Introduction to Generative AI for Data Analysis

This course is part of Microsoft Generative AI for Data Analysis Professional Certificate

Instructor: Microsoft

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5 modules

Gain insight into a topic and learn the fundamentals.

91 reviews

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

5 modules

Gain insight into a topic and learn the fundamentals.

91 reviews

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

29 assignments

Taught in English

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Build your Data Analysis expertise

This course is part of the Microsoft Generative AI for Data Analysis Professional Certificate

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

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 from Microsoft

There are 5 modules in this course

This foundational course provides a comprehensive understanding of generative AI and its applications in data analysis. You'll explore key tools and platforms, learn to integrate AI into existing workflows, and master prompt engineering for various data analysis tasks.

Develop a foundational understanding of what Generative AI is, its current applications in data analysis, and the key tools and platforms available.

What's included

7 videos8 readings4 assignments

7 videos Total 39 minutes

Welcome to generative AI for data analysis certificate 4 minutes
What is generative AI? 6 minutes
The creative potential of generative AI 6 minutes
Applying generative AI in data analysis 6 minutes
The field of generative AI 6 minutes
Microsoft Copilot for data analysis: A walkthrough 6 minutes
Integrating Microsoft Fabric/PowerBI/365 into workflows 6 minutes

8 readings Total 80 minutes

Generative AI for data analysts certificate syllabus overview 10 minutes
Coursera Community: Introduce yourself and say hi to your classmates 10 minutes
A paradigm shift in data analysis 10 minutes
Case studies: How generative AI is transforming data analysis 10 minutes
GenAI Tools for Data Analysis: A Practical Guide 10 minutes
Choosing the right generative AI tool: A guide for data analysts 10 minutes
Power BI and Generative AI: A powerful combination 10 minutes
Best practices for integrating Generative AI into your data analysis workflow 10 minutes

4 assignments Total 90 minutes

Project: Data analysis challenge 30 minutes
Introduction to Generative AI 30 minutes
Defining generative AI and its impact 15 minutes
Tools and platforms for data analysis 15 minutes

Integrate generative AI tools into their existing data analysis workflows to streamline data exploration, uncover insights, and enhance decision-making processes.

What's included

9 videos6 readings6 assignments

9 videos Total 47 minutes

Data exploration essentials: Key terms and concepts for analysts 5 minutes
The language of data: Visualizing key exploration concepts 2 minutes
How to ask effective questions: A guide to data exploration 5 minutes
Streamlining data exploration with generative AI tools 6 minutes
Demo: Data exploration with Microsoft Copilot 6 minutes
GenAI for data exploration: Best practices and tips 6 minutes
How to craft effective queries for generative AI 6 minutes
Demo: Refining prompts for better insights 6 minutes
Evaluating insights from generative AI: Separating facts from claims 6 minutes

6 readings Total 60 minutes

Data exploration: An introduction for data analysts 10 minutes
Asking the right questions: A guide to data exploration 10 minutes
Generative AI for data exploration: New possibilities 10 minutes
Case study: Data exploration with generative AI 10 minutes
Assessing the validity of generative AI insights: A framework for data analysts 10 minutes
Challenges and limitations of generative AI in data exploration 10 minutes

6 assignments Total 105 minutes

Activity: Data detective: Uncover the clues 15 minutes
Data exploration with generative AI 30 minutes
Key terms and questions in data exploration 15 minutes
Leveraging Generative AI for data exploration 15 minutes
Activity: Data detective: The first look 15 minutes
Analyzing a dataset with GenAI 15 minutes

Apply generative AI tools to investigate and summarize datasets, and identify patterns and relationships, and formulate hypotheses for further analysis.

What's included

7 videos8 readings6 assignments

7 videos Total 35 minutes

GenAI's role in uncovering inconsistencies 6 minutes
Demo: Automatic inconsistency flagging 6 minutes
Visualizing data inconsistency: A guided tour 2 minutes
Decoding GenAI reports: Understanding the impact of data inconsistencies 6 minutes
From report to action: Making informed decisions with GenAI insights 6 minutes
The outlier effect: How GenAI helps spot and address anomalies 3 minutes
Data transformation fundamentals: Why it matters for accurate analysis 6 minutes

8 readings Total 80 minutes

The data cleaning dilemma: How GenAI offers solutions 10 minutes
Beyond the basics: Advanced data cleaning techniques with GenAI 10 minutes
Data quality is key: Using GenAI to prioritize cleaning efforts 10 minutes
The ethics of automated data cleaning: Balancing efficiency and responsibility 10 minutes
The art and science of missing data: GenAI as your assistant 10 minutes
Beyond removal: When outliers are insights, not errors 10 minutes
The data transformation toolkit 10 minutes
Feature engineering in the age of GenAI: A balanced approach 10 minutes

6 assignments Total 90 minutes

Project: Unveiling Data Inconsistencies with GenAI 15 minutes
Project: Addressing data inconsistencies by cleaning your dataset with GenAI 15 minutes
Data Cleaning with GenAI 15 minutes
Identifying and categorizing data inconsistencies 15 minutes
Evaluating impact and making decisions 15 minutes
Imputing missing values and handling outliers 15 minutes

Develop the skills to create and optimize effective prompts for diverse data analysis tasks, enhancing the quality and efficiency of data cleaning, analysis, and visualization outcomes.

What's included

6 videos9 readings7 assignments

6 videos Total 28 minutes

The prompt makeover: From vague to valuable 3 minutes
Improving your prompts: Strategies for refinement 5 minutes
Sculpting your prompts: The art of iterative refinement 3 minutes
Learning paradigms in GenAI: Using examples effectively 5 minutes
Zero-shot, one-shot and few shot learning 7 minutes
Effective prompting: Using the RACE and PARE frameworks 5 minutes

9 readings Total 90 minutes

The art of prompting: A guide for data analysts 10 minutes
Prompt gallery: Real-world examples for inspiration 10 minutes
Iterative prompt refinement: A data analyst's secret weapon 10 minutes
Prompt engineering cheat sheet: Quick tips for data analysts 10 minutes
Zero-shot, one-shot, and few-shot learning with generative AI 10 minutes
Practical applications of learning paradigms in data analysis 10 minutes
Discussion: Choosing the right learning paradigm 10 minutes
Prompting with purpose: The RACE framework for data analysis 10 minutes
Using the PARE framework to ensure quality insights 10 minutes

7 assignments Total 115 minutes

Activity: Prompt refinement 15 minutes
Project: Evaluating with PARE 10 minutes
Prompt engineering fundamentals 30 minutes
Crafting effective prompts 15 minutes
Optimization techniques 15 minutes
Zero-shot, one-shot, and few-shot learning 15 minutes
Applying the RACE framework 15 minutes

Evaluate and apply ethical, legal, and practical considerations in utilizing generative AI for data analysis, ensuring responsible application and risk mitigation.

What's included

7 videos7 readings6 assignments

7 videos Total 36 minutes

Addressing ethical issues in generative AI: Bias, privacy, and misuse 6 minutes
Garbage in, garbage out: How bias persists in GenAI 3 minutes
AI as a double-edged sword: Power, responsibility, and consequences 3 minutes
The role of an AI ethicist: Balancing innovation and responsibility 6 minutes
Ethical challenges: Addressing issues in generative AI 6 minutes
Built-in safeguards: Comparing GenAI tools for ethical use 6 minutes
Why your organization needs custom ethical AI guidelines 6 minutes

7 readings Total 70 minutes

The ethical landscape of generative AI: A data analyst's perspective 10 minutes
Ethical dilemmas in action: Case studies from the data analysis field 10 minutes
Beyond compliance: Why responsible AI is a competitive advantage 10 minutes
Building an ethical AI framework: A guide for data teams 10 minutes
Before you deploy: Evaluating GenAI use cases for ethical risks 10 minutes
Implementing ethical GenAI: Best practices for data teams 10 minutes
The future of ethical AI: Challenges and opportunities for data analysts 10 minutes

6 assignments Total 115 minutes

Activity: Bias in generative AI 10 minutes
Project: Ensuring ethical use for a Data Analysis scenario 30 minutes
Ethical and Safe Use of GenAI Assessment 30 minutes
Identifying ethical concerns 15 minutes
The importance of responsible AI 15 minutes
Evaluating GenAI use in scenarios 15 minutes

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Instructor

Instructor ratings

(24 ratings)

Microsoft

287 Courses 2,368,381 learners

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Microsoft

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Reviewed on Jul 24, 2025

Too many assignments - some of these can be removed. Mostly theory and missing good practical examples and demos.

Reviewed on Jan 3, 2026

Easy to understand with good examples, resulting in applying the lessons immediately for creating GenAI prompts and workflows.

Reviewed on Mar 9, 2025

Overall it was really good, but theory was too much. Much appreciate if include more practical practices.

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