Relational Databases (PostgreSQL) & AI Assistants
Description
This hands-on course introduces relational database fundamentals and PostgreSQL development while integrating AI-assisted workflows throughout. Participants learn how to design schemas, write and optimize SQL queries, manage transactions, and integrate PostgreSQL with Java applications. AI tools are used to generate queries, explain execution plans, suggest optimizations, and scaffold integration code—emphasizing critical evaluation and responsible AI usage in database engineering.
Indicative Duration: 48 training hours
*Duration is adjusted based on the final scope and the target audience.
Scope
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1. Relational Database Foundations
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• Relational databases overview • PostgreSQL setup • Client tools • AI Practice: AI explains concepts (tables, keys, normalization) |
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| • Git & SQL scripts • Project organization • AI Practice: AI generates schema templates, Git commit messages |
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2. SQL Fundamentals
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• Basic SQL: SELECT, WHERE, ORDER BY • AI Practice: AI generates queries and explains results |
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| • Data modeling & ER diagrams • AI Practice: AI suggests tables, relationships, primary/foreign keys |
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3. Data Modeling & Schema Design
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• Advanced SQL: JOINs, GROUP BY, aggregates • AI Practice: AI generates complex queries, explains execution |
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| • Indexing & constraints • AI Practice: AI suggests indexes, constraints, uniqueness |
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| 4. Transactions & Data Integrity | • Transactions & ACID principles • AI Practice: AI explains isolation levels, rollback scenarios |
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| 5. Application Integration | • JDBC integration with Java • AI Practice: AI scaffolds connection code, CRUD operations |
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| 6. Database Programming | • Views • Stored procedures • Triggers • AI Practice: AI generates views and trigger examples |
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7. Performance & Operations
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• Query optimization & EXPLAIN • AI Practice: AI suggests query improvements |
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| • Backup • Restore • Migrations • AI Practice: AI suggests migration scripts and versioning strategies |
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| 8. Capstone Project | • Capstone Project Development • AI Practice: AI scaffolds database, queries, and JDBC integration |
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Learning Objectives
Upon completion of the course participants will be able to:
- Design relational schemas and model data using normalization and ER principles
- Write and optimize SQL queries, including joins, aggregations, and indexing strategies
- Manage transactions, constraints, and database integrity mechanisms
- Integrate PostgreSQL with Java applications using JDBC
- Use AI tools to generate, analyze, and improve database queries while validating correctness and performance
Target Audience
- Roles: Software Engineers, Backend Developers, Database Engineers
- Seniority: Junior to Mid-Level Professionals, Senior Professional interested in enhancing workflows with AI-assisted tooling
Prerequisite Knowledge
- Basic understanding of programming concepts
- Familiarity with command-line tools
- Introductory knowledge of Java (beneficial for JDBC integration)
Delivery Method
Sessions can be delivered via the following formats:
- Live Online – Interactive virtual sessions via video conferencing
- On-Site – At your organization’s premises
- In-Person – At Code.Hub’s training center
- Hybrid – A combination of online and in-person sessions
