Course Duration | Fees | Mode of Study | Course Level | Institute Type |
3 Years | Varies | Full-time | Undergraduate | Private |
Semester | Subjects | Topics |
---|---|---|
Semester 1 | Introduction to Programming Mathematics for Computing Introduction to Database Systems | Programming basics in C or Python Discrete Mathematics, Calculus DBMS concepts, SQL basics |
Semester 2 | Data Structures and Algorithms Operating Systems Database Design | Arrays, Linked Lists, Trees, Sorting and Searching Algorithms Processes, Threads, Memory Management ER Models, Normalization |
Semester 3 | Object-Oriented Programming Software Engineering Advanced SQL | Classes, Objects, Inheritance, Polymorphism in Java or C++ SDLC Models, Requirement Analysis Stored Procedures, Triggers, Indexes |
Semester 4 | Web Technologies Computer Networks Database Administration | HTML, CSS, JavaScript, PHP or Python for Web OSI Model, TCP/IP, Routing Algorithms Backup and Recovery, Security and User Management |
Semester 5 | Data Warehousing and Data Mining Cloud Computing Project Work (Database) | OLAP, Data Marts, Data Mining Techniques Cloud Service Models, Deployment Models Design and Implementation of a Database System |
Semester 6 | NoSQL Databases Big Data Analytics Internship | Key-Value Stores, Document Stores, Graph Databases Hadoop Ecosystem, MapReduce, Spark Real-world Database Management Experience |
Topic | Description |
---|---|
Introduction to Database Systems | Overview of database systems, importance, and applications. |
Database Design | Conceptual, logical, and physical design phases; ER diagrams. |
SQL | Structured Query Language basics, queries, updates, and database administration. |
Normalization | Techniques to eliminate redundancy and improve data integrity. |
Transaction Management | Properties of transactions, concurrency control, and recovery mechanisms. |
Database Security | Security issues, authorization, authentication, and data encryption. |
NoSQL Databases | Introduction to NoSQL databases, types, and when to use them. |
Data Warehousing and Data Mining | Concepts of data warehousing, OLAP, and data mining techniques. |