Intermediate SQL Course in Uganda: Practical Data Analysis

Course outline and learning expectations

This is a tutor-led course. The outline shows what your tutor will cover; teaching materials and examinations are provided directly to enrolled students.

What you will learn

• By the end of this intermediate SQL course, the learner will be able to:
• Plan and write accurate queries across several related tables.
• Use inner, outer, cross, and self joins for different data relationships.
• Find missing, unmatched, and duplicate records with reliable SQL patterns.
• Build scalar, multi-row, and correlated subqueries.
• Use `EXISTS`, `NOT EXISTS`, `IN`, and comparison subqueries appropriately.
• Break complex queries into readable stages with common table expressions.
• Combine result sets with `UNION`, `UNION ALL`, `INTERSECT`, and `EXCEPT`.
• Apply `CASE`, conditional aggregation, text, numeric, and date functions to reporting problems.
• Calculate rankings, running totals, period comparisons, and changes with SQL window functions.
• Create reusable views and protect multi-step data changes with transactions.
• Debug complex SQL and validate results for joins, `NULL`, duplicates, and incorrect totals.
• Deliver a portfolio-ready SQL analysis project using a realistic Uganda or Africa dataset.

Modules

1. 1

   Intermediate SQL foundations and query logic

   Reviewing `SELECT`, filtering, grouping, joins, and `NULL`Turning business questions into query stepsThe logical processing order of a `SELECT` queryChoosing clear table aliases and column namesPreventing accidental duplicates and misleading totalsFormatting longer SQL statements for readabilityPractice: auditing an existing sales or programme report
2. 2

   Multi-table and advanced SQL joins

   Joining three or more related tables`INNER`, `LEFT`, `RIGHT`, and `FULL OUTER JOIN``CROSS JOIN` and when Cartesian results are intentionalSelf joins for hierarchies and comparisonsOne-to-many and many-to-many relationshipsJoin conditions in `ON` versus filters in `WHERE`Finding unmatched data with anti-join patternsPractice: linking branches, staff, customers, products, orders, and payments
3. 3

   SQL subqueries and `EXISTS`

   Scalar and single-column subqueriesMulti-row subqueriesSubqueries in `SELECT`, `FROM`, and `WHERE`Correlated subqueries`IN`, `EXISTS`, and `NOT EXISTS`Comparing a row with group or overall resultsChoosing between a join and a subqueryPractice: customers above average, inactive members, and products without sales
4. 4

   Common table expressions and set operations

   Creating common table expressions with `WITH`Building a complex answer in clear stagesReusing calculated query resultsCombining compatible results with `UNION` and `UNION ALL`Finding shared results with `INTERSECT`Finding differences with `EXCEPT`Managing duplicates across result setsPractice: combining branch records and comparing reporting periods
5. 5

   Conditional logic and advanced SQL functions

   Creating categories with `CASE`Conditional aggregationHandling missing and zero values with `COALESCE` and `NULLIF`Cleaning and standardising textExtracting and comparing date partsCalculating intervals and reporting periodsNumeric calculations, percentages, and safe divisionPractice: loan status bands, sales categories, age groups, and programme indicators
6. 6

   Window functions for data analysis

   Understanding `OVER`, `PARTITION BY`, and window `ORDER BY`Ranking with `ROW_NUMBER`, `RANK`, and `DENSE_RANK`Comparing rows with `LAG` and `LEAD`Running totals and cumulative valuesPercent of total and group comparisonsFirst, latest, and top records within a categoryMoving and period-based calculationsPractice: branch rankings, monthly changes, repeat customers, and portfolio trends
7. 7

   Reusable and safe SQL

   Creating and querying viewsWhen a view improves consistency and reuseMulti-step data changesTransactions with `BEGIN`, `COMMIT`, and `ROLLBACK`Checking affected records before a changeApplying constraints for reliable dataWriting maintainable SQL with comments and consistent styleScope boundary: SQL language practice, not database server administration
8. 8

   Intermediate SQL project for Uganda and Africa

   Inspect a relational database with several connected tablesDefine useful operational or analytical questionsUse joins, subqueries, common table expressions, conditional logic, and window functionsValidate results against source totals and business rulesProduce a clean, commented SQL script and a concise findings summaryproject contexts: SACCO loan portfolioretail branch performanceagriculture supply chainhealth programme monitoringeducation outcomeslogisticsor e-commerce operations