Learn to answer business questions with data: measurable questions, pandas, cleaning with checks, descriptive statistics, clear charts, fair comparisons, and a guided sales performance report project.
Level
01
Modules
05
Lessons
22
Introduction
What Data Analysis Is
Asking Good Questions
Downloadable Assets and Resources
Types of Data and Measures
Reading a Dataset for the First Time
Assessment
Most people who "work with data" have only ever seen it in a spreadsheet. This course teaches you the workflow analysts actually use: ask a question that data can answer, load and clean the table in Python, summarize it, chart it and write down what you found, so that someone else can act on it. It is the first course of the Data Analysis path and it starts from zero: you do not need programming or statistics, only curiosity and a browser.
Every lesson has one idea and follows the same rhythm: a short real situation, the explanation, a code demo that you run yourself in Google Colab or Jupyter, a few exercises with hints, and a summary of the key points. The printed output in each lesson was produced by running the code, so what you see on the page is what you will get. Nothing is installed or paid for, and no account is needed beyond a free notebook environment.
You follow along on one shared, fictional business, the outdoor gear shop Trailhead Outfitters, so the same customers, products and orders come back in every lesson and you learn to read a dataset the way you would at a new job.
Short lessons that go from the analysis mindset through pandas, cleaning and preparing data, to summarizing and visualizing, plus a closing guided project. You also get the clean and messy datasets with a data dictionary, starter and solution notebooks with self-checks, and a quiz at the end of every module.
If you have ever pasted numbers into a spreadsheet and wished you could just ask the data a question, this is your starting line. You do not need any background, and you will finish the first module already thinking like an analyst. By the end you will have taken a real question from raw files to a written finding, something you can show, explain and build on. Enroll today, open the first lesson, and turn the data you meet every day into answers people listen to.
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