Do I need prior experience for this GenAI for Data Analytics course?

A basic understanding of data analytics, Python, and structured business problem-solving is recommended. This course builds practical AI for Data Analytics skills through hands-on exercises and real-world business scenarios.

How does GenAI improve data analytics?

GenAI for Data Analytics enhances every stage of the analytics lifecycle by accelerating data preparation, analysis, visualization, reporting, and insight generation while supporting more efficient, data-driven decision-making.

Who should take this GenAI for Data Analytics course?

This course is designed for data analysts, business analysts, BI professionals, data scientists, and decision-makers who want to apply AI for Data Analytics to solve business problems and deliver greater value through data.

What will I learn in this GenAI for Data Analytics course?

You'll learn how to apply Generative AI for Data Analytics, prompt engineering, Python, and AI-powered analytics tools to analyze data, create compelling visualizations, and communicate actionable business insights.

How will this course support my career?

By developing practical skills in AI for Data Analytics, you'll be better prepared for roles such as Data Analyst, Business Analyst, BI Analyst, Analytics Consultant, and other AI-enabled analytics positions.

Will I receive a certificate after completing the course?

Yes. Upon successfully completing the course and its assessments, you'll earn a Coursera certificate that demonstrates your knowledge of Generative AI for Data Analytics.

What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

GenAI for Data & Analytics

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kurs ist nicht verfügbar in Deutsch (Deutschland)

Wir übersetzen es in weitere Sprachen.

GenAI for Data & Analytics

Dozenten: Mark Peco

Bei Mehr erfahren enthalten

4 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

9 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

4 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

9 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

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.

Kompetenzen, die Sie erwerben

Kategorie: Data Storytelling
Kategorie: Cross-Functional Collaboration
Kategorie: Large Language Modeling
Kategorie: Data Management
Kategorie: Data Visualization
Kategorie: Exploratory Data Analysis
Kategorie: Report Writing
Kategorie: Business Analytics
Kategorie: Business Analysis
Kategorie: Data Analysis
Kategorie: Analytics
Kategorie: AI literacy
Kategorie: Business Reporting
Kategorie: Data Presentation

Werkzeuge, die Sie lernen werden

Kategorie: Generative AI
Kategorie: Prompt Engineering
Kategorie: ChatGPT

Wichtige Details

Zertifikat zur Vorlage

Zu Ihrem LinkedIn-Profil hinzufügen

Kürzlich aktualisiert!

Juli 2026

Bewertungen

4 Aufgaben

Unterrichtet in Englisch

Erfahren Sie, wie Mitarbeiter führender Unternehmen gefragte Kompetenzen erwerben.

Weitere Informationen zu Coursera für Unternehmen

Logos von Petrobras, TATA, Danone, Capgemini, P&G und L'Oreal

In diesem Kurs gibt es 4 Module

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.

Through practical demonstrations, hands-on exercises, and real-world business scenarios, you will learn how to use AI for data analytics by applying prompt engineering, AI-assisted data analysis, Python for data analytics, and data storytelling to solve complex business problems and communicate insights effectively. You'll discover how using Generative AI for data analytics strengthens collaboration between technical and business teams, streamlines decision-making, and enables more efficient, data-driven strategies. By the end of the course, you'll be equipped to confidently use AI-powered analytics tools to transform data into meaningful insights, support business decisions, and create lasting organizational value.

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.

Das ist alles enthalten

11 Videos2 Lektüren1 Aufgabe1 peer review2 Diskussionsthemen

11 VideosInsgesamt 74 Minuten

Intro Video to Course 3 Minuten
Module Introduction 4 Minuten
Introduction to GenAI for Analytics7 Minuten
Understanding Analytics Workflows 7 Minuten
Demo: Introducing the Software Tools Used in the Course7 Minuten
Why Prompt Design Matters 7 Minuten
Demo: ChatGPT for Problem Framing 8 Minuten
Demo: Gemini for Code Generation8 Minuten
LLM Modes: Exploration, Validation, Execution, Communication 7 Minuten
Demo: Setting Up Gemini in Colab and Excel11 Minuten
Module Wrap-Up: LLMs as Analyst Thinking Partners 5 Minuten

2 LektürenInsgesamt 10 Minuten

Welcome to the Course: Course Overview5 Minuten
A Primer on Generative Artificial Intelligence5 Minuten

1 AufgabeInsgesamt 20 Minuten

Foundations of GenAI in Data Analytics 20 Minuten

1 peer reviewInsgesamt 10 Minuten

Hands-On-Learning: From Business Problem → Prompt → First SQL + Python Insights10 Minuten

2 DiskussionsthemenInsgesamt 20 Minuten

Clarify the Problem Before You Touch the Data10 Minuten
The Hidden Risk of Skipping Validation 10 Minuten

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.

Das ist alles enthalten

10 Videos1 Lektüre1 Aufgabe1 peer review2 Diskussionsthemen

10 VideosInsgesamt 65 Minuten

Module Introduction3 Minuten
How LLMs Support Business and Data Understanding 7 Minuten
Demo: ChatGPT for Exploring Data Based on Domain Knowledge6 Minuten
Demo: Gemini for Structuring Analytics Opportunities Based on EDA Results Combined with Domain Knowledge 9 Minuten
Linking Business Goals to Data and Models 6 Minuten
Demo: ChatGPT for Prompt Iteration 5 Minuten
Demo: Gemini for Generating SQL queries and Python Code to Discover and Visualize Patterns in the Data 8 Minuten
Profiling and Exploring Data with AI 7 Minuten
Demo: Gemini in Colab for Data Summaries 7 Minuten
Demo: Gemini in Colab for Communicating Narraitives 8 Minuten

1 LektüreInsgesamt 5 Minuten

Realising the Promises of Artificial Intelligence in Manufacturing by Enhancing CRISP-DM 5 Minuten

1 AufgabeInsgesamt 20 Minuten

Automated Data Analysis and Insight Generation 20 Minuten

1 peer reviewInsgesamt 10 Minuten

Hands-On-Learning: Staff Utilization vs Margin Analysis10 Minuten

2 DiskussionsthemenInsgesamt 20 Minuten

From a Vague Ask to a Structured Analytics Task 10 Minuten
The Risk of Trusting Profiling Without Validation 10 Minuten

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.

Das ist alles enthalten

10 Videos1 Lektüre1 Aufgabe1 peer review2 Diskussionsthemen

10 VideosInsgesamt 66 Minuten

Module Introduction 2 Minuten
Principles of Modeling in Analytics Workflows 6 Minuten
Demo: Gemini in Colab for Predictive Modeling 8 Minuten
Demo: ChatGPT for Model Interpretation 8 Minuten
Accuracy, Explainability, and Trust in GenAI Outputs 6 Minuten
Demo: Gemini for Model Validation 8 Minuten
Demo: ChatGPT for Critiquing Outputs6 Minuten
From Models to Insights: The Analyst’s Role 5 Minuten
Demo: Google Colab for Automated Reports5 Minuten
Demo: ChatGPT and Google Colab for Stakeholder Communication 13 Minuten

1 LektüreInsgesamt 5 Minuten

Generative AI and the Future of Storytelling 5 Minuten

1 AufgabeInsgesamt 20 Minuten

Data Visualization and Communication with GenAI 20 Minuten

1 peer reviewInsgesamt 10 Minuten

Hands-On-Learning: Build a Baseline Model, Validate the Story, and Produce a Mini Insight Report 10 Minuten

2 DiskussionsthemenInsgesamt 20 Minuten

What Makes an Insight Actionable? 10 Minuten
Using an LLM to Test Report Clarity for Non-Technical Stakeholders 10 Minuten

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.

Das ist alles enthalten

11 Videos1 Lektüre1 Aufgabe2 peer reviews2 Diskussionsthemen

11 VideosInsgesamt 63 Minuten

Module Introduction 2 Minuten
Real-World Applications of GenAI in Analytics 5 Minuten
Demo: Gemini Industry Case Simulation 9 Minuten
Demo: ChatGPT as an Analyst Advisor 11 Minuten
GenAI Governance Across CRISP-DM 5 Minuten
Demo: Gemini For Audit and Conrols 5 Minuten
Demo: ChatGPT for Auditing Prompts & Outputs 5 Minuten
Embedding GenAI Across CRISP-DM 5 Minuten
Demo: End-to-End Workflow (Gemini)6 Minuten
Module Wrap-Up: Best Practices for Scaling and Future Readiness 6 Minuten
Course Wrap-Up2 Minuten

1 LektüreInsgesamt 5 Minuten

Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile5 Minuten

1 AufgabeInsgesamt 20 Minuten

Real-World Applications and Advanced Techniques 20 Minuten

2 peer reviewsInsgesamt 40 Minuten

Hands-On-Learning: Apply GenAI Tools End-to-End: Execute, Govern, and Critique 10 Minuten
Project: Driving Successful Data Analytics with Generative AI30 Minuten

2 DiskussionsthemenInsgesamt 20 Minuten

Governance in Practice: Applying Controls When Using LLMs for Analytics 10 Minuten
Balancing Automation and Human Oversight in GenAI-Enabled Workflows 10 Minuten

Dozenten

Mark Peco

STARWEAVER

2 Kurse299 Lernende

von

STARWEAVER

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Häufig gestellte Fragen

AI for Data Analytics applies artificial intelligence and machine learning to enhance the entire analytics lifecycle, from data preparation and analysis to visualization and insight generation. By automating repetitive tasks, identifying patterns, and accelerating analysis, it enables organizations to make faster, more accurate, and data-driven business decisions.

A GenAI for Data Analytics course teaches you how to apply Generative AI, large language models (LLMs), and leading AI tools for data analytics to solve real-world business problems. You'll learn to automate analytics workflows, generate visualizations, communicate insights effectively, and integrate AI into modern data analytics practices.

You'll gain hands-on experience with leading AI tools for data analytics, including ChatGPT and Google Gemini, and learn how to use them to automate analytics workflows, accelerate data analysis, and generate actionable business insights.

To access course materials, assignments, and earn a Certificate, you'll need to purchase the Certificate experience when you enroll in a course. Eligible learners may also have the option to start with a Free Trial. Some courses may also offer a Full Course, No Certificate option. This lets you access course materials, submit required assessments, and receive a final grade, but you won't be able to earn or purchase a Certificate.