This course prepares you to apply Microsoft Copilot to core generative AI use cases in data science, from model building and data augmentation to risk management and responsible AI practices. Designed for data scientists, ML practitioners, and technically oriented data professionals who want to go beyond prompt-based workflows and understand how generative AI actually works — and how to use it responsibly — this course bridges foundational GenAI concepts with practical, Copilot-powered implementation. Whether you're new to generative AI or looking to formalize how it fits into your data science pipeline, you'll build both the theoretical grounding and hands-on skills needed to integrate Copilot into sophisticated, real-world workflows.

Generative AI for Data Science with Copilot

Generative AI for Data Science with Copilot
This course is part of Generative AI for Data Scientists Specialization

Instructor: Microsoft
Access provided by National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”
6,538 already enrolled
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What you'll learn
Define and differentiate types of generative AI models
Use Microsoft Copilot to generate code, analyze data, and build generative models
Identify practical use cases for generative AI in data science, such as data augmentation and anomaly detection
Assess the strengths and weaknesses of different generative models and understand their ethical implications
Skills you'll gain
Tools you'll learn
Details to know

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