AI & Data
Data Analyst roadmap
Turn raw data into decisions with spreadsheets, statistics, SQL, Python and pandas, visualization, BI and storytelling.
- Beginner
- about 24 hours
- 11 modules
- 37 steps
What you will learn
1. Spreadsheets for Analysis
Formulas and references, lookups, data validation and cleaning, pivot tables and charts in Excel and Google Sheets.
- Formulas & References — Spreadsheets · Formulas & References
- Lookup Functions — Spreadsheets · Lookup Functions
- Data Validation — Spreadsheets · Data Validation
- Cleaning Data in Sheets — Spreadsheets · Cleaning Data in Sheets
- Pivot Tables — Spreadsheets · Pivot Tables
- Charts in Spreadsheets — Spreadsheets · Charts in Spreadsheets
2. Statistics Foundations
Summarize data with descriptive statistics, reason with probability and distributions, and spot sampling bias.
- Descriptive Statistics — Statistics · Descriptive Statistics
- Probability — Statistics · Probability
- Distributions — Statistics · Distributions
- Sampling & Bias — Statistics · Sampling & Bias
3. SQL Foundations
Query relational data with SELECT, filtering, sorting and joins.
- SQL Basics — Databases · SQL Basics
- Joins — Databases · Joins
4. Python Core
Pythonic syntax and collections, functions and decorators, iterators and generators, classes and exceptions.
- Syntax & Collections — Python · Syntax & Collections
- Functions & Decorators — Python · Functions & Decorators
- Iterators & Generators — Python · Iterators & Generators
- Classes — Python · Classes
- Exceptions & Context Managers — Python · Exceptions & Context Managers
5. Statistical Inference & Experiments
Draw conclusions from samples with hypothesis tests and confidence intervals, tell correlation from causation, run A/B tests and fit simple regressions.
- Hypothesis Testing — Statistics · Hypothesis Testing
- Confidence Intervals — Statistics · Confidence Intervals
- Correlation vs Causation — Statistics · Correlation vs Causation
- A/B Testing — Statistics · A/B Testing
- Regression Basics — Statistics · Regression Basics
6. SQL for Analytics
Summarize data with GROUP BY and HAVING, and answer harder questions with subqueries, CTEs and window functions.
- GROUP BY & HAVING — Databases · GROUP BY & HAVING
- Subqueries, CTEs & Window Functions — Databases · Subqueries, CTEs & Window Functions
7. Data Analysis with NumPy & pandas
Load, clean, join and aggregate tabular data with NumPy and pandas.
- NumPy — Data Analysis with Python · NumPy
- pandas Fundamentals — Data Analysis with Python · pandas Fundamentals
- Data Cleaning — Data Analysis with Python · Data Cleaning
- Merge & Join — Data Analysis with Python · Merge & Join
- GroupBy & Aggregation — Data Analysis with Python · GroupBy & Aggregation
8. Data Visualization
Pick the right chart for the question, plot it with Matplotlib and Seaborn, and combine charts into clear dashboards.
- Choosing the Right Chart — Data Visualization & BI · Choosing the Right Chart
- Visualization with Matplotlib & Seaborn — Data Analysis with Python · Visualization with Matplotlib & Seaborn
- Dashboards — Data Visualization & BI · Dashboards
9. BI Modeling & Tools
Model data for BI and learn the core concepts shared by Power BI, Tableau and Looker.
- Data Modeling for BI — Data Visualization & BI · Data Modeling for BI
- Power BI, Tableau & Looker Concepts — Data Visualization & BI · Power BI, Tableau & Looker Concepts
10. Business Questions & Storytelling
Turn business questions into KPIs and metrics, and present findings as a story that drives decisions.
- KPIs & Metrics — Data Visualization & BI · KPIs & Metrics
- Data Storytelling — Data Visualization & BI · Data Storytelling
11. Data Analyst Capstone
A scenario-based final challenge mixing spreadsheets, statistics, SQL, pandas, visualization and business storytelling.
- Data Analyst Capstone — Capstones · Data Analyst Capstone
Each step unlocks when you answer its questions well enough, and a module you finish counts in every roadmap that shares it.
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