Computer Science & Engineering

Computer Science and Engineering (CSE) is an academic program at many universities which comprises scientific and engineering aspects of computing. CSE is also a term often used in Europe to translate the name of engineering informatics academic programs. It is offered in both Undergraduate as well Postgraduate with specializations.

Academic programs vary between colleges. Undergraduate Courses usually include programming, algorithms and data structures, computer architecture, operating systems, computer networks, parallel computing, embedded systems, algorithms design, circuit analysis and electronics, digital logic and processor design, computer graphics, scientific computing, software engineering, database systems, digital signal processing, virtualization, computer simulations and games programming. CSE programs also include core subjects of theoretical computer science such as theory of computation, numerical methods, machine learning, programming theory and paradigms.

Modern academic programs also cover emerging computing fields like image processing, data science, robotics, bio-inspired computing, computational biology, autonomic computing and artificial intelligence.Most of the above CSE areas require initial mathematical knowledge, hence the first year of study is dominated by mathematical courses, primarily discrete mathematics, mathematical analysis, linear algebra, Probability, and statistics, as well as the basics of Electrical and electronic engineering, physics - field theory, and electromagnetism.

Vision

To generate competent professionals to become part of the industry and research organizations at the national and international levels.

Mission

• Providing a strong theoretical and practical background across the computer science discipline with an emphasis on software development.

• Empowering the youth in rural communities with computer education.

• Inculcating professional behavior, strong ethical values, innovative research capabilities, and leadership abilities.

Laboratory Details Computer Science & Engineering

IT LAB - 2

The Computer Science and Engineering department has Hi-Tech Laboratory for developing programs. This lab is designed and maintained based on the curriculum.

LABORATORIES

• GE3171 - Problem Solving and Python Programming Laboratory
• CS3271 – Programming in C Laboratory
• CS3311 – Data Structures Laboratory
• CS3381 – Object Oriented Programming Laboratory
• CS3361 – Data Science Laboratory
• CS3461 – Operating Systems Laboratory
• CS3481 – Database Management Systems Laboratory
• CS3491 – Artificial Intelligence and Machine Learning Laboratory
• CS3401 - Algorithms Laboratory

PROBLEM SOLVING AND PYTHON LABORATORY(Area : 1420.84 sq.m)

Students to explore various problem-solving approaches while gaining a solid understanding of basic programming constructs in Python. Through hands-on practice, students will develop and apply computational strategies to create Python-based solutions for real-world challenges. They will delve into Python's versatile data structures, including lists, tuples, and dictionaries, to manage and process data effectively. Additionally, students will learn to perform file input and output operations, equipping them with essential skills for tackling diverse programming tasks.

COURSE OUTCOMES:

At the end of the course, students will be capable of developing algorithmic solutions for simple computational problems and writing basic Python programs. They will be able to implement programs using conditionals and loops to address various problem-solving scenarios. Students will also learn how to decompose Python programs into smaller, manageable functions. Additionally, they will gain experience in processing compound data through Python's data structures, such as lists, tuples, and dictionaries. Lastly, students will acquire the skills to use Python packages for developing software applications, preparing them for real-world programming challenges.

PROGRAMMING IN C LABORATORY(Area : 1420.84 sq.m)

Students explore the fundamental constructs of C programming and apply them to real-world problems. Students will start by familiarizing themselves with basic C programming constructs, laying the foundation for further exploration. They will then advance to developing programs using arrays to manage data more efficiently. The course will also cover more advanced topics, such as utilizing strings, pointers, and functions to create dynamic applications. As students progress, they will explore the use of structures to organize complex data and file processing techniques to handle data input and output. By the end of the course, students will have a strong understanding of how to develop comprehensive applications using C programming.

COURSE OUTCOMES:

Upon completion of the course, students will be able to demonstrate a strong understanding of C programming constructs and apply them effectively in various programming scenarios. They will be capable of developing programs using basic constructs, as well as more advanced techniques, including the use of arrays to handle data. Students will also gain the skills to create applications utilizing strings, pointers, and functions to enhance program functionality. Additionally, they will be able to develop applications using structures for organizing complex data and implement file processing techniques to manage data input and output efficiently. Overall, students will be well-prepared to design and implement robust applications in C.

DATA STRICTURES LABORATORY(Area : 1420.84 sq.m)

Students to explore and implement a wide range of important data structures and algorithms. Students will begin by demonstrating the array implementation of linear data structure algorithms and advance to developing applications using stacks and linked lists. The course will then cover more complex data structures, including the implementation of Binary Search Tree (BST) and AVL Tree algorithms, essential for efficient data organization and retrieval. Students will also gain experience with the Heap algorithm for priority-based data management and implement Dijkstra’s algorithm to solve shortest-path problems. Additionally, students will explore graph algorithms, such as Prim’s algorithm, and focus on key techniques in sorting, searching, and hashing to optimize data processing. Through these practical implementations, students will deepen their understanding of algorithmic problem-solving and their application to real-world computational challenges.

COURSE OUTCOMES:

At the end of this course, students will be equipped to implement a variety of linear data structure algorithms and develop applications using stacks and linked lists. They will also gain proficiency in implementing key operations for Binary Search Trees (BST) and AVL trees, essential for efficient data management. The course will enable students to implement graph algorithms to solve complex network-based problems. Additionally, students will analyze and apply various searching and sorting algorithms, gaining the ability to evaluate their efficiency in different scenarios. Through these skills, students will be well-prepared to tackle a wide range of algorithmic challenges in real-world applications.

OBJECT ORIENTED PROGRAMMING LABORATORY (Area : 1420.84 sq.m)

This course is designed to help students explore and build software development skills using Java programming for real-world applications. Students will gain a deep understanding of key concepts such as classes, packages, interfaces, inheritance, exception handling, and file processing, and will apply these concepts in the creation of practical applications. The course will also focus on developing applications using generic programming techniques, enabling students to write reusable and type-safe code. Additionally, students will explore event handling to create interactive applications with responsive user interfaces. By the end of the course, students will be well-equipped to develop robust, scalable software solutions using Java.

COURSE OUTCOMES:

Upon completion of this course, students will be able to design and develop Java programs using core object-oriented programming concepts, including classes, inheritance, and polymorphism. They will have the skills to develop simple applications utilizing object-oriented principles such as packages and exception handling to ensure robust and maintainable code. Students will also gain expertise in implementing multithreading and generics to create efficient and reusable code. The course will further enable students to build graphical user interfaces (GUIs) and develop event-driven applications to solve real-world problems. Lastly, students will be capable of implementing and deploying web applications using Java, equipping them with the skills to create modern, interactive, and scalable web-based solutions.

DATA SCIENCE LABORATORY(Area : 1420.84 sq.m)

This course is designed to help students explore the essential Python libraries for data science, enabling them to work with and analyze data effectively. Students will begin by understanding basic statistical and probability measures, which are foundational for interpreting data in the field of data science. The course will then guide students through descriptive analytics, helping them extract meaningful insights from benchmark datasets. As part of their learning, students will apply correlation and regression analytics to standard datasets to identify relationships and trends. Finally, students will explore Python’s visualization packages to present and interpret their findings, gaining the skills needed to communicate data-driven insights through clear and impactful visualizations.

COURSE OUTCOMES:

At the end of this course, students will be able to effectively utilize Python libraries for data science, equipping them with the tools necessary for data analysis. They will apply fundamental statistical and probability measures to interpret and analyze data in the context of data science. Students will gain the skills to perform descriptive analytics on benchmark datasets, uncovering valuable insights. Additionally, they will be able to perform correlation and regression analysis on standard datasets, identifying relationships and trends. Finally, students will be proficient in presenting and interpreting data using Python's visualization packages, allowing them to communicate their findings clearly and effectively through visualizations.

OPERATING SYSTEMS LABORATORY (Area : 1420.84 sq.m)

The course aims to provide students with a strong foundation in operating system concepts and practical skills. It begins by teaching the installation of Windows operating systems, enabling students to understand the setup process, system configuration, and troubleshooting techniques. Moving forward, students will gain familiarity with Unix commands and shell programming, which are essential for command-line operations and task automation. The course emphasizes key operating system functionalities by guiding students to implement various CPU scheduling algorithms, such as FCFS, SJF, Priority, and Round Robin, ensuring they grasp the principles of process scheduling. It also covers Deadlock Avoidance and Detection algorithms, equipping students to analyze and resolve resource allocation issues effectively. Memory management is another critical focus, where students will implement Page Replacement Algorithms like FIFO, LRU, and Optimal strategies, along with exploring various memory allocation methods to optimize system performance. Additionally, the course introduces students to file organization and allocation strategies, helping them understand techniques such as sequential, indexed, and linked allocation for efficient data management. By the end of the course, students will possess a practical and theoretical understanding of operating systems, preparing them for advanced technical challenges and real-world applications..

COURSE OUTCOMES:

At the end of this course, students will have gained a comprehensive understanding of operating system concepts and their practical applications. They will be able to define and implement essential UNIX commands, equipping them with the skills required for command-line operations and basic scripting tasks. Additionally, students will be capable of comparing the performance of various CPU scheduling algorithms, analyzing their efficiency in different scenarios. The course also enables students to compare and contrast various memory allocation methods, providing insights into their advantages and limitations in optimizing system performance. Furthermore, students will develop a clear understanding of file organization and file allocation strategies, which are crucial for effective data management and storage optimization. Lastly, students will be proficient in implementing various disk scheduling algorithms, allowing them to manage and optimize disk access efficiently. These skills collectively prepare students to address real-world challenges in operating system design and management.

DATABASE MANAGEMENT SYSTEMS LABORATORY (Area : 1420.84 sq.m)

This course is designed to provide students with a strong foundation in database management systems and their practical applications. Students will begin by learning and implementing essential SQL commands, enabling them to manipulate and manage data effectively. They will also gain expertise in constructing and utilizing nested and join queries to retrieve and analyze data from relational databases efficiently. The course focuses on understanding functions, procedures, and procedural extensions of databases, equipping students with the skills to create robust and dynamic database solutions. Additionally, students will explore the design and implementation of typical database applications, providing them with hands-on experience in solving real-world data management challenges. Moreover, the course introduces students to front-end tools for GUI-based application development, enabling them to integrate user-friendly interfaces with database systems. By the end of this course, students will possess the knowledge and skills to design, develop, and manage database-driven applications effectively.

COURSE OUTCOMES:

This course provides students with the essential skills and knowledge to work with diverse database technologies and applications. Students will learn to create databases while applying various key constraints, ensuring robust data modelling and maintaining data integrity. They will also develop the ability to construct both simple and complex SQL queries using DML (Data Manipulation Language) and DCL (Data Control Language) commands, enabling them to perform effective data retrieval, manipulation, and access control. The course emphasizes the use of advanced database features, such as stored procedures and triggers, which students will learn to implement and integrate into GUI-based application development for creating interactive and user-friendly database systems. Additionally, students will gain expertise in designing and validating XML databases using metadata like XML schemas, equipping them to handle data representation and exchange efficiently. Furthermore, the course introduces students to NoSQL databases, allowing them to create, manipulate, and manage data in non-relational database systems suitable for handling unstructured or semi-structured data. By the end of the course, students will possess a well-rounded understanding of both traditional and modern database technologies and their application in solving real-world problems.

Library Details Computer Science & Engineering

The CSE Library houses a comprehensive collection of books, journals, A/V resources and newsclippings on environment, science, technology and development, with special emphasis on South Asia and India. The Library is also used by external research scholars, NGOs, educational institutions, media, consultants and Corporations.

Library Details

Research Journals

The CSE Library subscribes to leading national and international journals, both Print and Online

Recent books and documents

View the latest books acquired by the Library, categorized by subject

News Clippings

Fully searchable and Digitized newsclippings from more than 80 leading national and international newspapers and newsmagazines are available

CD Rooms

CDs available with us provide significant information in digital format.These include yearbooks, statistics, maps, data on environmental development etc.

COMPUTER SCIENCE AND ENGINEERING

PROGRAM EDUCATIONAL OBJECTIVES (PEOs)

❖ To enable graduates to pursue higher education and research, or have a successful career in industries associated with Computer Science and Engineering, or as entrepreneurs.

❖ To ensure that graduates will have the ability and attitude to adapt to emerging technological changes.

PROGRAM SPECIFIC OUTCOMES (PSOs)

At the end of the program students will be able to

❖ Analyze, design and develop computing solutions by applying foundational concepts of Computer Science and Engineering.

❖ Apply software engineering principles and practices for developing quality software for scientific and business applications.

❖ Adapt to emerging Information and Communication Technologies (ICT) to innovate ideas and solutions to existing or novel problems.

PROGRAM OUTCOMES

PROGRAM OUTCOMES (POs)

❖ Engineering knowledge :Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

❖ Problem analysis :Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

❖ Design/development of solutions :Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for public health and safety, and the cultural, societal, and environmental considerations.

❖ Conduct investigations of complex problems :Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.

❖ Modern tool usage :Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.

❖ The engineer and society :Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to professional engineering practice.

❖ Environment and sustainability :Understand the impact of professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.

❖ Ethics :Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

❖ Individual and team work :Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

❖ Communication :Communicate effectively on complex engineering activities with the engineering community and with society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.

❖ Project management and finance :Demonstrate knowledge and understanding of the engineering and management principles and apply these to one's own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.

❖ Life-long learning :Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

Course Outcomes

COURSE OUTCOMES (POs)

• Course Outcome 2017
• Course Outcome 2021

R & D Cell Computer Science and Engineering

Sanctioned R & D Projects :