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Data Science

Data Scientist

Turn data into insight and decisions: statistics, Python, exploratory analysis, machine learning, and clear communication of results.

PythonpandasSQLscikit-learnJupyter
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1

Math & Python foundations

Python for data analysis (pandas, NumPy)

Essential

Statistics & probability

Essential

SQL for analysis

Recommended
2

Exploratory data analysis

Data cleaning & wrangling

Essential

Visualization & storytelling

Recommended
Build it

EDA on a real dataset

beginner

Pick a Kaggle dataset, clean it, and produce a notebook of insights and charts.

3

Machine learning

Supervised learning (regression & classification)

Essential

Model evaluation & validation

Essential

Feature engineering

Recommended
Build it

Build and submit a Kaggle competition entry

intermediate

Train, validate, and submit a model to a beginner competition.

4

Experimentation & communication

A/B testing & experiment design

Recommended

Communicating results to stakeholders

Recommended

Land the job

Turn the skills you built into offers โ€” resume, tailoring, applications, and interview prep.

Build a recruiter-ready resume

Essential

Use the builder to produce a clean, ATS-friendly resume from your career memory.

Go

Tailor your resume to each role

Recommended

Match keywords and highlight the experience each job actually asks for.

Go

Browse and apply to open roles

Essential

Find roles that match the skills on this path and apply with your tailored resume.

Go

Prep for interviews

Essential

Practice coding, system design, and behavioral rounds with AI-driven mock interviews.

Go