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Artificial Intelligence & Machine Learning (AI/ML) for Application Developers

This 2-day workshop introduces what is necessary to leverage one of the most powerful tools in technology today - Artificial Intelligence and Machine Learning (AI/ML). The course will balance concept, theory, implementation, and practice to provide participants with a foundation for understanding machine learning. This course is ideal for application developers who desire a hands-on approach to learning and want an intro to Machine Learning.

Full Course Description
This class is currently only offered privately.
Please contact us about scheduling a private class.

AI/ML for Application Developers Course Details

The AI/ML for Application Developers course will be implemented with Microsoft’s ML.NET in the C# programming language. Any app developer familiar with OOP concepts and a basic understanding of C# will do well – the focus is on building a machine-learning model using the toolset. No experience with ML is required; this class will provide the foundational knowledge, and we will build a few intro-level machine learning models in the labs. We will also learn to utilize hosted AI services on Microsoft Azure.

Students will bring a computer ready to develop in .NET 8 SDK with an IDE such as Visual Studio Code. Python will also be demonstrated, but prior experience with Python is optional. Day 2 has multiple lab options for students in either C# .NET or Python. Students leave the class after building many types of models and a great intro foundation in Machine Learning.


  • Basic knowledge of C#.NET

  • Basic understanding of data storage and analysis

Learning Outcomes

  • Understanding the power and scope of Artificial Intelligence offerings

  • Designing data analysis systems for Machine Learning

  • Developing feedback tools and processes to train machine learning models

  • Developing machine learning models for data analysis

  • Developing machine learning models for image and video analysis

  • Implementing industry cloud tools for process acceleration

  • Deployment and Operations of Machine Learning tools (e.g. ML Ops, Weka, etc)

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