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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Ce cours n'est pas disponible en Français (France)

Nous sommes actuellement en train de le traduire dans plus de langues.

GenAI for Data & Analytics

Instructeurs : Mark Peco

Inclus avec En savoir plus

4 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Intermédiaire

Expérience recommandée

9 heures à compléter

Planning flexible

Apprenez à votre propre rythme

4 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Intermédiaire

Expérience recommandée

9 heures à compléter

Planning flexible

Apprenez à votre propre rythme

Ce que vous apprendrez

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.

Compétences que vous acquerrez

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

Outils que vous découvrirez

Catégorie : Generative AI
Catégorie : Prompt Engineering
Catégorie : ChatGPT

Détails à connaître

Certificat partageable

Ajouter à votre profil LinkedIn

Récemment mis à jour !

juillet 2026

Évaluations

4 devoirs

Enseigné en Anglais

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logos de Petrobras, TATA, Danone, Capgemini, P&G et L'Oreal

Il y a 4 modules dans ce cours

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.

Inclus

11 vidéos2 lectures1 devoir1 évaluation par les pairs2 sujets de discussion

11 vidéosTotal 74 minutes

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

2 lecturesTotal 10 minutes

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

1 devoirTotal 20 minutes

Foundations of GenAI in Data Analytics 20 minutes

1 évaluation par les pairsTotal 10 minutes

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

2 sujets de discussionTotal 20 minutes

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

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.

Inclus

10 vidéos1 lecture1 devoir1 évaluation par les pairs2 sujets de discussion

10 vidéosTotal 65 minutes

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

1 lectureTotal 5 minutes

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

1 devoirTotal 20 minutes

Automated Data Analysis and Insight Generation 20 minutes

1 évaluation par les pairsTotal 10 minutes

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

2 sujets de discussionTotal 20 minutes

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

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.

Inclus

10 vidéos1 lecture1 devoir1 évaluation par les pairs2 sujets de discussion

10 vidéosTotal 66 minutes

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

1 lectureTotal 5 minutes

Generative AI and the Future of Storytelling 5 minutes

1 devoirTotal 20 minutes

Data Visualization and Communication with GenAI 20 minutes

1 évaluation par les pairsTotal 10 minutes

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

2 sujets de discussionTotal 20 minutes

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

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.

Inclus

11 vidéos1 lecture1 devoir2 évaluations par les pairs2 sujets de discussion

11 vidéosTotal 63 minutes

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

1 lectureTotal 5 minutes

Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile5 minutes

1 devoirTotal 20 minutes

Real-World Applications and Advanced Techniques 20 minutes

2 évaluations par les pairsTotal 40 minutes

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

2 sujets de discussionTotal 20 minutes

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

Instructeurs

Mark Peco

STARWEAVER

2 Cours303 apprenants

Offert par

STARWEAVER

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Foire Aux Questions

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.