See joins as row pairing, then explain duplicates, left joins, and group-by counts with hand-checkable tables
5 sections · 10 lessons
Define joins as row pairing, then trace how INNER JOIN and LEFT JOIN preserve or discard rows and where duplicate-looking results come from.
4 lessonsBuild three-table joins one relationship at a time, checking intermediate keys and row counts instead of guessing at the final shape.
1 lessonPredict how GROUP BY changes COUNT, SUM, and AVG after a join, then choose safer aggregation order to prevent double-counting.
2 lessonsPlace filters in ON or WHERE with intent, then debug wrong counts and aggregates by inspecting uniqueness, keys, and intermediate results.
2 lessonsExplain a complete join and grouping example from rows to totals, then apply a repeatable checklist to future queries.
1 lessonEvery lesson in order.
10 lessons
Joins start making sense when you stop treating them as magic and start seeing how they pair rows. This course rebuilds that model from the ground up, then shows how INNER JOIN, LEFT JOIN, duplicates, multi-table joins, and GROUP BY actually change row counts and totals. It is aimed at SQL users who can write joins but still have to guess at the result. By the end, you can reason through small examples by hand and explain where every row and aggregate came from.
The course covers join row pairing, INNER JOIN and LEFT JOIN behavior, duplicate-looking rows from one-to-many and many-to-many matches, and stepwise joins across three tables. It also covers GROUP BY after joins, avoiding double-counting with derived tables, ON versus WHERE placement, and a debugging workflow for row counts and aggregates.
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Average pass rate · Freeman et al., PNAS 2014
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Retrieval practiceRe-reading
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