Starweaver

GenAI for Data & Analytics

Starweaver

GenAI for Data & Analytics

Mark Peco
Starweaver

Instructors: Mark Peco

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

9 hours to complete
Flexible schedule
Learn at your own pace
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 to frame business problems for data analytics by tools likeChatGPT, Gemini in Colab, for solution.

  • Create and communicate actionable insights through reports, narratives, and visualizations that drive business decisions.

  • Evaluate data, models, and GenAI outputs for accuracy and clarity across CRISP-DM and the Analytics Value Chain.

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Recently updated!

July 2026

Assessments

4 assignments

Taught in English

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There are 4 modules in this course

This module introduces and describes AI compared with GenAI. It explains how LLMs support analysts across the CRISP-DM framework, how prompt engineering helps clarify problems, guide analysis and generate code to carry out the analysis and publish results. Learners will explore tools (ChatGPT, Gemini in Colab) and see how to use them as thinking partners, code generators and workflow accelerators.

What's included

11 videos2 readings1 assignment1 peer review2 discussion prompts

This module focuses on the early phases of CRISP-DM. Learners will see how LLMs (ChatGPT, Gemini) act as partners in clarifying business needs, reframing problems into analytics tasks, and exploring data to uncover opportunities.

What's included

10 videos1 reading1 assignment1 peer review2 discussion prompts

This module focuses on the modeling, evaluation, and insight-generation phases of CRISP-DM. Learners will use LLMs not only to generate models and outputs but also to interpret, refine, and communicate insights through narratives, reports, and visualizations.

What's included

10 videos1 reading1 assignment1 peer review2 discussion prompts

This module focuses on the later phases of CRISP-DM framework. Learners will explore real-world applications of GenAI, practice evaluating outputs for trust and governance, and learn how to integrate LLMs into analytics workflows responsibly and effectively.

What's included

11 videos1 reading1 assignment2 peer reviews2 discussion prompts

Instructors

Mark Peco
Starweaver
1 Course187 learners

Offered by

Starweaver

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