Typorithm learning path
SQL: query foundations
Build correct queries from row grain, filters and NULL to joins, aggregation and a country-aware report. Six sections per lesson, small independent tasks and explained acceptance tables. No previous SQL required; run the optional companion lab on a computer.
Study with a practical destination
Use the linked lessons in order, complete the lab and explain the decisions without the reference. Select the path and depth that match your role.
SQL: correct queries and practical analytics
Before starting: No previous SQL is required for query foundations. Complete its row-grain, NULL, join and aggregate lessons before the analytics track. Reading and self-checks work in the app; optional database execution uses a computer and the disposable companion lab.
Build and explain: Write a country-aware report with correct entity counts, observed denominators, explicit ties and reproducible time windows; bind values safely and inspect a local query plan.
- 1. Tables, rows and the question behind a query
- 2. NULL and three-valued logic
- 3. INNER JOIN and relationship cardinality
- 4. LEFT JOIN, missing matches and filter placement
- 5. Multiple one-to-many joins and honest counts
- 6. COUNT, SUM, AVG and observed denominators
- 7. Capstone: a country-aware hiring report
- 8. EXISTS, NOT EXISTS and nullable anti-joins
- 9. ROW_NUMBER and top-N per group
- 10. ROWS, RANGE and peer-aware running totals
- 11. Calendar scaffolds and justified zero days
- 12. Bound values and safe query boundaries
- 13. Indexes, EXPLAIN and measured query reasoning
- 14. Transactions, conditional changes and rollback evidence
- 15. Capstone: one representative role per company
Review evidence: Predict exact identities and values before running a query. Include empty companies, unknown and zero observations, repeated child relationships, tied ordering values and missing days. Reject the intentionally wrong queries and explain their failure. Production concurrency needs its own multi-connection evidence.
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Module 1 · 1 lessons
Tables, rows and the question behind a query
Identify the entity represented by each row before counting or joining it.
Module 2 · 1 lessons
SELECT, aliases and readable outputs
Select only the columns the consumer needs and give expressions meaningful names.
Module 3 · 1 lessons
WHERE, AND, OR and explicit precedence
Translate combined business rules into predicates that admit exactly the intended records.
Module 4 · 1 lessons
NULL and three-valued logic
Distinguish missing observations from real zero and choose explicit unknown-value behavior.
Module 5 · 1 lessons
Ordering, ties and NULL placement
Make result order explicit before asking for a first row or stable page.
Module 6 · 1 lessons
LIMIT, OFFSET and cursor boundaries
Define a stable page and distinguish a fixed snapshot from a changing catalogue.
Module 7 · 1 lessons
DISTINCT, duplicates and business identity
Remove repeated values only when that is the question you intend to answer.
Module 8 · 1 lessons
CASE and explicit category boundaries
Derive understandable categories without silently treating missing data as a measured value.
Module 9 · 1 lessons
Text search, normalization and literal patterns
Separate case normalization, pattern matching and safe parameter values.
Module 10 · 1 lessons
Half-open date ranges and declared storage
Choose inclusive starts and exclusive ends instead of guessing the last moment of a day.
Module 11 · 1 lessons
INNER JOIN and relationship cardinality
Join identities through declared relationships and predict how many rows each match creates.
Module 12 · 1 lessons
LEFT JOIN, missing matches and filter placement
Keep companies without matching roles while filtering the right-side population correctly.
Module 13 · 1 lessons
Multiple one-to-many joins and honest counts
Preaggregate independent child relationships before combining their measures.
Module 14 · 1 lessons
COUNT, SUM, AVG and observed denominators
Report how many values were observed alongside a statistic computed from them.
Module 15 · 1 lessons
GROUP BY, HAVING and population stages
Filter rows before grouping and groups afterward, without changing the intended denominator.
Module 16 · 1 lessons
Capstone: a country-aware hiring report
Combine filters, skill evidence, correct grain and observation coverage without losing empty companies.