Instructor Profile:
Dr. Prajakta Shirke
Assistant Professor, Department of Computer Sciences and Engineering, Sandip University, Nashik
Dr. Prajakta Shirke is an accomplished academic and researcher in the field of Computer Engineering, currently serving as an Assistant Professor in the Department of Computer Sciences and Engineering at Sandip University, Nashik. With a solid educational foundation, she earned her Bachelor of Engineering (BE) degree in Information Technology and her Master of Engineering (ME) degree in Computer Science & Engineering, both from the Sandip Institute of Technology and Research Centre, affiliated with SPPU. She further advanced her academic journey by obtaining a PhD degree in Computer Engineering from Sandip University.
With over nine years of teaching experience, Dr. Shirke has established herself as a dedicated educator, inspiring and guiding students in their academic pursuits. Her commitment to knowledge dissemination is evident in her impressive publication record, which includes approximately 15 research papers in both international journals and conferences. Many of her works are published in prestigious SCI/Scopus-indexed journals, showcasing her contributions to the advancement of her field. In addition to her research papers, Dr. Shirke holds three patents, one copyright, and has authored a book, underscoring her innovative spirit and expertise.
Dr. Shirke’s research interests lie primarily in the areas of Artificial Intelligence, Machine Learning, and Deep Learning. She is passionate about exploring the transformative potential of these technologies and their applications across various domains. Through her work, she aims to contribute to the development of intelligent systems that enhance human capabilities and improve the quality of life.
Dr. Prajakta Shirke is a valuable asset to the academic community, and her extensive knowledge and experience make her a highly sought-after expert in her fields of interest. She is dedicated to fostering a culture of learning and innovation, preparing her students for the challenges of the evolving technological landscape.
Course Outline: DBMS – Language & Data Models
Module 1: Introduction to Database Management Systems
- Overview of DBMS: Definition and purpose of a Database Management System, Importance of DBMS in modern applications
- Database Models: Hierarchical Model, Network Model, Relational Model, Object-Oriented Model
- Database Architecture: Three-tier architecture, Client-server architecture
- Database System Components: Database engine, Data definitions and data manipulation
Module 2: Data Models
- Introduction to Data Models: Definition and significance of data models, Types of data models
- Entity-Relationship (ER) Model: ER diagrams and components (entities, attributes, relationships), Mapping ER diagrams to relational schema
- Relational Data Model: Structure of relational databases, Relations, tuples, and attributes, Primary keys, foreign keys, and constraints
- Object-Oriented Data Model: Concepts of objects, classes, and inheritance, Differences between relational and object-oriented models
Module 3: Query Languages
- Introduction to Query Languages: Purpose and types of query languages, Overview of SQL (Structured Query Language)
- SQL Syntax and Semantics: Basic SQL commands (SELECT, INSERT, UPDATE, DELETE), Data definition language (DDL) commands, Data manipulation language (DML) commands
- Advanced SQL Queries: Joins (inner, outer, cross), Subqueries and nested queries, Aggregate functions and grouping
- Transaction Control: Transactions and ACID properties, Concurrency control and locking mechanisms
Module 4: Emerging Trends in DBMS
- NoSQL Databases: Overview of NoSQL and its significance, Types of NoSQL databases (document, key-value, column-family, graph)
- Data Warehousing and Data Mining: Concepts of data warehousing, Introduction to data mining techniques
- Big Data and Distributed Databases: Challenges of big data management, Introduction to distributed databases and their architecture
- Future Trends in DBMS: Cloud databases and services, Emerging technologies (Blockchain, AI integration in databases)
Course Objectives: By the end of this course, participants will be able to:
- Understand the fundamental concepts and architectures of Database Management Systems.
- Differentiate between various data models and their applications.
- Write complex SQL queries for data manipulation and retrieval.
- Explore emerging trends and technologies in the field of database management.
