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 DBS Bank

5,671 already enrolled

3 modules

Gain insight into a topic and learn the fundamentals.

36 reviews

Beginner level

Recommended experience

7 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

36 reviews

Beginner level

Recommended experience

7 hours to complete

Flexible schedule

Learn at your own pace

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

Shareable certificate

Add to your LinkedIn profile

Assessments

6 assignments¹

AI Graded see disclaimer

Taught in English

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Build your subject-matter expertise

This course is part of the Generative AI for Data Scientists Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

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.

You'll gain hands-on experience using Microsoft Copilot to implement generative AI solutions, ultimately enhancing your data science toolkit and preparing you for the future of AI-driven data analysis. Required Course Materials: A Copilot license is required to complete this course. If you don’t have a Microsoft 365 Personal or Family license, you can start a free 30-day trial using the link provided in the 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 videos6 readings2 assignments

12 videos Total 68 minutes

The power of data science with generative AI and Copilot 5 minutes
Getting started with generative AI with Copilot 2 minutes
What Is Generative AI? 3 minutes
Demystifying generative AI: Concepts and Copilot connection 8 minutes
How generative AI works, powered by Copilot 3 minutes
Exploring Copilot's generative AI capabilities 8 minutes
Copilot in action: Real-world data science case study 7 minutes
Demo: Privacy-preserving techniques in action 7 minutes
Bias in Generative AI 4 minutes
Demo: Using Copilot for data analysis and visualization 8 minutes
Mitigating bias in generative models with Copilot 8 minutes
Demo: Copilot for code generation and debugging 5 minutes

6 readings Total 60 minutes

A look at Copilot for data science syllabus 10 minutes
How to Get Started with Microsoft Copilot 10 minutes
Using Copilot with data science 10 minutes
The rise of generative AI in data science with Copilot 10 minutes
Ethical considerations in generative AI and Copilot 10 minutes
Advanced Copilot tips and tricks for data scientists 10 minutes

2 assignments Total 45 minutes

Applying generative AI and Copilot concepts 30 minutes
Applying the basics of generative AI and Copilot 15 minutes

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

3 videos Total 11 minutes

Generative AI: A data scientist's best friend 3 minutes
How generative models learn and create 3 minutes
Designing generative models for specific tasks 5 minutes

5 readings Total 50 minutes

Generative AI in data science 10 minutes
Copilot in action: Real-world examples 10 minutes
Generative models: A deep dive 10 minutes
Practical tips for data augmentation 10 minutes
Evaluating generative models: Metrics and methods 10 minutes

2 assignments Total 45 minutes

Generative AI use cases and data science 30 minutes
Generative models and data augmentation 15 minutes

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.