Unit 1: Defining Data Science and Data Ethics

Data science starts before Python, a chart, or a model. It starts with a question, the people affected by the answer, and the limits of the evidence.

This Unit preserves two Microsoft Data Science for Beginners lessons and then adds a Robotnix evidence check.

Source lessons

1. Defining Data Science
2. Introduction to Data Ethics

Read them as one argument: first define the work, then ask what can go wrong when data is collected, interpreted, and used to make decisions.

What you should be able to prove

By the end of the Unit, you should be able to:

• turn a broad topic into a question that data could actually investigate;
• name the stakeholder or decision affected by the analysis;
• identify missing perspectives, privacy concerns, or possible harms; and
• state one boundary on what the data could prove.

Evidence check

Finish with Evidence Check — Frame the Question Before Touching the Data in the Unit rail. Your artifact is a short question-and-risk brief.

The goal is not to sound certain. The goal is to make the question and its risks inspectable before analysis begins.

Runtime boundary

No notebook, account, or cloud service is required for this Unit. The complete pinned Microsoft source remains available through the course source record.