Developer career roadmap

Data Analyst Roadmap

Use SQL, Python, statistics, and visualization to produce reproducible analysis and decision-ready reports.

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Dependency-aware sequence

1
Programming Foundations
Understand how programs process data, make decisions, repeat work, organize logic, and report errors, then build and debug a command-line application.
2
Python Fundamentals
Build, test, and debug useful Python programs with clear control flow, reusable functions, structured data, files, exceptions, packages, and classes.
3
SQL and Relational Databases
Design a relational schema, write reliable queries, update data safely, use transactions, and diagnose common correctness and performance problems.
4
Statistics for Data Science
Summarize data, reason about probability and sampling, interpret confidence intervals and tests, and communicate statistical uncertainty responsibly.
5
Data Analysis with Python
Clean, explore, summarize, validate, combine, and communicate findings from structured datasets through reproducible Python workflows.
6
Data Visualization
Select, create, evaluate, and communicate clear, accessible visualizations for distributions, comparisons, relationships, time series, and dashboards.

Project ladder

Stage 1

Build evidence that combines the skills from the roadmap stages you have completed.

Stage 2

Build evidence that combines the skills from the roadmap stages you have completed.

Stage 3

Build evidence that combines the skills from the roadmap stages you have completed.

Extend your capability

Track changes, create focused commits, work safely with branches, collaborate through pull requests, and recover from routine Git mistakes.

Automate safe, repeatable workflows involving files, structured data, spreadsheets, web requests, reports, scheduling, logging, and recovery.