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Deep learning models are data-hungry; but what if you could leverage a pre-trained network to solve your problem with much less data?

In deep learning, a model can either underfit (not learn enough from the data) or overfit (memorize the data, losing the ability to generalize).

Once you’ve built and trained your model, what’s next? You need to persist it so that it can be used later without retraining — whether that’s for evaluation, deployment, or inference on new data.

This hands-on course introduces the fundamentals of deep learning, neural networks, and PyTorch—one of the most widely used deep learning frameworks.

This immersive 3-hour hands-on training explores how AI-powered coding tools enhance software development.

Claude Code is Anthropic’s agentic coding assistant that runs directly in a developer’s terminal and works with the local codebase. It can analyze projects, edit files, run commands, and automate development tasks through natural-language instructions.

This course introduces the artificial intelligence capabilities available on Microsoft Azure. Participants will explore core AI concepts and learn how organizations use Azure AI services to build intelligent applications.

This course teaches developers how to build generative AI applications using Azure OpenAI Service. Participants will learn how to use large language models to create intelligent applications, integrate enterprise data, and implement prompt engineering techniques.

This course teaches participants how to build intelligent AI agents using Azure AI Studio. Learners will design conversational agents capable of retrieving knowledge, interacting with users, and performing automated tasks.