Generative AI is transforming modern data analytics, enabling organizations to move beyond traditional reporting toward faster, more accurate, and actionable business insights. This hands-on course, GenAI for Data & Analytics explores how leading AI tools for data analytics, including ChatGPT, Google Gemini, Python, and Google Colab, can be integrated into the CRISP-DM framework to enhance every stage of the analytics lifecycle - from business understanding and data preparation to predictive modeling, visualization, and stakeholder communication. Designed for data analysts, business analysts, BI developers, data scientists, and decision-makers, this AI for Data Analytics course demonstrates how large language models (LLMs) accelerate analytics workflows, improve productivity, and support responsible AI adoption while delivering measurable business outcomes.

GenAI for Data & Analytics

Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
9 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Differentiate the building blocks of AI, GenAI, and Data Analytics, and describe how LLMs support the CRISP-DM and Value Chain frameworks.
Apply prompt engineering techniques with ChatGPT, Gemini, and Google Colab to solve business problems using AI for Data Analytics.
Create actionable insights through AI-assisted data analysis, visualizations, and storytelling to support business decisions.
Evaluate data, models, and GenAI outputs for accuracy, clarity, and business value across AI-powered data analytics workflows.
Skills you'll gain
Tools you'll learn
Details to know

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Assessments
4 assignments
Taught in English
Recently updated!
July 2026
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There are 4 modules in this course
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