Placements @ SRIT

2021-22 Placements: DBS - 49(8.9 LPA), CTS - 181 (4(6.75 LPA), 18 (4.25 LPA), 159 (4.0 LPA)), Wipro - 239(3.5 LPA), Infor - 10 (6.5 LPA), Infosys- 43(3(6.5 LPA), 40 (3.6 LPA)), TCS - 119(Ninja - 115 (3.36 LPA) & Digital - 4 (7.0 LPA)), Capgemini - 39 (4.0 LPA), EPAM - 1(6.0 LPA),Astrazeneca - 1(5.56 LPA), Hitachi - 1(5.0 LPA), Accolite - 1(5.0 LPA), IBM - 36 (4.25 LPA), Hexaware - 17 ( 2 (5.0 LPA) & 15 (4.0 LPA)), Mindtree - 12 (4.0 LPA), HCL - 11(3.5 LPA) , KPIT - 5(4.0 LPA), Virtusa -1(4.0 LPA), Quest Global - 4(3.0 LPA), Zensar - 2(3.3 LPA)

2021-22 Placements: DBS - 49(8.9 LPA), CTS - 181 (4(6.75 LPA), 18 (4.25 LPA), 159 (4.0 LPA)), Wipro - 239(3.5 LPA), Infor - 10 (6.5 LPA), Infosys- 43(3(6.5 LPA), 40 (3.6 LPA)), TCS - 119(Ninja - 115 (3.36 LPA) & Digital - 4 (7.0 LPA)), Capgemini - 39 (4.0 LPA), EPAM - 1(6.0 LPA),Astrazeneca - 1(5.56 LPA), Hitachi - 1(5.0 LPA), Accolite - 1(5.0 LPA), IBM - 36 (4.25 LPA), Hexaware - 17 ( 2 (5.0 LPA) & 15 (4.0 LPA)), Mindtree - 12 (4.0 LPA), HCL - 11(3.5 LPA) , KPIT - 5(4.0 LPA), Virtusa -1(4.0 LPA), Quest Global - 4(3.0 LPA), Zensar - 2(3.3 LPA)

CSE - Data Science

Intro of CSE - DS Program

The B.Tech program in Data Science trains engineering graduates to be skilled Data Scientists. The emphasis is on core data science subjects along with the related computational mathematics, statistics, and computer science subjects. The Data Science program introduces students to various application domains like finance, business, and healthcare, to make optimal decisions.

Data Science is a unique multidisciplinary confluence of Computer Science, Mathematics, Statistics, and Management. SRIT, being a pioneer in the field of engineering education, offers this course as a full-time B.Tech program from the academic year 2020 under the department of Computer Science and Engineering  with an intake of 60, increased to 120 in 2021. The curriculum was designed thoughtfully to include Computer Science’s knowledge framework with a strong foundation of Data Science. The laboratory setup and the intellectual resources of the department will help the students to become competent data scientists.

20 k+
Students
150 +
Courses
2 k+
Teachers

PROGRAM OVERVIEW

Computer Science and Engineering ( Data Science ) Program Overview

VISION:

To evolve as a leading department by offering best comprehensive teaching and learning practices for  students to be self-competent technocrats with professional ethics and social responsibilities.

MISSION:

DM 1: Continuous enhancement of the teaching-learning practices to gain profound knowledge in theoretical & practical aspects of computer science applications.

DM 2: Administer training on emerging technologies and motivate the students to inculcate self-learning abilities, ethical values and social consciousness to become competent professionals.

DM 3: Perpetual elevation of Industry-Institute interactions to facilitate the students to work on real-time problems to serve the needs of the society.

An SRIT graduate in Computer Science & Engineering, after three to four years of graduation will:

PEO 1: Lead a successful professional career in IT / ITES industry / Government organizations with ethical values.

PEO 2: Become competent and responsible computer science professional with good communication skills and leadership qualities to respond and contribute significantly for the benefit of society at large. 

PEO 3: Engage in life-long learning, acquiring new and relevant professional competencies / higher academic qualifications.

PO’s & PSO’s

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.

Program Specific Outcomes

At the end of the B. Tech program in Computer Science and Engineering( Data Science), the graduate will be able to:

 

PSO1: Use the concepts and practical knowledge in analysis, design, implement and development of computing systems and applications to multi-disciplinary problems.

 

PSO2: Design information systems using standard statistical tools and techniques to analyze large data for visualization and interpretation.

 

PSO3: Expertise in developing relevant Data science models and working with extensive data sets required to meet the industry’s growing demand for data scientists and engineers.

 

  Achievements:

1Department of CSE Accredited by NBA in 2018.
2Department of CSE has been Permanently Affiliated by JNTUA in 2018.

COURSE STRUCTURE

Computer Science and Engineering ( Data Science ) Course Structure

E-CONTENT

Computer Science and Engineering Course E-CONTENT

FACULTY

Computer Science and Engineering ( Data Science )Faculty 

STUDENTS

Computer Science and Engineering ( Data Science ) Students