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SCHOOL OF COMPUTER SCIENCE & ENGINEERING

The School of Computer Science is distinguished for its pioneering research and provision of world-class education. We attract outstanding students and esteemed faculty members, ensuring the department remains at the forefront of international-level training and research.

Our department offers high-standard computing facilities to our students, promoting a robust academic environment. Additionally, we foster strong industry-department collaborations, identifying mutual areas of interest and engaging in research projects and consultancy services.

Our research encompasses various domains, including systems, software, networking, databases, security, and the foundations of computer science. We also delve into advanced areas such as artificial intelligence, robotics, and scientific computing. Beyond basic research, the department is committed to interdisciplinary applications that drive fundamental research, thereby contributing significantly to the field of computer science engineering.

VALUE ADDED COURSES

C & C++

JAVA

PYTHON

PHP

PROGRAMME OVERVIEWS

Programme Educational Objectives (PEO)

PEO.1 Can effectively use the English language to articulate ideas both in oral and written communication.
PEO.2 Able to contribute to multi-disciplinary teams for the achievement of collective goals.

PEO.3 Demonstrate technical competence and proficiency in computer science and engineering principles, tools, and techniques.
PEO.4 Pursue a successful career in computer science and engineering or related fields.

 

Programme Outcomes (PO)

PO-1 Engineering knowledge : Apply the knowledge of mathematics, science, engineering fundamentals, and an
engineering specialization to the solution of complex engineering problems.
PO-2 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.
PO-3 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 the public health and safety, and the cultural, societal, and environmental considerations.
PO-4 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.
PO-5 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
PO-6 The engineer and society : Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice
PO-7 Environment and sustainability : Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
PO-8 Ethics  :Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

PO-9 Individual and team work : Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
PO-10 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.
PO-11 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.
PO-12 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.

Programme Highlights (PH)

● Core Computer Science Foundation: The program begins with a strong foundation in core computer science & Engineering subjects, including algorithms, data structures, computer organization & architecture and programming languages.

● Specialization Courses: Specialized courses in Artificial Intelligence (AI) and Machine Learning (ML) form a significant part of the curriculum. These courses cover topics such as neural networks, deep learning, natural language processing and computer vision.

● Mathematics and Statistics: As AI and machine learning heavily rely on mathematical and statistical concepts, the program includes courses in linear algebra, probability, statistics, and calculus to provide a solid mathematical foundation.

● Practical Implementation: Emphasis on practical implementation through hands-on projects, labs, and real-world case studies. Students are required to work on AI and ML projects to gain practical experience.

● Industry-Relevant Tools and Technologies: Exposure to industry-relevant tools and technologies used in AI and machine learning, such as TensorFlow, PyTorch, scikit-learn, and others.

● Capstone Projects: Culmination projects or capstone projects where students apply their knowledge and skills to solve real-world problems. This may involve developing AI-based applications, implementing machine learning models, or working on research projects.

● Internships and Industry Collaboration: Opportunities for internships and collaboration with industries, research labs, or AI/ML-focused companies to gain hands-on experience and understand industry practices.

● Guest Lectures and Workshops: Regular guest lectures by industry experts and researchers in the field of AI and machine learning to keep students updated on the latest advancements and industry trends.

● Soft Skills Development: Besides technical skills, the program may focus on developing soft skills such as communication, problem-solving, and teamwork, which are essential for success in any professional setting.

● Research Opportunities: For students interested in research, the program may provide opportunities to engage in AI and machine learning research projects, contributing to the academic community.

● Career Guidance and Placement Support: Assistance with career guidance, job placement, and networking opportunities within the AI and machine learning industry.

● Continuous Learning: Given the rapid advancements in AI and machine learning, programs often encourage a culture of continuous learning and adaptation to emerging technologies.

LAboratories

Scrollable 5-Column Table
S.N. Name of Laboratories In-Charge System Software
1. Artificial Intelligence Lab/ Computer Programming Lab Mr. Shafiqual Islam Open Source
2. Cloud Computing Lab/Multimedia & Web Technologies Lab Mr. Aakash Open Source
3. Software Engineering Lab/ Java Programming Lab Mr. Nijamuddin Open Source
4. Database Management Systems Lab/ Compiler Design Lab Mrs. Shreya Open Source
5. Data Structure Using C Lab Mr. Aslam Khan Open Source
6. Computer Network Lab/Operating Systems Lab Mr. Aakash Open Source
7. English Communication Lab/Office Automation Mrs. Swati Open Source
8. Central Research Lab Mr. Hemant singh Open Source
9. Software Development Lab Mr. Shafiqual Islam Open Source

Course Offered ( Computer Science and Engineering )

B.Tech. (CSE)
Eligibility

•Candidates must have earned at least 50% on their 10+2 exam from an accredited board in any stream (ideally science).
•For Kashmiri Migrants (KM) relaxation in cut-off percentage up to 10% subject to minimum eligibility requirement.
•Diploma Examination passed with at least 45% marks (40% reserve category) in aggregate in any Branch of Engineering and Technology., Diploma in Engineering & Technology ( 3 Years )

B.Tech. (H) CSE AI & ML
Eligibility

•Candidates must have earned at least 50% on their 10+2 exam from an accredited board in any stream (ideally science).
•For Kashmiri Migrants (KM) relaxation in cut-off percentage up to 10% subject to minimum eligibility requirement.

B.Tech. (H) CSE Cyber Security
Eligibility

•Candidates must have earned at least 50% on their 10+2 exam from an accredited board in any stream (ideally science).
•For Kashmiri Migrants (KM) relaxation in cut-off percentage up to 10% subject to minimum eligibility requirement.

B.Tech. (H) CSE FWD
Eligibility

•Candidates must have earned at least 50% on their 10+2 exam from an accredited board in any stream (ideally science).
•For Kashmiri Migrants (KM) relaxation in cut-off percentage up to 10% subject to minimum eligibility requirement.

B.Tech. (H) Data Analysis
Eligibility

•Candidates must have earned at least 50% on their 10+2 exam from an accredited board in any stream (ideally science).
•For Kashmiri Migrants (KM) relaxation in cut-off percentage up to 10% subject to minimum eligibility requirement.

M.Tech. CSE
Eligibility

c

Ph.D. CSE
Eligibility

•A Master's degree or a professional degree equivalent to the Master’s degree, with at least 55% marks in aggregate or its equivalent grade ‘B’ on the UGC 7-point scale. Degrees from recognized foreign institutions are also acceptable.
•Candidates must qualify in the entrance test conducted by the university with a minimum of 50% marks.

Courses Offered ( Computer Application )

BCA Hons.
Eligibility

The candidate must have passed with 50% minimum marks in Senior Secondary Certificate Examination (10+2 Standard) from any recognized Board

BCA With FSWD
Eligibility

The candidate must have passed with 50% minimum marks in Senior Secondary Certificate Examination (10+2 Standard) from any recognized Board

BCA With Cyber Security
Eligibility

The candidate must have passed with 50% minimum marks in Senior Secondary Certificate Examination (10+2 Standard) from any recognized Board

BCA With Data Science
Eligibility

The candidate must have passed with 50% minimum marks in Senior Secondary Certificate Examination (10+2 Standard) from any recognized Board

MCA
Eligibility

The Candidate must pass BCA with 50% marks or any Graduation with Math with 50% marks and Math at Senior Secondary Certificate Examination (10+2 Standard) level.

Ph.D. Computer Application
Eligibility

The candidate must have passed with 50% minimum marks in Senior Secondary Certificate Examination (10+2 Standard) from any recognized Board

Faculty

Dr. Anil Kumar Lamba (Prof. & Head) Professor
Dr. Bhawna Singla Professor
Dr. Poonam Associate Professor
Dr. Suresh Kumar Associate Professor
Dr. Ezaj Sabir Lone Assistant Professor
Dr. Geeta Assistant Professor
Dr. Parmjeet Kaur Assistant Professor
Mr. Ashish Singh Yadav Assistant Professor
Mr. Mohammad Aslam Assistant Professor
Mr. Kapil Saini Assistant Professor
Ms. Shreya Sharma Assistant Professor
Mr. Hemant Singh Assistant Professor
Ms. Aarti Assistant Professor
    Mr. Nijamuddin Assistant Professor
    Ms. Prachi Miglani Assistant Professor
    Mr. Ronak Duggar Assistant Professor
    Ms. Sukhwinder Assistant Professor
    Ms. Chetna Assistant Professor
    Mr. Deepak Bhardwaj Assistant Professor
    Ms. Swati Ambasta Assistant Professor
    Ms. Prachi Sharma Assistant Professor
    Ms. Neha Bansal Assistant Professor
    Ms. Priyanka Chopra Assistant Professor
    Ms. Rakhi Chauhan Assistant Professor
    Ms. Anshu Assistant Professor
    Mr. Krishnanand Sharma Assistant Professor

      FACILITIES

      Computer Programming & Graphics Lab

      Object-oriented Programming Lab(OOPS Lab)

      Language Processor Lab

      Network & OS Lab

      Internet & Project Lab

      Language Lab

      PG Lab

      Computer Lab 

      Code Quotient ( Lab)

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