This comprehensive practical course introduces SQL as a fundamental tool for working with structured data in data science, business intelligence, analytics and database environments. Learners will develop the ability to retrieve, filter, organise, transform and analyse data stored in relational databases using practical SQL techniques.
The course begins with database and SQL fundamentals before progressing to database structures, tables, records, fields, primary keys, foreign keys and relationships. Learners will learn how to write SQL queries using SELECT statements, filtering conditions, sorting, grouping, aggregation and different types of joins.
The programme also covers subqueries, common table expressions, views, data cleaning, handling missing values, date and time data, text manipulation and conditional logic. Learners will learn how SQL can be used to prepare datasets for analysis and support data-driven decision-making.
Practical exercises will introduce learners to commonly used relational database systems and SQL environments. The course also demonstrates how SQL works alongside data science tools such as Python and analytical workflows, allowing learners to retrieve database information and prepare it for further analysis.
Through practical datasets, business scenarios and a final data analysis project, learners will develop the confidence to write SQL queries, investigate datasets, identify patterns, generate analytical summaries and prepare clean data for data science applications.
Introduction to SQL and data science
Introduces SQL, relational databases and the role of SQL in data science and data analytics.
1 LessonsDatabase fundamentals
Provides a foundation in database concepts and structures used when working with SQL.
1 LessonsSQL data types and database structure
Introduces common SQL data types and how data is structured within relational databases.
2 LessonsBasic SQL queries
Teaches learners how to retrieve information from databases using fundamental SQL queries.
2 LessonsFiltering and sorting data
Develops skills for finding specific information and organising query results.
2 LessonsSQL functions and data transformation
Introduces built-in SQL functions used to transform and analyse data.
2 LessonsAggregation and data summarisation
Teaches learners how to summarise large datasets and generate useful analytical information.
2 LessonsSQL joins and relational data analysis
Develops practical skills for combining information from multiple related tables.
1 LessonsSubqueries and advanced querying
Introduces techniques for writing more powerful queries and solving complex data analysis problems.
2 LessonsTeaches learners how to identify and correct common data quality problems using SQL.
2 LessonsCommon table expressions and views
Introduces reusable SQL structures that simplify complex analysis and data workflows.
2 LessonsData modification and database management
Introduces basic SQL commands for adding, modifying and removing data.
2 LessonsSQL for exploratory data analysis
Applies SQL techniques to explore datasets and identify patterns, trends and relationships.
2 LessonsSQL for business and data analytics
Demonstrates how SQL can be used to solve practical business and analytical problems.
1 LessonsSQL with Python and data science tools
Introduces the integration of SQL with Python and other data science workflows.
2 LessonsSQL performance and best practices
Introduces techniques for writing efficient, readable and maintainable SQL queries.
2 LessonsData security and responsible database use
Covers essential security and ethical practices when accessing and analysing data.
2 LessonsFinal SQL data science project
Allows learners to apply their SQL skills to a complete practical data analysis project
2 Lessons
Senior ICT Academy
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- Price
USh480,000
USh650,000 - Instructor Senior ICT Academy
- Duration 120 days
- Category Programming Languages
- Curriculum 18
- Lectures 32
- Enrolled 0