This course provides a comprehensive introduction to Generative AI in data science. You'll explore the foundational concepts of generative AI, including GANs, VAEs, and Transformers, and discover how Microsoft Copilot leverages these models to streamline data science workflows.
Generative AI for Data Science with Copilot
This course is part of Microsoft Copilot for Data Science Specialization
Instructor: Microsoft
Sponsored by BrightStar Care
1,823 already enrolled
(12 reviews)
Recommended experience
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
- Computer Science
- Unsupervised Learning
- Cybersecurity
- Anomaly Detection
- Data Security
- Data Governance
- Enterprise Security
- Data Science
- Information Systems Security
- Information Assurance
- Artificial Intelligence
- Generative AI
- Data Analysis
- Machine Learning
- Artificial Intelligence and Machine Learning (AI/ML)
- Data Ethics
- Information Privacy
- Cyber Governance
Details to know
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6 assignments
September 2024
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There are 3 modules in this course
This module provides a comprehensive introduction to generative AI, exploring its definition, key concepts like GANs, VAEs, and Transformers, and highlighting the role of Microsoft Copilot in enhancing data science workflows through code generation, data analysis, and bias mitigation. It also addresses the ethical implications of generative AI and provides practical guidance on integrating Copilot into existing data science practices.
What's included
12 videos5 readings2 assignments
This module dives into practical applications of generative AI in data science, demonstrating how tools like Microsoft Copilot can be used to augment data, uncover hidden patterns, detect anomalies, and simulate scenarios for enhanced decision-making and risk management.
What's included
3 videos5 readings2 assignments
This module dives into the data security and privacy challenges of generative AI, focusing on Microsoft Copilot. You'll learn about potential risks like data breaches and the creation of misleading information, while also exploring strategies and techniques to safeguard data and ensure responsible AI use.
What's included
6 videos3 readings2 assignments1 peer review
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