Introduction to Generative AI for Data Analysis

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Introduction to Generative AI for Data Analysis

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

Instructor: Microsoft

21,587 already enrolled

Included with

5 modules

Gain insight into a topic and learn the fundamentals.

99 reviews

Intermediate level

Recommended experience

Flexible schedule

2 weeks at 10 hours a week

Learn at your own pace

94%

Most learners liked this course

5 modules

Gain insight into a topic and learn the fundamentals.

99 reviews

Intermediate level

Recommended experience

Flexible schedule

2 weeks at 10 hours a week

Learn at your own pace

94%

Most learners liked this course

Skills you'll gain

Category: Data Ethics
Category: Anomaly Detection
Category: AI Integrations
Category: Responsible AI
Category: Data Analysis
Category: Exploratory Data Analysis
Category: Transfer Learning
Category: Data Preprocessing
Category: Data Cleansing

Tools you'll learn

Category: Prompt Engineering
Category: Generative AI

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

29 assignments

Taught in English

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 videosTotal 39 minutes

Welcome to generative AI for data analysis certificate4 minutes
What is generative AI?6 minutes
The creative potential of generative AI6 minutes
Applying generative AI in data analysis6 minutes
The field of generative AI6 minutes
Microsoft Copilot for data analysis: A walkthrough6 minutes
Integrating Microsoft Fabric/PowerBI/365 into workflows6 minutes

8 readingsTotal 80 minutes

Generative AI for data analysts certificate syllabus overview10 minutes
Coursera Community: Introduce yourself and say hi to your classmates10 minutes
A paradigm shift in data analysis10 minutes
Case studies: How generative AI is transforming data analysis10 minutes
GenAI Tools for Data Analysis: A Practical Guide10 minutes
Choosing the right generative AI tool: A guide for data analysts10 minutes
Power BI and Generative AI: A powerful combination10 minutes
Best practices for integrating Generative AI into your data analysis workflow10 minutes

4 assignmentsTotal 90 minutes

Project: Data analysis challenge30 minutes
Introduction to Generative AI30 minutes
Defining generative AI and its impact15 minutes
Tools and platforms for data analysis15 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 videosTotal 47 minutes

Data exploration essentials: Key terms and concepts for analysts5 minutes
The language of data: Visualizing key exploration concepts 2 minutes
How to ask effective questions: A guide to data exploration5 minutes
Streamlining data exploration with generative AI tools6 minutes
Demo: Data exploration with Microsoft Copilot6 minutes
GenAI for data exploration: Best practices and tips6 minutes
How to craft effective queries for generative AI6 minutes
Demo: Refining prompts for better insights6 minutes
Evaluating insights from generative AI: Separating facts from claims6 minutes

6 readingsTotal 60 minutes

Data exploration: An introduction for data analysts10 minutes
Asking the right questions: A guide to data exploration10 minutes
Generative AI for data exploration: New possibilities10 minutes
Case study: Data exploration with generative AI10 minutes
Assessing the validity of generative AI insights: A framework for data analysts10 minutes
Challenges and limitations of generative AI in data exploration10 minutes

6 assignmentsTotal 105 minutes

Activity: Data detective: Uncover the clues15 minutes
Data exploration with generative AI30 minutes
Key terms and questions in data exploration15 minutes
Leveraging Generative AI for data exploration15 minutes
Activity: Data detective: The first look15 minutes
Analyzing a dataset with GenAI15 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 videosTotal 35 minutes

GenAI's role in uncovering inconsistencies6 minutes
Demo: Automatic inconsistency flagging6 minutes
Visualizing data inconsistency: A guided tour2 minutes
Decoding GenAI reports: Understanding the impact of data inconsistencies6 minutes
From report to action: Making informed decisions with GenAI insights6 minutes
The outlier effect: How GenAI helps spot and address anomalies3 minutes
Data transformation fundamentals: Why it matters for accurate analysis6 minutes

8 readingsTotal 80 minutes

The data cleaning dilemma: How GenAI offers solutions10 minutes
Beyond the basics: Advanced data cleaning techniques with GenAI10 minutes
Data quality is key: Using GenAI to prioritize cleaning efforts10 minutes
The ethics of automated data cleaning: Balancing efficiency and responsibility10 minutes
The art and science of missing data: GenAI as your assistant10 minutes
Beyond removal: When outliers are insights, not errors10 minutes
The data transformation toolkit10 minutes
Feature engineering in the age of GenAI: A balanced approach10 minutes

6 assignmentsTotal 90 minutes

Project: Unveiling Data Inconsistencies with GenAI15 minutes
Project: Addressing data inconsistencies by cleaning your dataset with GenAI 15 minutes
Data Cleaning with GenAI15 minutes
Identifying and categorizing data inconsistencies15 minutes
Evaluating impact and making decisions15 minutes
Imputing missing values and handling outliers15 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 videosTotal 28 minutes

The prompt makeover: From vague to valuable3 minutes
Improving your prompts: Strategies for refinement5 minutes
Sculpting your prompts: The art of iterative refinement3 minutes
Learning paradigms in GenAI: Using examples effectively5 minutes
Zero-shot, one-shot and few shot learning7 minutes
Effective prompting: Using the RACE and PARE frameworks5 minutes

9 readingsTotal 90 minutes

The art of prompting: A guide for data analysts10 minutes
Prompt gallery: Real-world examples for inspiration10 minutes
Iterative prompt refinement: A data analyst's secret weapon10 minutes
Prompt engineering cheat sheet: Quick tips for data analysts10 minutes
Zero-shot, one-shot, and few-shot learning with generative AI10 minutes
Practical applications of learning paradigms in data analysis10 minutes
Discussion: Choosing the right learning paradigm10 minutes
Prompting with purpose: The RACE framework for data analysis10 minutes
Using the PARE framework to ensure quality insights10 minutes

7 assignmentsTotal 115 minutes

Activity: Prompt refinement15 minutes
Project: Evaluating with PARE10 minutes
Prompt engineering fundamentals30 minutes
Crafting effective prompts15 minutes
Optimization techniques15 minutes
Zero-shot, one-shot, and few-shot learning15 minutes
Applying the RACE framework15 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 videosTotal 36 minutes

Addressing ethical issues in generative AI: Bias, privacy, and misuse6 minutes
Garbage in, garbage out: How bias persists in GenAI3 minutes
AI as a double-edged sword: Power, responsibility, and consequences3 minutes
The role of an AI ethicist: Balancing innovation and responsibility6 minutes
Ethical challenges: Addressing issues in generative AI6 minutes
Built-in safeguards: Comparing GenAI tools for ethical use6 minutes
Why your organization needs custom ethical AI guidelines6 minutes

7 readingsTotal 70 minutes

The ethical landscape of generative AI: A data analyst's perspective10 minutes
Ethical dilemmas in action: Case studies from the data analysis field10 minutes
Beyond compliance: Why responsible AI is a competitive advantage10 minutes
Building an ethical AI framework: A guide for data teams10 minutes
Before you deploy: Evaluating GenAI use cases for ethical risks10 minutes
Implementing ethical GenAI: Best practices for data teams10 minutes
The future of ethical AI: Challenges and opportunities for data analysts10 minutes

6 assignmentsTotal 115 minutes

Activity: Bias in generative AI10 minutes
Project: Ensuring ethical use for a Data Analysis scenario30 minutes
Ethical and Safe Use of GenAI Assessment30 minutes
Identifying ethical concerns15 minutes
The importance of responsible AI15 minutes
Evaluating GenAI use in scenarios15 minutes

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Instructor

Instructor ratings

(27 ratings)

Microsoft

356 Courses2,670,582 learners

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Microsoft

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Reviewed on Dec 28, 2024

This is very good course for anyone planning to use Gen AI for data analysis tasks.

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 Mar 9, 2025

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

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