Learn by Source
IBM · on edX

IBM: Mastering Generative AI for Data Analytics

Intermediate 16.5 hours English Course CertificateFREE
SkillsGenerative AIData analyticsVisualisationDashboardsData storytellingAI tools

Is this course right for you?

Our take
IBM's edX course on applying generative AI across the data-analytics workflow specifically — from preparation right through to the story you tell with the results.

Good for: Using generative AI across the data-analytics workflow.

Skip if: You are new to analytics or want general GenAI concepts.

What distinguishes it from its data-science sibling is the emphasis on the last mile: analysis, visualisation, dashboards and storytelling, using tools including ChatGPT and others. That's the analyst's real job — not just finding the insight but communicating it persuasively — and genAI genuinely helps with the drafting and the visuals. It's about working faster, not learning analytics from scratch.

It assumes you already work in analytics, and it's a poor fit if analytics is new to you, or you want generative-AI concepts in the abstract. Audit it free on edX (verified certificate a paid option, financial assistance available); some third-party tools shown may carry their own subscriptions or usage costs. The specific tools change fast, so expect some to have moved on (as of 2026).

Comparison · LBS

Compare alternatives for IBM: Mastering Generative AI for Data Analytics

Same topic, different options. We surface the trade-offs others hide so you can pick the course that actually fits your time, budget, and goals.
edX
IBM: Mastering Generative AI for Data Analytics
Price
Free
Audit free · paid verified certificate
Duration
16.5 hrs
Level
Intermediate
Certificate
Course Certificate
freeCodeCamp4.7(5,400)
Data Analysis with Python Certification
Price
Free
Completely free, forever
Duration
300 hrs
Level
Intermediate
Certificate
Course Certificate
View course →
LinkedIn Learning
Excel with Copilot: AI-Driven Data Analysis
Price
Paid
LinkedIn Learning subscription
Duration
1.6 hrs
Level
Intermediate
Certificate
Course Certificate
View course →
Udemy4.6(10,000)
Tableau 2026: Advanced Training for Analysts
Price
Paid
Paid, frequently discounted
Duration
8 hrs
Level
Intermediate
Certificate
Course Certificate
View course →
Prices & availability can change — confirm on the provider's site. We're not affiliated with any single provider.

About this course

This course covers applying generative AI throughout the data analytics workflow: data preparation, analysis, visualization, dashboard creation, and storytelling, using tools including ChatGPT, ChatCSV, Mostly.AI, and SQLthroughAI. It includes hands-on labs throughout and a guided practice project. It also weighs where an AI-generated result needs a human check before it reaches a stakeholder, so speed does not come at the cost of trust.

Browse all AI & ML courses Browse all edX courses

Instructor

RA
Rav Ahuja
edX instructor

Rav Ahuja is IBM's Global Program Director for the IBM Skills Network, leading curriculum strategy for AI, data science, and cloud courses on edX.

Frequently asked questions

Data analysts and business-analytics professionals who want to use generative AI to work faster and smarter — applying AI tools to data preparation, analysis, and reporting. It assumes an analytics context, so it suits practising or aspiring analysts rather than complete beginners. If you work with data in a business setting and want to fold generative AI into that work, it is aimed at you.

Applying generative AI to data analytics: using large language models and AI assistants to help clean and explore data, generate queries or code, interpret results, and communicate findings, plus the sensible and responsible use of these tools in an analytics workflow. It is about augmenting the analyst's toolkit with generative AI rather than teaching analytics or AI from the ground up.

Possibly. If the course uses commercial AI tools or large-language-model APIs, those may carry usage costs beyond any course subscription, though many tasks fit within free tiers. Budget a little for tool or API access if you want to complete every hands-on part fully, and check the course's specific requirements before assuming everything is free.

Check the recent-update date, as generative AI evolves rapidly. The core idea — using AI to accelerate analytics work — stays relevant, but the specific tools and their features change within months. Treat it as a current snapshot of applying generative AI to analytics, and keep learning from up-to-date sources, since this fast-moving area outpaces what any single course can capture.

You can audit it on Coursera to watch the material at no cost, with graded elements and the certificate behind a subscription. Since much of the value is in applying the generative-AI techniques yourself, the paid track (and possibly tool access) is worth considering if you want hands-on practice rather than only watching the lectures.
Free
to audit
Enroll now