLOps vocabulary
Intermediate
Compare course focus, level and study time
| Course | Level | Focus | Study time |
|---|---|---|---|
| This course — Free MLOps Course: Azure Machine Learning Workflows | Intermediate | Connect machine learning work with operational workflows · Review repeatable development and deployment practices · Consider what changes as an ML practice grows | 32m of video; practice time is additional |
| Free AI Fundamentals Course: Machine Learning Concepts | Beginner | Understand the purpose of machine learning · Explore how a model learns from examples · Recognize a classification problem | 34m of video; practice time is additional |
| Introduction to Machine Learning in Production: Free Course | Intermediate | ML lifecycle · Deployment planning · Model monitoring | 5h 11m of video; practice time is additional |
| MLOps Getting Started: Free Google Course Instruction | Intermediate | ML lifecycle analysis · MLOps vocabulary · Workflow-automation planning | 4 hours 30 minutes; provider full-course estimate including practical activities; instruction-only study time may differ. |
Provider: Microsoft. Videos play from the Microsoft Developer channel on YouTube.
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