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Data Modeling with AI: Fundamentals to ChatGPT & Copilot
Role Play
Rating: 4.9 out of 5(27 ratings)
222 students

Data Modeling with AI: Fundamentals to ChatGPT & Copilot

Master business intelligence fundamentals, data warehouse & ETL. Use AI tools like ChatGPT & Copilot for data modeling!
Last updated 4/2026
English

What you'll learn

  • Understand data modeling fundamentals: conceptual, logical & physical models
  • Learn how to use Artificial Intelligence (Copilot & ChatGPT) in every step of the Data Modeling process
  • Build star schemas, identify facts & dimensions, and master additivity
  • Learn ETL & ELT basics and understand how they shape your data models
  • Practice normalized vs. dimensional models and know when to use which
  • Use MySQL Workbench and dbdiagram to design and implement models
  • Practice hands-on ETL flows with free tools (Apache Hop)
  • Work through a capstone project combining all skills

Course content

10 sections130 lectures14h 43m total length
  • Welcome and getting to know your lecturer3:33
  • What to Expect from this course & Learning Outcomes8:09
  • Course Slides0:02

Requirements

  • Just be curious, all foundations are provided in the course :-)

Description

The world of data is changing fast. On one side, organizations still rely on proven data modeling and business intelligence fundamentals — star schemas, facts and dimensions, data warehouses, and ETL pipelines. On the other side, AI tools like ChatGPT and GitHub Copilot are transforming the way we design, implement, and optimize data models.

This course brings both worlds together. It gives you a solid foundation in traditional data modeling while showing you how to use AI as a co-pilot in your daily work. You’ll learn how to design conceptual, logical, and physical models, build data warehouses and data marts, and understand how ETL and OLAP vs. OLTP systems shape your architecture. At the same time, you’ll discover how ChatGPT and Copilot can help you brainstorm schemas, generate SQL code, check data quality, and even document your models.

Unlike many theory-heavy courses, this one is practical and hands-on. You’ll work with free tools like MySQL Workbench and dbdiagram to create your models, build ETL flows with Apache Hop, and connect your data to Power BI for analytics. You’ll also tackle realistic dirty datasets, practicing data cleansing and transformation just like you would in a real project.

The highlight of the course is the FastBite Capstone Project, a simulated food delivery business. You’ll start from raw source data, design the dimensional model, implement a data warehouse in MySQL, build ETL flows to populate your fact and dimension tables, and finally connect to Power BI to answer real business questions. Along the way, you’ll learn how to use AI tools as your assistant: to suggest schema designs, classify facts and dimensions, generate transformation logic, and write documentation.

By the end of this course, you will:

  • Apply AI support with ChatGPT and Copilot at every stage of the modeling workflow

  • Confidently design and implement data warehouses and data marts

  • Master dimensional modeling with star schemas, SCDs, facts, dimensions, and additivity

  • Understand the role of ETL/ELT pipelines and where to implement logic

  • Build a portfolio-ready project that proves your skills in data modeling and business intelligence

This is the modern way to learn data modeling: combining classic BI best practices with AI-powered productivity.

If you want to build strong foundations in data modeling and business intelligence, while also learning how to leverage AI tools to become a faster and smarter data professional, this course is for you.

Who this course is for:

  • Students or career changers aiming for a career in BI, data engineering, or analytics
  • Business Intelligence professionals who want to deepen their data modeling skills
  • Data analysts who need to understand data warehouses and dimensional models
  • Aspiring data engineers looking for hands-on practice with ETL and data architecture
  • Students or career changers aiming for a career in BI, data engineering, or analytics