Learn to create Machine Learning Models through the machine learning path in Microsoft Learn Platform. Check the details below!
About Microsoft Learn
Microsoft Learn is a free online platform that provides interactive, hands-on training on Microsoft products and technologies. It offers a wide variety of content, including modules, paths, sandboxes, and certifications. Microsoft Learn is a great resource for anyone who wants to learn about Microsoft products and technologies.
The modules and paths on Microsoft Learn are designed to be interactive, so you can learn by doing. The content on Microsoft Learn is also constantly being updated to reflect the latest changes to Microsoft products and technologies. This makes Microsoft Learn a valuable resource for anyone who wants to stay up-to-date on the latest Microsoft technologies.
About the Course
Microsoft Learn provides several interactive ways to get an introduction to classic machine learning. These learning paths will get you productive on their own, and also are an excellent base for moving on to deep learning topics.
From the most basic classical machine learning models to exploratory data analysis and customizing architectures, you’ll be guided by easy-to-digest conceptual content and interactive Jupyter notebooks, all without leaving your browser. These modules teach some machine learning concepts but move fast so they can get to the power of using tools like sci-kit-learn, TensorFlow, and PyTorch. This learning path is also the best one for you if you’re looking for just enough familiarity to understand machine learning examples for products like Azure ML or Azure Databricks.
Topics
- Explore and analyze data with Python
- Train and evaluate regression models
- Train and evaluate classification models
- Train and evaluate clustering models
- Train and evaluate deep learning models
Eligibility
There are no formal prerequisites for the course, but Microsoft recommends knowledge of basic mathematical concepts. Some experience with Python is also beneficial.
How to Apply?
Interested candidates can apply directly via this link.
