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⇱ GenAI for Data Analysts | Coursera

GenAI for Data Analysts

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Gain insight into a topic and learn the fundamentals.
4.7

25 reviews

Intermediate level

Recommended experience

2 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.7

25 reviews

Intermediate level

Recommended experience

2 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Identify the advanced capabilities of GenAI for enhancing various data analysis tasks, including unique functionalities and innovative use cases.

  • Examine and apply real-world applications of GenAI in data analysis, highlighting unique success stories and innovative practices.

  • Reflect on how GenAI can significantly improve productivity & foster innovation in data analysis, with insights into future trends & industry shifts.

Details to know

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Assessments

2 assignments¹

AI Graded see disclaimer
Taught in English

Build your subject-matter expertise

This course is part of the Modern Data Analytics with Python, Excel & Generative AI 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 is 1 module in this course

"GenAI for Data Analysts" explores the revolutionary impact of Generative AI on data analysis. This course offers a comprehensive introduction to GenAI's capabilities and practical strategies for integrating these powerful tools into everyday data analysis tasks. Through discussions, video demos, and guided hands-on activities, you will learn how GenAI can enhance productivity in data preprocessing, pattern recognition, predictive analytics, and report generation.

This course is designed for individual data analysts seeking to enhance their workflows with GenAI, team leads guiding their teams toward innovative practices, and aspiring data analysts aiming to future-proof their skills. It is also ideal for those looking to advance their careers by mastering GenAI applications in data science. Learners should have a basic understanding of data preprocessing, pattern recognition, and predictive analytics. Familiarity with common data storage and analysis tools (e.g., databases, data visualization software) and experience with programming languages (e.g., Python, R, SQL) are also required. An open mindset and eagerness to explore new technologies are essential. By the end of the course, you will be equipped to leverage GenAI for more efficient and innovative data analysis.

'GenAI for Data Analysts' explores the revolutionary impact of Generative Artificial Intelligence on data analysis. This course offers a comprehensive introduction to the capabilities of GenAI and provides practical strategies for integrating these powerful tools into everyday data analysis tasks. Through a combination of discussions, video demos, and guided hands-on activities, learners will gain an understanding of how GenAI can significantly enhance productivity in data preprocessing, pattern recognition, predictive analytics, and report generation.

What's included

6 videos5 readings2 assignments

6 videos•Total 41 minutes
  • Introduction to GenAI for Data Analysts•7 minutes
  • History & Background For GenAI and Data Analysts•9 minutes
  • Demo for Data Processing and Pattern Recognition with ChatGPT•6 minutes
  • Remediating Risks and Ethical Concerns•13 minutes
  • Demo for Data Analysis and Insight Generation with ChatGPT•5 minutes
  • Closing Thoughts: What’s Next•2 minutes
5 readings•Total 50 minutes
  • Our Roadmap & Resources Available: How to Get Started•10 minutes
  • Glossary for GenAI and Data Analyst•10 minutes
  • Demo for Dataset Report Generation with ChatGPT•10 minutes
  • Demo for Predictive Insight Generation and Advanced Analytics with Coefficient•10 minutes
  • Demo for Advanced Data Interaction with Crux Copilot and Copilot•10 minutes
2 assignments•Total 50 minutes
  • Your Turn! Practice Assignments •30 minutes
  • GenAI for Data Analyst•20 minutes

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Instructors

Instructor ratings
3.8 (6 ratings)

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LT
·

Reviewed on Dec 13, 2025

Khóa học rất hay, hướng dẫn cho người học cách suy nghĩ và hành động của GenAI, hỗ trợ công việc một cách hiệu quả

Frequently asked questions

In this course, GenAI-assisted data analysis means using generative AI to support core analysis work rather than treating AI as a separate add-on. The focus is on how GenAI helps with data preparation, pattern recognition, predictive analytics, and report generation.

You would use it when an analysis involves several linked tasks and you want AI to support more than one step. The course shows this approach being used to prepare data, explore patterns, generate predictive insight, and summarize findings.

It fits into the earlier and middle stages of analysis, where you are preparing data, exploring signals, and deciding what to investigate next. In this course, GenAI also carries into later stages by helping turn analysis results into usable reports.

Traditional analysis usually relies more on the analyst to carry out each step directly, while GenAI-assisted analysis adds AI support across those steps. In this course, the goal is not to replace data analysis methods but to show how GenAI can help with recurring tasks while keeping human judgment and ethics in view.

A basic understanding of data preprocessing, pattern recognition, and predictive analytics is expected. It also helps to be comfortable with common analysis tools and at least one language such as Python, R, or SQL.

The course mainly uses conversational generative AI tools, especially ChatGPT, alongside familiar data analysis tools. The main methods are prompting and iteration to support preprocessing, pattern recognition, predictive analytics, and report generation.

You will practice using GenAI to prepare data, explore patterns, generate predictive insights, and draft analysis reports. You will also evaluate outputs for ethical use so those tasks fit into a responsible analysis workflow.

Financial aid available,

¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.