Dept. of Computer Science and Data Analytics

The Department of  Computer Science and Data Analytics is committed to advancing computing through innovative research, transformative technologies, and excellence in education. We strive to develop secure, scalable, sustainable, accessible, and socially responsible solutions that address emerging challenges in industry and society.

With a strong focus on Data Analytics, Quantum Computing, and other emerging technologies, the department fosters interdisciplinary research, industry–academia collaboration, and knowledge-driven innovation. We nurture a culture of curiosity, creativity, and entrepreneurship, empowering students and researchers to transform ideas into impactful solutions and contribute meaningfully to a technologically advanced and sustainable future.

A premier Computer Science and Data Analytics department with strong expertise in Theoretical Computer Science, Data Science, Machine Learning and Computer Systems.

Comprehensive and well-structured curriculum that balances strong theoretical foundations with hands-on practical skills.

State-of-the-art laboratories and research infrastructure equipped to facilitate learning and keep pace with emerging technologies.

Dynamic research environment fostering interdisciplinary collaboration, innovation, and the development of impactful solutions.

Strong encouragement for entrepreneurship and innovation, supporting students and researchers in transforming ideas into successful startups.

Robust industry engagement through internships, expert guest lectures, industry-sponsored projects, and collaborative initiatives.

 

 

“To attain global excellence and recognition in  Computer Science and Data Analytics education, research, and professional training by fostering innovation, advancing knowledge, and addressing the evolving needs of industry and society.”

 

 

 

 

 

 

 

 

 

 

 

 

 

 

To impart quality education through a contemporary, industry-aligned curriculum that equips students with the knowledge, skills, and competencies required to address the evolving challenges of the software industry.

To establish state-of-the-art research infrastructure and foster a culture of innovation that facilitates knowledge creation, technological advancement, and impactful research in emerging and thrust areas of  Computer Science and Data Analytics.

To forge strategic collaborations with globally renowned organizations and strengthen industry–academia partnerships, enabling knowledge exchange, collaborative research, skill development, and mutual growth.

 

 

 

 

 

 

 

 

 

 

 

S.No. Photo Faculty Name Designation Specialization View Profile
01
Dr. Enugala Vishnu Priya Reddy
Ph.D. in Computer Science
Assistant Professor (Guest Faculty) Deep Learning, Machine Learning, Internet of Things View Profile
02
Shri. Ramanakar Mogurampelli
M. Tech (CSE) – JNTU, Hyderabad
Assistant Professor (Guest Faculty) Web Application Development | Problem Solving Methodologies View Profile
03
Ms. Rajini Thanam
M.Tech. (CSE)
Assistant Professor (Guest Faculty) Full Stack Development, Web Technologies View Profile

B.Sc. (Hons.) Computer Science and Data Analytics

The B.Sc. (Hons.) Computer Science and Data Analytics program was started in the year 2026 with an intake of 09 students.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Semester I 24 Credits
Course Title Category Credits L T P
Computer Science and IT Fundamentals Major-Core 4 3 0 2
Engineering Maths Major-Core 4 3 1 0
Problem Solving and Programming in C Major-Core 4 3 0 2
Digital Twins IDE-I 3 3 0 0
Communicative English AEC-I 2 2 0 0
Python Programming SEC-I 3 3 0 2
Environmental Studies VAC-I 2 0 0 0
Bhasha AEC-II 2 2 0 0
Semester II 22 Credits
Course Title Category Credits L T P
Introduction to OOPs Using Java Major-Core 4 3 0 2
Discrete Maths Major-Core 4 3 1 0
Probability and Statistics Major-Core 4 3 1 0
Internet of Things IDE-II 3 3 0 0
Logical And Reasoning AEC-III 2 2 0 0
Data Visualization SEC-II 3 3 0 0
Universal Human Values VAC-II 2 2 0 0
Semester III 20 Credits
Course Title Category Credits L T P
Fundamentals of Data Structures Major-Core 4 3 0 2
Computer Organization and Architecture Major-Core 4 3 1 0
Fundamentals of AI and Applications Minor-Core 4 3 1 0
IDE IDE-III 3 3 1 0
Building Mathematical Ability and Financial Literacy AEC-IV 2 2 0 0
Web Application Development SEC-III 3 3 0 0
Semester IV 20 Credits
Course Title Category Credits L T P
Operating Systems Major-Core 4 3 0 2
Fundamentals of Data Science using Python Minor-Core 4 3 0 2
Design and Analysis of Algorithms Major-Core 4 3 1 0
Introduction to Machine Learning Minor-Core 4 3 0 2
Climate Change VAC-III 2 2 0 0
Summer Internship Project SIP 2 2 0 0
Semester V 20 Credits
Course Title Category Credits L T P
Database Management Systems Major-Core 4 3 0 2
Introduction to Deep Learning and Generative AI Minor-Core 4 3 0 2
Software Engineering Major-Core 4 3 0 2
Basics of Cloud Computing Major-Core 4 3 1 0
Computer Networks Minor-Core 4 3 1 0
Semester VI 20 Credits
Course Title Category Credits L T P
Data Mining Minor-Core 4 3 1 0
Introduction to DevOps Major-Core 4 3 1 0
Introduction to Information Security Major-Core 4 3 1 0
Image Processing Minor Elective – I 4 4 0 0
Dissertation – I / Major Elective Research Project / Major Elective 4 4 0 0
Semester VII 20 Credits
Course Title Category Credits L T P
Natural Language Processing Major-Core 4 3 1 0
Big Data Analytics Minor-Core 4 3 1 0
Introduction to Reinforcement Learning Minor Elective-II 4 4 0 0
Mobile Application Development Major Elective-II 4 4 0 0
Distributed systems Major Elective-III 4 4 0 0
Semester VIII 16 Credits
Course Title Category Credits L T P
Quantum Computing Major Elective-IV 4 4 0 0
Dissertation – II Research Project 12 – – –

* Note: Course Curriculum is Dynamic and Subject to change as per the requirements.

To be eligible for a B.Sc. (Hons.) Computer Science and Data Analytics, you must complete your

  • 10+2 education from a recognized board with Physics and Mathematics as compulsory subjects, alongside Chemistry and a minimum of 60 % aggregate marks (55% for SC/ST/PwBD candidates).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Admission to all undergraduate programmes in SSCTU will be made through a Joint Entrance Examination, Common University Entrance Test, University Entrance Test.

 

 

 

 

 

 

 

 

 

 

 

 

 

E-RESOURCES

Swayam NPTEL

S.No Program Sanction Intake
1. B.Sc. (Hons.) Computer Science and Data Analytics 25 09

 An Extension Lecture by Associate Professor Department of Computer Science Engineering National Institute of Technology Warangal.