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Data Science & Analytics in Practice

The practitioner's course. Learn to turn messy data into confident decisions โ€” from cleaning and exploration to statistics, A/B testing, visualization, SQL, and complete ML workflows. You'll build a portfolio-ready end-to-end analysis on a real dataset and earn a certification.

Machine Learning Intermediate Data Science
  • 9 lessons
  • Updated 09/05/2026
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The language of data

Most business data lives in databases, and SQL is how you get it. Analysts who know SQL don't wait on anyone.

The core you'll use constantly

SELECT region, COUNT(*) AS orders, SUM(revenue) AS total
FROM sales
WHERE order_date >= '2025-01-01'
GROUP BY region
HAVING SUM(revenue) > 10000
ORDER BY total DESC;

What to master

  • SELECT / WHERE / ORDER BY โ€” filtering and sorting.
  • GROUP BY & aggregations โ€” counts, sums, averages.
  • JOINs โ€” combining tables (the skill that unlocks everything).
  • Subqueries & CTEs โ€” for readable, layered logic.

Takeaway: SQL is the highest-leverage single skill for a working analyst.

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