Path to Becoming

Become a Data Scientist

[ Ask useful questions, work with data and explain the evidence. ]

Learning towards Data Scientist

Build foundations in statistics, programming and analysis, then apply them to a question that matters to you. These stages are an example rather than a fixed schedule or promise of job readiness.

Example practice

Example practice: inspect a dataset, explain the question and assumptions, and present findings with their limitations. Use a suitable external data tool when the exercise needs one.

An example path

Phase I: The Foundation

Start here

Learn to inspect data and ask a clear analytical question.

Statistics & Probability

Python & SQL

Data Wrangling

Exploratory Analysis

Phase II: Modeling & Inference

Build on

Choose a method and examine what its results support.

Hypothesis Testing

Regression & Classification

Experiment Design

Data Visualization

Phase III: Applied Science

Practise

Communicate findings, assumptions and uncertainty.

Causal Inference

Machine Learning in Practice

Storytelling with Data

Production Dashboards

Ready to build the path?

[ Start with your goal and take the next step. ]