Data Analysis Essentials
⏱ TBDMost people do not need to become data scientists. They need to answer a question with data and be right. Data Analysis Essentials teaches the full workflow — scope, clean, analyze, visualize, share — with an AI tool supporting every step.
Six self-paced modules move in the order real analysis happens. Module 1 orients you and builds your learning path. Module 2 sets up a data project properly, starting with an objective sharp enough to answer. Module 3 covers the unglamorous majority of the job: cleaning and combining messy data from different sources. Module 4 works through core analyses and calculations. Module 5 turns findings into summaries, charts, and dashboards people actually read. Module 6 closes with data integrity, ethics, and how to share results responsibly.
Each module includes a purpose-built AI tool — Learning Path Planner, Analysis Objective Builder, Data Cleaning Copilot, Formula Builder, Chart and Dashboard Advisor, and a Capstone Evaluator that scores your final work — plus a knowledge check and workbook reflection.
You get the full Course Book, Workbook, and glossary. AI handles the mechanical work of cleaning, calculating, and charting. You keep the judgment about what the numbers actually mean and which decision they support.
What you’ll learn
Set up a data project with an objective sharp enough to answer Clean and combine messy data from multiple sources Run the core analyses and calculations most business questions need Summarize findings in charts and dashboards people actually read Apply data integrity and ethics standards before you share results Complete a capstone analysis and get it scored by an AI evaluator
Who this course is for
Anyone who needs to answer real questions with data — analysts, managers, operations staff, and business owners working out of spreadsheets.
Course curriculum
- Get Started
Orientation: how this class works and how to use it.
- Get Started
- Course Book
The full self-guided Course Book for this class.
- Course Book
- Workbook
- Module 1: Getting Started with Data Analysis
Module 1 — Getting Started with Data Analysis.
- Getting Started with Data Analysis
- AI Tool — Learning Path Planner
- Getting Started with Data Analysis — Knowledge Check
- Module 1 — Workbook Reflection
- Module 2: Setting Up Your Data Project
Module 2 — Setting Up Your Data Project.
- Setting Up Your Data Project
- AI Tool — Analysis Objective Builder
- Setting Up Your Data Project — Knowledge Check
- Module 2 — Workbook Reflection
- Module 3: Cleaning and Combining Data
Module 3 — Cleaning and Combining Data.
- Cleaning and Combining Data
- AI Tool — Data Cleaning Copilot
- Cleaning and Combining Data — Knowledge Check
- Module 3 — Workbook Reflection
- Module 4: Core Analyses and Calculations
Module 4 — Core Analyses and Calculations.
- Core Analyses and Calculations
- AI Tool — Formula Builder
- Core Analyses and Calculations — Knowledge Check
- Module 4 — Workbook Reflection
- Module 5: Summarizing and Visualizing Data
Module 5 — Summarizing and Visualizing Data.
- Summarizing and Visualizing Data
- AI Tool — Chart and Dashboard Advisor
- Summarizing and Visualizing Data — Knowledge Check
- Module 5 — Workbook Reflection
- Module 6: Data Integrity Ethics and Sharing Results
Module 6 — Data Integrity Ethics and Sharing Results.
- Data Integrity Ethics and Sharing Results
- AI Tool — Capstone Evaluator
- Data Integrity Ethics and Sharing Results — Knowledge Check
- Module 6 — Workbook Reflection
- Course Wrap-Up
Course conclusion: what you built, where you go next, and the glossary.
- Course Conclusion