
DBMS course
Master every layer of modern database systems, from ER modelling and SQL to concurrency control and cloud platforms. This course gives you the theoretical foundation and hands-on skills employers expect from database professionals. Whether you are aiming for a DBA role or building data-driven applications, you will finish ready to design, query, and protect production databases.
What your team will master:
You will learn how to model data requirements using entity-relationship diagrams and convert them into normalised relational schemas. You will write SQL statements for defining structures, manipulating records, and querying data across multiple tables. The course covers transaction management, isolation levels, and concurrency control so you can handle multi-user environments safely. You will also explore physical storage, indexing strategies, and query optimisation to improve database performance. Security fundamentals, backup strategies, and recovery techniques prepare you to manage production systems responsibly. Supplementary content introduces NoSQL models, distributed databases, data warehousing, and emerging trends such as vector databases and AI-assisted query tools.
How your team learns in practice DBMS course
How your team practises DBMS course
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Course content
8 Chapters • 34 LessonsDuration between 4 and 360 hours (you decide)
Chapter 1HideHide detailsSee detailsFoundations of Database Systems
Foundations of Database Systems
Lesson 1 • Roles in a Database Environment
Identifies stakeholders including DBAs, developers, and end users. Clarifies responsibilities relevant to professional practice.
Lesson 2 • Database Models and Classifications
Surveys hierarchical, network, relational, and NoSQL models. Connects model choice to use-case requirements.
Lesson 3 • DBMS Architecture and Components
Explains the three-schema architecture and internal DBMS layers. Learners map data independence to system design decisions.
Lesson 4 • What Is a Database System
Defines databases and DBMS components, contrasting them with flat-file storage. Establishes vocabulary used throughout the course.
Chapter 2HideHide detailsSee detailsEntity-Relationship Modeling
Entity-Relationship Modeling
Lesson 1 • Advanced ER Constructs
Extends basic ER with weak entities, generalisation and aggregation. Prepares learners to model complex domains accurately.
Lesson 2 • ER Diagram Design Practice
Applies ER concepts to realistic business scenarios through guided exercises. Reinforces diagram accuracy and completeness before schema conversion.
Lesson 3 • Core ER Concepts
Introduces entities, attributes, and relationships as modelling primitives. Provides the notation foundation for all subsequent ER work.
Lesson 4 • Keys and Constraints in ER Models
Covers primary keys, candidate keys, and participation constraints. Learners apply constraints to enforce business rules in diagrams.
Chapter 3HideHide detailsSee detailsRelational Model and Schema Design
Relational Model and Schema Design
Lesson 1 • ER-to-Relational Mapping
Provides systematic rules for converting ER diagrams to relational tables. Learners practise mapping all ER constructs including weak entities.
Lesson 2 • Relational Model Fundamentals
Defines relations, tuples, attributes, and domains formally. Grounds learners in the mathematical basis of the relational model.
Lesson 3 • Relational Algebra Basics
Introduces select, project, join, and set operations as query foundations. Connects algebraic operations to later SQL query writing.
Lesson 4 • Integrity Constraints
Covers domain, entity, referential, and key constraints. Learners enforce data correctness through constraint specification.
Chapter 4HideHide detailsSee detailsStructured Query Language Essentials
Structured Query Language Essentials
Lesson 1 • Views and Indexes in SQL
Defines views for abstraction and indexes for performance. Learners create and manage both objects within a live schema.
Lesson 2 • Joins and Subqueries
Combines data across tables using inner, outer, and self-joins. Learners also write correlated and nested subqueries.
Lesson 3 • Filtering, Sorting, and Aggregation
Applies WHERE, ORDER BY, GROUP BY, and HAVING clauses. Learners extract precise result sets using aggregate functions.
Lesson 4 • Data Manipulation Language
Teaches INSERT, UPDATE, DELETE, and SELECT fundamentals. Learners perform complete CRUD operations on relational tables.
Lesson 5 • Data Definition Language
Covers CREATE, ALTER, and DROP statements for schema management. Learners build and modify table structures with appropriate constraints.
Chapter 5HideHide detailsSee detailsNormalisation and Schema Refinement
Normalisation and Schema Refinement
Lesson 1 • Third Normal Form and BCNF
Removes transitive dependencies and addresses BCNF violations. Learners compare 3NF and BCNF trade-offs in practical schemas.
Lesson 2 • Higher Normal Forms
Introduces 4NF and 5NF for multi-valued and join dependencies. Learners recognise when higher normalisation is warranted.
Lesson 3 • Functional Dependencies
Defines functional dependencies and Armstrong's axioms for inference. Learners derive closures and identify all keys in a relation.
Lesson 4 • First and Second Normal Forms
Identifies and eliminates repeating groups and partial dependencies. Learners decompose unnormalised tables into 1NF and 2NF.
Chapter 6HideHide detailsSee detailsTransaction Management and Concurrency
Transaction Management and Concurrency
Lesson 1 • Concurrency Problems and Schedules
Identifies dirty reads, lost updates, and unrepeatable reads. Learners classify schedules as serial, serialisable, or non-serialisable.
Lesson 2 • Isolation Levels and MVCC
Maps SQL isolation levels to concurrency anomalies they prevent. Introduces multiversion concurrency control as an alternative to locking.
Lesson 3 • Transaction Concepts and ACID Properties
Defines transactions and the four ACID properties with examples. Establishes why transactions are essential for data integrity.
Lesson 4 • Locking Protocols
Covers shared and exclusive locks, two-phase locking, and deadlock handling. Learners apply 2PL to ensure serializable execution.
Chapter 7HideHide detailsSee detailsDatabase Storage, Indexing, and Query Processing
Database Storage, Indexing, and Query Processing
Lesson 1 • Query Processing Pipeline
Traces a query from parsing through optimization to execution. Learners read execution plans and identify bottlenecks.
Lesson 2 • Physical Storage and File Organization
Describes disk storage, buffer management, and heap file organization. Learners connect physical layout to I/O cost in query execution.
Lesson 3 • Query Optimization Techniques
Applies heuristic and cost-based optimization strategies. Learners rewrite queries and choose indexes to reduce execution cost.
Lesson 4 • Indexing Structures
Covers dense and sparse indexes, B+ trees, and hash indexes. Learners select appropriate index structures for given query patterns.
Chapter 8HideHide detailsSee detailsDatabase Security, Recovery, and Administration
Database Security, Recovery, and Administration
Lesson 1 • Failure Types and Recovery Concepts
Classifies transaction, system, and media failures and their recovery strategies. Learners match failure types to appropriate recovery mechanisms.
Lesson 2 • Database Security Fundamentals
Covers authentication, authorization, and the GRANT/REVOKE model. Learners define role-based access policies aligned with least-privilege principles.
Lesson 3 • Database Performance Monitoring
Uses system metrics, slow-query logs, and profiling tools to diagnose issues. Learners establish baselines and respond to performance degradation.
Lesson 4 • Auditing and Data Privacy Controls
Introduces audit logging, data masking, and encryption at rest and in transit. Learners implement controls that satisfy common data-privacy requirements.
Lesson 5 • Backup Strategies and High Availability
Compares full, incremental, and differential backups with replication options. Learners design backup schedules that meet recovery-time objectives.
Your valid completion certificate
This course is for you:
Software developer: wants to stop treating the database as a black box.
Career changer: moving into tech and targeting data-focused entry-level roles.
Business analyst: needs to own data models instead of just consuming reports.
IT generalist: responsible for databases but never received formal training in them.
Computer science student: looking to reinforce classroom theory with applied, practical skills.
Aspiring data engineer: building the foundational knowledge required before specialising further.
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