Generative AI: Enhance your Data Analytics Career (Coursera)

Offered by IBM,
Generative AI: Enhance your Data Analytics Career (Coursera)

This comprehensive course unravels the potential of generative AI in data analytics. The course will provide an in-depth knowledge of the fundamental concepts, models, tools, and generative AI applications regarding the data analytics landscape.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

In this course, you will examine real-world applications and use generative AI to gain data insights using techniques such as prompts, visualization, storytelling, querying and so on. In addition, you will understand the ethical implications, considerations, and challenges of using generative AI in data analytics across different industries.
You will acquire practical experience through hands-on labs where you will leverage generative AI models and tools such as ChatGPT, ChatCSV, Mostly.AI, SQLthroughAI and more.
Finally, you will apply the concepts learned throughout the course to a data analytics project. Also, you will have an opportunity to test your knowledge with practice and graded quizzes and earn a certificate.
This course is suitable for both practicing data analysts as well as learners aspiring to start a career in data analytics. It requires some basic knowledge of data analytics, prompt engineering, Python programming and generative artificial intelligence.
This course is part of the IBM Generative AI for Cybersecurity Professionals Specialization.

What you'll learn

  • Describe how you can use Generative AI tools and techniques in the context of data analytics across industries
  • Implement various data analytic processes such as data preparation, analysis, visualization and storytelling using Generative AI tools
  • Evaluate real-world case studies showcasing the successful application of Generative AI in deriving meaningful insights
  • Analyze the ethical considerations and challenges associated with using Generative AI in data analytics

Syllabus

Data Analytics and Generative AI
This module introduces Generative AI for Data Analytics. You will explore several generative AI tools used in data analytics and gain insights into implementing them successfully. The module covers using generative AI for tasks like data generation and augmentation, data preparation, querying databases, and obtaining insights from Q&A models.

Use of Generative AI for Data Analytics
In this module, you will have the skills and knowledge to effectively use Generative AI to derive insights, create visually compelling data representations, and construct interactive dashboards for data analytics pipelines. You will also understand the importance of ethical practices in utilizing generative models for data analytics.

Final Project and Exam
In this module, you will complete a guided practice project where you will use a real-world data set and practice generative AI to generate Python codes that can perform data preparation, analysis, visualization and dashboarding. In addition, you will attempt a final graded exam designed to evaluate your understanding of generative AI.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Generative AI Essentials: Overview and Impact (Coursera) Coursera
University of Michigan

Generative AI Essentials: Overview and Impact (Coursera)

With the rise of generative artificial intelligence, there has been a growing demand to explore how to use these powerful tools not only in our work but also in our day-to-day lives. Generative AI Essentials: Overview and Impact introduces learners to large language models and generative AI tools, like ChatGPT. In this course, you’ll explore generative AI essentials, how to ethically use artificial intelligence, its implications for authorship, and what regulations for generative AI could look like.

Jun 12th 2026
1 Week
Applying Data Analytics in Finance (Coursera) Coursera
University of Illinois at Urbana-Champaign

Applying Data Analytics in Finance (Coursera)

This course introduces an overview of financial analytics. You will learn why, when, and how to apply financial analytics in real-world situations. You will explore techniques to analyze time series data and how to evaluate the risk-reward trade off expounded in modern portfolio theory. While most of the focus will be on the prices, returns, and risk of corporate stocks, the analytical techniques can be leverages in other domains. Finally, a short introduction to algorithmic trading concludes the course.

Jun 14th 2026
4 Weeks
Introduction to Spreadsheets and Models (Coursera) Coursera
University of Pennsylvania

Introduction to Spreadsheets and Models (Coursera)

The simple spreadsheet is one of the most powerful data analysis tools that exists, and it’s available to almost anyone. Major corporations and small businesses alike use spreadsheet models to determine where key measures of their success are now, and where they are likely to be in the future. But in order to get the most out of a spreadsheet, you have know how to use it. This course is designed to give you an introduction to basic spreadsheet tools and formulas so that you can begin harness the power of spreadsheets to map the data you have now and to predict the data you may have in the future.

Jun 8th 2026
4 Weeks
Infonomics II: Business Information Management and Measurement (Coursera) Coursera
University of Illinois at Urbana-Champaign

Infonomics II: Business Information Management and Measurement (Coursera)

Even decades into the Information Age, accounting practices yet fail to recognize the financial value of information. Moreover, traditional asset management practices fail to recognize information as an asset to be managed with earnest discipline. This has led to a business culture of complacence, and the inability for most organizations to fully leverage available information assets. This second course in the two-part Infonomics series explores how and why to adapt well-honed asset management principles and practices to information, and how to apply accepted and new valuation models to gauge information’s potential and realized economic benefits.

Jun 10th 2026
4 Weeks
Understanding China, 1700-2000: A Data Analytic Approach, Part 1 (Coursera) Coursera
The Hong Kong University of Science and Technology - HKUST

Understanding China, 1700-2000: A Data Analytic Approach, Part 1 (Coursera)

The purpose of this course is to summarize new directions in Chinese history and social science produced by the creation and analysis of big historical datasets based on newly opened Chinese archival holdings, and to organize this knowledge in a framework that encourages learning about China in comparative perspective. Our course demonstrates how a new scholarship of discovery is redefining what is singular about modern China and modern Chinese history.

Jun 8th 2026
5-12 Weeks
Introduction to Probability and Data with R (Coursera) Coursera
Duke University

Introduction to Probability and Data with R (Coursera)

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization.

Jun 8th 2026
5-12 Weeks
Leadership Through Marketing (Coursera) Coursera
Northwestern University

Leadership Through Marketing (Coursera)

The success of every organization depends on attracting and retaining customers. Although the marketing concepts for doing so are well established, digital technology has empowered customers, while producing massive amounts of data, revolutionizing the processes through which organizations attract and retain customers. In this course, students will learn how to identify new opportunities to create value for empowered consumers, develop strategies that yield an advantage over rivals, and develop the data science skills to lead more effectively, allocate resources, and to confront this very challenging environment with confidence.

Jun 14th 2026
4 Weeks
Market Research and Consumer Behavior (Coursera) Coursera
IE Business School

Market Research and Consumer Behavior (Coursera)

Your marketing quest begins here! The first course in this specialization lays the neccessary groundwork for an overall successful marketing strategy. It is separated into two sections: Market Research and Consumer Behavior. Gain the tools and techniques to translate a decision problem into a research question in the Market Research module. Learn how to design a research plan, analyze the data gathered and accurately interpret and communicate survey reports, translating the results into practical recommendations.

Jun 8th 2026
4 Weeks
Inferential Statistics (Coursera) Coursera
University of Amsterdam

Inferential Statistics (Coursera)

Inferential statistics are concerned with making inferences based on relations found in the sample, to relations in the population. Inferential statistics help us decide, for example, whether the differences between groups that we see in our data are strong enough to provide support for our hypothesis that group differences exist in general, in the entire population. We will start by considering the basic principles of significance testing: the sampling and test statistic distribution, p-value, significance level, power and type I and type II errors. Then we will consider a large number of statistical tests and techniques that help us make inferences for different types of data and different types of research designs.

Jun 8th 2026
5-12 Weeks
Fundamentals of GIS (Coursera) Coursera
University of California, Davis

Fundamentals of GIS (Coursera)

Explore the world of spatial analysis and cartography with geographic information systems (GIS). What you will learn: define core geospatial concepts; practice with subset data using selections and feature attributes; create map books using advanced mapping techniques; create layer and map packages.

Jun 8th 2026
4 Weeks
Introducción a Data Science: Programación Estadística con R (Coursera) Coursera
Universidad Nacional Autónoma de México

Introducción a Data Science: Programación Estadística con R (Coursera)

Este curso te proporcionará las bases del lenguaje de programación estadística R, la lengua franca de la estadística, el cual te permitirá escribir programas que lean, manipulen y analicen datos cuantitativos. Te explicaremos la instalación del lenguaje; también verás una introducción a los sistemas base de gráficos y al paquete para graficar ggplot2, para visualizar estos datos. Además también abordarás la utilización de uno de los IDEs más populares entre la comunidad de usuarios de R, llamado RStudio.

Jun 8th 2026
4 Weeks