SQL & Data Analysis

1. SELECT Fundamentals — your first queries (~8h) — You can pull exactly the rows you want from any table — SELECT, WHERE, ORDER BY, LIMIT — and predict the row count before you hit run.
2. Joins, Aggregations & Subqueries (~12h) — You can combine tables and summarize them: JOINs you can draw before you write, GROUP BY you can defend, and a subquery when nothing simpler does the job.
3. Window Functions & Real-World SQL (~10h) — You can rank, compare rows to their neighbors, and compute running totals — the SQL that separates working analysts from tutorial-finishers, and the layer interviews actually test.
4. Python + pandas — when SQL isn't enough (~12h) — You can load a messy CSV, audit it, clean it with documented decisions, and answer questions SQL alone can't reach — inside a notebook someone else can run.
5. Visualization & Dashboards (~8h) — You can turn a table of numbers into a chart that makes exactly one point, and a live dashboard a non-technical person can filter without your help.
6. The Full Analysis — from question to story (~10h) — You can take a vague question and a raw dataset all the way to a written, published finding that someone could act on — and you know what to cut when time runs out.

Capstone assignments: One dataset, one question, one page of truth · The personal-data audit · A dashboard your least-technical relative can use

After this course: Intro to SQL + Advanced SQL certificates · Data Analysis with Python certification · SQL (Basic) skill certification · LinkedIn Jobs · Internshala · Kaggle competitions · Upwork

Continue with: AI Engineering with Claude

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