• EAMCET/ECET/ICET CODE: VMEG

Computer Science and Engineering (Data Science)

Where Computer Science Meets the Power of Data

Overview

The Department of Computer Science & Engineering (Data Science) is dedicated to equip students with the skills required to manage and analyze large volumes of data. The program integrates foundational components including analytics, knowledge extraction, and data visualization to ensure accurate and efficient data management. The curriculum emphasizes experiential learning through laboratory practice and realworld problemsolving using computational techniques and technologies, preparing students for careers as Software Engineers, Data Scientists, Data Analysts, and Data Engineers etc. In addition, the department actively encourages students to pursue global certifications and industry internships, and motivate students to participate in Hackathons, global coding events, workshops, seminars, conferences etc., thereby strengthening the bridge between academic learning and professional practice.

The Department of Computer Science and Engineering (Data Science) was established in 2023 with a sanctioned intake of 180. The Professor & HOD, Dr. Shanthi Makka has a vast academic experience spanning nearly 21 years. The department has signed MoUs with a few MNCs to offer real time exposure among the students.

Academic Programmes Offered

  • B.Tech in Computer Science and Engineering (Data Science)  
In addition to the core programme, the department offers Minors in Data Science and Honors in CSE (Data Science), designed to provide advanced exposure to specialized topics and industry relevant skills. All programmes are affiliated to Jawaharlal Nehru Technological University, Hyderabad (JNTUH) and are structured in line with the AICTE model curriculum and evolving industry requirements.

Head of the Department

Dr. Shanthi Makka

The curriculum emphasizes data analytics, machine learning, big data, cloud computing, and ethical AI practices, ensuring that students are well prepared for higher studies, competitive examinations, and professional careers in cutting edge domains.

The Department of CSE–Data Science offers state of the art laboratories that serve as hubs for technology learning, innovative projects, and experiential education. With specialized labs in Cloud Computing, Deep Learning, Data Analytics, Core Technologies, Object Oriented Programming, Big Data, and Soft Computing, students gain hands- on exposure to cutting edge tools and platforms. These facilities empower learners to transform ideas into impactful projects, foster research guided by faculty mentors, and create an environment where innovation and practical learning go hand in hand.

Strong industry collaboration is nurtured through technical workshops, industrial internships, guest lectures, certification programs, and collaborative student projects. Student centric initiatives such as mentoring systems, remedial coaching, bridge courses, and value added programs further enrich the academic environment. Professional societies like IEEE, ISTE, ACM and Data Science Clubs actively contribute to technical exposure and skill development.

Backed by highly qualified faculty and a dynamic team of young innovators, the department maintains a legacy of quality education, innovation, and social responsibility. Through its comprehensive academic ecosystem, CSE–Data Science continues to shape ethical, competent, and future ready engineers equipped to lead in a technology driven world.

Vision

To be an epicentre of excellence in education by offering cutting-edge technologies, research, and product-based opportunities for the students and make them to succeed in global professional competitions with an attitude of core knowledge, entrepreneurial skills, ethical values, and social concern.

Mission

  • Impart quality technical Education with State-of-the-art laboratories, Analytical and Core. Technical Skills with International standards by qualified and experienced faculty.
  • Prepare for Global professional competitions and examinations for higher studies/Employment in product-based companies. 
  • Develop professional attitude, Research aptitude, Critical Reasoning, Problem-solving skills, and technical consultancy by providing training in cutting-edge technologies.
  • Endorse and nurture the knowledge, Life-long learning, Entrepreneurial practices, ethical values, and social concern.

Strengths of the Department

Core Technical Competency in Data Science and Computing:

Enhance students’ expertise in programming, data structures, database systems, statistical analysis, data science methodologies, big data analytics, and cloud computing through intensive laboratory practice and hands-on workshops using Python, R, SQL, TensorFlow, PyTorch, Power BI, Tableau, Hadoop, and Spark.

Multidisciplinary and Industry-Relevant Projects:

Encourage interdisciplinary project development in collaboration with Electronics, Mechanical, Biotechnology, Management, and Healthcare departments to address real-world challenges in smart systems, predictive analytics, automation, fintech, and healthcare analytics.

Industry Collaboration and Innovation Infrastructure:

Build a strong industry-linked ecosystem through Centres of Excellence in Data Analytics, Cyber Security, and Cloud Computing. Strengthen partnerships with leading IT organizations and technology firms to support consultancy, live projects, skill development programs, and technology-driven innovation.

Internship, Placement, and Industry Interaction

Develop a strong internship-to-placement pipeline by partnering with IT industries, data-driven enterprises, and start-ups. Organize industry expert talks, technical workshops, coding bootcamps, hackathons, and collaborative certification programs to enhance employability and industry readiness.

Upgradation of Curriculum with Emerging Technologies

Continuously integrate cutting-edge domains such as Generative AI, Deep Learning, Data Engineering, MLOps, Blockchain, IoT Analytics, and Responsible AI into the curriculum, ensuring alignment with global industry standards and evolving technological trends.

Research, Innovation, and Entrepreneurship

Promote high-quality publications, funded projects, patents, and faculty–student collaborative research while fostering an entrepreneurial mindset through incubation support, innovation cells, start-up mentoring, and technology commercialization initiatives.