Dept. of Computer Science and Artificial Intelligence
The Department of Computer Science Engineering & Artificial Intelligence 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 Artificial Intelligence, 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 Engineering & Artificial Intelligence department with strong expertise in Theoretical Computer Science, Data Science, 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 Engineering 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 Engineering.
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 |
The B. Tech (Computer Science and Engineering & Artificial Intelligence) program was started in the year 2026 with an intake of 54 students.
| Course Title | Category | Credits | L | T | P |
|---|---|---|---|---|---|
| Computer Science and IT Fundamentals | Major-Core | 4 | 3 | 0 | 2 |
| Engineering Maths | Major-Core | 4 | 4 | 0 | 0 |
| Problem Solving and Programming in C | Major-Core | 4 | 3 | 0 | 2 |
| Python Programming | SEC-I | 3 | 2 | 0 | 2 |
| Basic Electronics | IDE-I | 3 | 3 | 0 | 0 |
| Communicative English | AEC-I | 2 | 2 | 0 | 0 |
| Course Title | Category | Credits | L | T | P |
|---|---|---|---|---|---|
| Linear Algebra for Engineers | Minor-Core | 4 | 3 | 0 | 2 |
| Introduction to OOPs Using Java | SEC-II | 4 | 3 | 1 | 0 |
| Discrete Mathematics | Major-Core | 4 | 3 | 1 | 0 |
| Probability and Statistics | Major-Core | 3 | 3 | 0 | 0 |
| Logic and Reasoning | AEC-II | 2 | 2 | 0 | 0 |
| Digital Electronics | IDE-II | 3 | 3 | 0 | 0 |
| 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 |
| Optimization Techniques for AI | Minor-Core | 4 | 3 | 1 | 0 |
| AEC – III | AEC | 2 | 2 | 0 | 0 |
| IDE – III | IDE | 3 | 3 | 0 | 0 |
| 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 |
| VAC – II | VAC | 2 | 2 | 0 | 0 |
| AEC – IV | AEC | 2 | 2 | 0 | 0 |
| Summer Internship Project (SIP) | SIP | 2 | 2 | 0 | 0 |
| Course Title | Category | Credits | L | T | P |
|---|---|---|---|---|---|
| Introduction to Deep Learning and Generative AI | Minor-Core | 4 | 3 | 0 | 2 |
| Database Management Systems | Major-Core | 4 | 3 | 0 | 2 |
| Software Engineering | Major-Core | 4 | 3 | 0 | 2 |
| Basics of Cloud Computing | Major-Core | 4 | 3 | 1 | 0 |
| Introduction to Reinforcement Learning | Minor-Core | 4 | 3 | 1 | 0 |
| VAC – III | VAC | 2 | 2 | 0 | 0 |
| Course Title | Category | Credits | L | T | P |
|---|---|---|---|---|---|
| Data Mining | Major-Core | 4 | 3 | 1 | 0 |
| Introduction to Information Security | Major-Core | 4 | 3 | 1 | 0 |
| Introduction to DevOps | Major-Core | 4 | 3 | 1 | 0 |
| Major Elective – I | Major-Elective | 4 | 4 | 0 | 0 |
| Minor Elective – I | Minor-Elective | 4 | 4 | 0 | 0 |
| Course Title | Category | Credits | L | T | P |
|---|---|---|---|---|---|
| Big Data Analytics | Minor-Core | 4 | 3 | 1 | 0 |
| Dissertation – I | Major | 4 | – | – | – |
| Major Elective – II | Major-Elective | 4 | 4 | 0 | 0 |
| Minor Elective – II | Minor-Elective | 4 | 4 | 0 | 0 |
| SEC – II | SEC | 3 | 3 | 0 | 0 |
| Course Title | Category | Credits | L | T | P |
|---|---|---|---|---|---|
| Minor Elective – III | Minor | 4 | 4 | 0 | 0 |
| Dissertation – II | Major | 12 | – | – | – |
* Note: Course Curriculum is Dynamic and Subject to change as per requirements.
To be eligible for a B.Tech in Computer Science and Engineering & Artificial Intelligence CSE&AI, 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).
B.Tech Admission Details
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.Tech CSE & AI | 60 | 54 |
An Extension Lecture by Associate Professor Department of Computer Science Engineering National Institute of Technology Warangal.