Video course · 5 chapters · 48 min · certificate
How to Design a Machine Learning Training Solution
An overview of operationalizing machine learning and generative AI on Azure: what the AI-300 course covers, the materials and exam, and the core of designing training solutions that are secure, scalable and monitored.
What you'll learn
- Describe the scope of operationalizing ML and GenAI
- Navigate course labs and certification resources
- Identify data types and training approaches
- Design a training solution in Azure Machine Learning
- Understand MLOps automation with pipelines
- Check understanding with a knowledge check
Chapters
5 chapters · 48:00-
1:06
01Intro Members
Welcome to AI-300
An introduction to operationalizing machine learning and generative AI solutions.
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6:22
02Scope Members
Course overview
Training and optimizing in Azure ML, automating MLOps with pipelines and GitHub Actions, deploying and monitoring models.
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1:48
03Resources Members
Materials and certification
Hands-on labs, open lab repositories for MLOps and GenAIOps, and the certification exam.
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36:54
04Core Members
Designing the training solution
Bridging experimentation and real impact: data, training approaches, and secure, scalable, monitored operations.
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1:50
05Review Members
Knowledge check
Checking understanding: data types like semi-structured JSON and tools for fast iteration.
Jobs this course suits
Our AI checked this course against 500 jobs; these get the most out of it. Each job links to its learning path.