Path to Becoming
Become a Data Scientist
[ Turn raw data into decisions. Master analysis, statistics, and communication. ]
The Architecture of a Data Scientist
A data scientist extracts insight from data and turns it into decisions. This path builds your statistics, programming, and analytical thinking from the ground up — verified by real analysis, not by completion metrics.
The Verification Standard
To complete this path, you must analyze a real dataset end-to-end — forming a hypothesis, testing it rigorously, and presenting findings that drive a decision.
The Curriculum Map
1
Phase I: The Foundation
Weeks 1-4The statistical and computational bedrock of all data work.
Statistics & Probability
Python & SQL
Data Wrangling
Exploratory Analysis
2
Phase II: Modeling & Inference
Weeks 5-8From questions to models. Making defensible claims from data.
Hypothesis Testing
Regression & Classification
Experiment Design
Data Visualization
3
Phase III: Applied Science
Weeks 9-12Analysis that moves decisions. Communicating insight that actually gets used.
Causal Inference
Machine Learning in Practice
Storytelling with Data
Production Dashboards