Database Management Systems - Course Syllabus

Course Information

Course Title: Database Management Systems with SQL Course Code: DBMS-SQL-Labs Duration: 16 Weeks Credit Hours: 3-4 credits Prerequisites: Basic programming knowledge

Course Description

This course provides comprehensive hands-on experience with database systems, from fundamental SQL operations to advanced database concepts and modern database technologies. Students will learn to design, implement, query, and manage relational databases while also exploring NoSQL and graph database systems.

Learning Outcomes

Upon successful completion of this course, students will be able to:

1. Design and implement normalized relational database schemas
2. Write complex SQL queries using joins, subqueries, and aggregate functions
3. Create and manage database objects (tables, views, triggers, stored procedures)
4. Implement database transactions with appropriate isolation levels
5. Connect applications to databases using multiple programming languages
6. Understand and apply database optimization techniques
7. Work with modern database technologies including NoSQL and graph databases
8. Implement database security and integrity constraints

Course Structure

Module 1: Database Fundamentals (Weeks 1-4)

Topics:

• Database concepts and architecture
• SQL basics: CREATE, INSERT, SELECT, UPDATE, DELETE
• Data types and constraints
• Primary and foreign keys
• Basic queries and filtering

Labs:

• Quick Start Guide
• Foundations Lab
• In-Class Exercise
• Single Table Queries
• Foreign Keys
• Joins Part 1

Deliverables:

• Quiz 1: SQL Basics
• Assignment 1: Create a database schema

Learning Objectives:

• Create databases and tables with appropriate data types
• Write SELECT queries with WHERE, ORDER BY, and LIMIT
• Understand primary and foreign key relationships
• Perform basic INSERT, UPDATE, and DELETE operations

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Module 2: Advanced SQL Queries (Weeks 5-8)

Topics:

• Set operations (UNION, INTERSECT, EXCEPT)
• Subqueries and nested queries
• Aggregate functions and GROUP BY
• HAVING clause
• CASE expressions
• Window functions and analytical queries
• Common Table Expressions (CTEs)
• Recursive queries

Labs:

• Multi-Table Queries
• Set Operations & Nested Queries
• Aggregation & GROUP BY
• CASE Expressions
• Window Functions & Recursive Queries

Deliverables:

• Quiz 2: Advanced SQL
• Assignment 2: Complex query problems
• Midterm Project: Database analysis report

Learning Objectives:

• Write complex multi-table queries
• Use aggregate functions effectively
• Apply window functions for analytical queries
• Implement conditional logic with CASE expressions

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Module 3: Database Design & Normalization (Weeks 9-10)

Topics:

• Entity-Relationship (ER) modeling
• Database normalization (1NF, 2NF, 3NF, BCNF)
• Denormalization and when to use it
• Database design patterns
• Views and virtual tables

Labs:

• Views & Virtual Tables
• Database Normalization
• Advanced SQL Techniques
• Query Patterns

Deliverables:

• Quiz 3: Database Design
• Assignment 3: Design and normalize a database

Learning Objectives:

• Create ER diagrams
• Apply normalization principles
• Design efficient database schemas
• Create and use views for data abstraction

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Module 4: Database Programming (Weeks 11-12)

Topics:

• Stored procedures
• Functions
• Triggers
• Cursors
• Transaction management
• ACID properties
• Concurrency control
• Isolation levels

Labs:

• Cursors
• Transactions
• Triggers
• Bank Triggers Example
• Isolation Levels
• Python Database Interface
• Java Interface - Part 1
• Java Interface - Part 2
• Java Interface - Part 3

Deliverables:

• Quiz 4: Database Programming
• Assignment 4: Implement triggers and stored procedures
• Assignment 5: Bank transaction system

Learning Objectives:

• Write stored procedures and functions
• Implement database triggers
• Manage transactions with proper isolation levels
• Connect databases to applications using Python and Java

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Module 5: Modern Database Technologies (Weeks 13-16)

Topics:

• Semi-structured data (JSON, XML)
• NoSQL databases
• Document databases (MongoDB)
• Graph databases (Neo4j)
• Database optimization and indexing
• Query performance tuning

Labs:

• JSON & XML Processing
• MongoDB (NoSQL)
• Neo4j (Graph Database)
• ORM (Object-Relational Mapping)
• Node.js Database Interface

Deliverables:

• Quiz 5: Modern Databases
• Assignment 6: NoSQL project
• Final Project: Complete database application

Learning Objectives:

• Work with JSON and XML data in SQL
• Understand NoSQL database concepts
• Perform CRUD operations in MongoDB
• Write Cypher queries for Neo4j
• Choose appropriate database types for different use cases

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Grading Policy

Component	Weight
Lab Assignments	30%
Quizzes (5)	20%
Midterm Project	15%
Final Project	25%
Class Participation	10%

Grading Scale

• A: 90-100%
• B: 80-89%
• C: 70-79%
• D: 60-69%
• F: Below 60%

Required Materials

Software (All Free/Open Source)

• MySQL Community Server or MariaDB
• Python 3.7+ with MySQL connector
• Java JDK 11+
• Jupyter Notebook
• MongoDB Community Edition
• Neo4j Desktop
• A code editor (VS Code, IntelliJ IDEA, or similar)

Optional Tools

• MySQL Workbench (GUI tool)
• DBeaver (Universal database tool)
• Postman (API testing)

Textbooks & Resources

Primary Resource:

• Course Repository: DBMS-SQL-Labs

Recommended Reading:

• "Learning SQL" by Alan Beaulieu (O'Reilly)
• "Database System Concepts" by Silberschatz, Korth, and Sudarshan
• MySQL Official Documentation

Online Resources:

• SQLZoo (https://sqlzoo.net/)
• W3Schools SQL Tutorial
• DataLemur SQL Interview Questions

Course Policies

Attendance

• Regular attendance expected for lab sessions
• More than 3 unexcused absences may affect your grade

Late Work

• Assignments submitted late will incur a 10% penalty per day
• No submissions accepted after 5 days past the deadline
• Extensions may be granted for extenuating circumstances

Academic Integrity

• Collaboration is encouraged for learning, but all submitted work must be your own
• Plagiarism or cheating will result in a zero for the assignment and possible disciplinary action
• Cite any external resources used

Accessibility

• Students with disabilities should contact the instructor to discuss accommodations
• All course materials will be made available in accessible formats upon request

Weekly Schedule

Week 1: Introduction to Databases

• Topics: Database concepts, DBMS overview, SQL introduction
• Lab: Quick Start Guide
• Reading: Getting Started Guide

Week 2: Basic SQL Operations

• Topics: SELECT, INSERT, UPDATE, DELETE, WHERE clause
• Lab: Workers Database
• Quiz: SQL Basics Concepts

Week 3: Relationships and Joins

• Topics: Primary keys, Foreign keys, JOIN operations
• Lab: Foreign Keys
• Assignment 1 Due

Week 4: Multi-Table Queries

• Topics: Inner joins, Outer joins, Cross joins
• Lab: Multi-Table Operations
• Quiz 1: SQL Fundamentals

Week 5: Set Operations

• Topics: UNION, INTERSECT, EXCEPT, Subqueries
• Lab: Set Operations & Nested Queries

Week 6: Aggregate Functions

• Topics: COUNT, SUM, AVG, GROUP BY, HAVING
• Lab: Aggregate Functions & Grouping
• Assignment 2 Due

Week 7: Conditional Logic

• Topics: CASE expressions, IF statements
• Lab: CASE Expressions
• Quiz 2: Advanced SQL

Week 8: Analytical Queries

• Topics: Window functions, ROW_NUMBER, RANK, PARTITION BY
• Lab: Window Functions & Recursive Queries
• Midterm Project Due

Week 9: Database Design

• Topics: ER modeling, Normalization (1NF, 2NF, 3NF)
• Lab: Database Normalization

Week 10: Views and Virtual Tables

• Topics: Creating views, Updatable views, Materialized views
• Lab: Views & Virtual Tables
• Quiz 3: Database Design

Week 11: Database Programming I

• Topics: Stored procedures, Functions, Parameters
• Lab: Triggers & Stored Procedures
• Assignment 3 Due

Week 12: Database Programming II

• Topics: Transactions, ACID, Isolation levels
• Lab: Transaction Management
• Lab: Isolation Levels
• Assignment 4 Due

Week 13: Application Integration

• Topics: JDBC, Python DB-API, Connection pooling
• Lab: Java Database Interface
• Lab: Python Database Interface
• Quiz 4: Database Programming

Week 14: Analytical Tools

• Topics: Jupyter notebooks, ROLLUP, CUBE
• Lab: Advanced SQL Techniques
• Lab: ORM & Database Patterns

Week 15: NoSQL Databases

• Topics: JSON/XML, MongoDB, Document databases
• Lab: JSON & XML Processing
• Lab: MongoDB
• Assignment 5 Due

Week 16: Graph Databases

• Topics: Graph theory, Neo4j, Cypher language
• Lab: Neo4j (Graph Database)
• Quiz 5: Modern Databases
• Final Project Due

Projects

Midterm Project: Database Analysis Report

Create a comprehensive database for a real-world scenario, including:

• ER diagram
• Normalized schema (3NF minimum)
• 10+ complex SQL queries
• Analysis and insights from the data
• Documentation

Final Project: Complete Database Application

Build a full-stack application with:

• Well-designed database backend
• Application in Python or Java
• User interface (web or desktop)
• CRUD operations
• Transaction management
• Documentation and presentation

Project Ideas

• E-commerce platform
• Library management system
• Hospital patient management
• Social media clone
• Inventory management system
• Online learning platform
• Banking system
• Restaurant ordering system

Additional Support

Office Hours

• Monday & Wednesday: 2:00 PM - 4:00 PM
• Or by appointment

Online Resources

• Course repository: GitHub
• Discussion forum: Course website
• Email response time: Within 24 hours on weekdays

Study Groups

Students are encouraged to form study groups for:

• Lab assignments
• Project work
• Exam preparation

Tips for Success

1. Practice Regularly: SQL is a skill that improves with practice
2. Complete Labs on Time: Each lab builds on previous concepts
3. Ask Questions: Don't hesitate to seek help when stuck
4. Use Real Data: Practice with the provided datasets
5. Read Documentation: Get comfortable with official database documentation
6. Experiment: Try variations of queries to understand behavior
7. Start Projects Early: Don't wait until the deadline
8. Backup Your Work: Use version control (Git) for projects

Course Evaluation

Students will have the opportunity to provide feedback:

• Mid-semester evaluation (anonymous)
• End-of-course evaluation
• Continuous feedback welcome

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Note: This syllabus is subject to change. Any modifications will be announced in advance.

Last Updated: Spring 2026

Instructor Contact: Available through course repository issues or email