• views: 114
• date: 2 July 2026
• posted by: voska89

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 to frame business problems for data analytics by using tools like ChatGPT, Gemini in Colab, for solutions.
Create and Communicate actionable insights to generate narratives, reports, and visualizations for analytical findings and their business impact to stakeholders
Evaluate data, models, and GenAI outputs for accuracy and clarity, to critique, validate, and refine insights across CRISP-DM Phases and Value Chains.

Requirements

Basic understanding of data analytics concepts, such as datasets, charts, reports, and data visualization. Familiarity with Microsoft Excel and an interest in solving business problems using data. Prior Python experience is helpful but not required. Access to a computer with an internet connection and free accounts for ChatGPT and Google Colab (Gemini-enabled) to complete the hands-on exercises.

Description

Data analytics is no longer just about creating reports and dashboards. Modern organizations expect professionals to uncover meaningful insights, predict trends, and communicate findings that drive better business decisions. This course, Gen AI for Data & Analytics Professionals, teaches you how to use Generative AI to transform traditional analytics workflows into faster, smarter, and more impactful processes.
Designed for business analysts, data analysts, BI developers, data scientists, and decision-makers, this hands-on course explores how AI-powered tools can support every stage of the analytics lifecycle. You will learn how to frame business problems, explore and prepare data, generate code, build analytical models, validate results, and present actionable insights using ChatGPT, Google Gemini, Python, and Microsoft Excel. Rather than replacing analytical thinking, these tools act as intelligent assistants that improve productivity, reduce repetitive work, and enable more strategic decision-making.
The course introduces industry-recognized analytics frameworks, including CRISP-DM and the Analytics Value Chain, to demonstrate how Generative AI enhances structured problem-solving and creates measurable business value. Through practical demonstrations, guided activities, and real-world business scenarios, you will gain experience using AI to automate routine tasks, improve collaboration, and communicate insights effectively to both technical and non-technical stakeholders.
By the end of the course, you will be able to integrate Generative AI into your analytics workflows, create meaningful data-driven insights, evaluate AI-generated outputs for quality and accuracy, and apply responsible AI practices. Whether you are looking to increase productivity, strengthen your analytical capabilities, or stay ahead in the rapidly evolving world of AI-powered analytics, this course provides practical, job-ready skills that you can apply immediately.

Who this course is for

Designed for data analysts, business professionals, BI developers, data scientists, and decision-makers who want to apply Generative AI to improve analytics and business outcomes.




   
   
   

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