Admissions 2019

Ever since its inception on 7th October 1996, the Department of Computer Science and Engineering at Amrita Vishwa Vidyapeetham has been progressing towards excellence in the field of teaching and research. With a team of dedicated, experienced and qualified faculty members, the department has witnessed tremendous growth in academics and research. Major research areas include Image Processing, Multimedia Mining, Evolutionary Computing, Network Security and Wireless Networks. The department is progressing towards setting up of research laboratories and R & D centers.

The department offers B.Tech in Computer Science and Engineering. Regular interaction with software companies has helped the department in maintaining its syllabus abreast with technology and industrial standards. The rigorous learning environment has helped make students job-ready.

Program Educational Objectives (PEO):

  • Graduate will strive on a global platform to pursue their professional career in Computer Science and Engineering.
  • Graduate will contribute to product development as entrepreneurs in inter disciplinary fields of engineering and technology.
  • Graduate will demonstrate high regard for professionalism, integrity and respect values in diverse culture, and have a concern for society and environment.

Program Specific Outcomes (PSO):

  • Ability to design and engineer, innovative, optimal and elegant computing solutions to interdisciplinary problems using standard practices, tools and technologies.
  • Ability to learn emerging computing paradigms for research and innovation

Program Outcomes (PO):

  • Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  • 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.
  • Design and 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  • Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  • 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.
  • 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.
  • 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.

Curriculum based on recommendations of IEEE-ACM Joint task force on Computing Curricula

  • Right combination of courses from Humanities, Basic Sciences, Engineering, and  Computer Science
  • Mathematics courses to supplement the Computer Science requirements
  • Unique course in India on “Computational Thinking for Problem Solving” to aid in better logical thinking and  strengthen programming skills
  • Innovative use of tools and programming languages like Scratch, Raptor, Python and Visual Java
  • Industry case studies in courses like Software Engineering, Database Management Systems and Data Mining
  • Project based courses to integrate  the theoretical and practical aspects of computer science
  • Courses reflecting industry trends like Machine Learning and Data Mining, Cloud Computing, Service Oriented Architecture, OS for Smart Devices, Pervasive Computing, Big Data Analytics, etc
  • Open Labs for tech geeks and coders to take up competitive coding
  • Curriculum prepares the students towards internship at industries, Research labs and Exchange Programmes at International Universities
  • Support for publications, patenting and entrepreneurship
Communicative English Vector Calculus and Ordinary Differential Equations Humanities-1 Humanities II
Calculus and Matrix Algebra Chemistry/Physics Amrita Value Program-1 Amrita Value Program II
Computational Thinking and Problem Solving Computer Programming Discrete Mathematics Probability & Random Processes
Physics/Chemistry Computer Science Essentials Digital Systems Design and Analysis of Algorithms
Physics/Chemistry Lab Fundamentals of Electrical and Electronics Engineering Data Structures & Algorithms Introduction to Embedded Systems
Workshop A/Workshop B Chemistry Lab. / Physics Lab. Object Oriented Programming Operating Systems
Engg.Drawing- CAD Workshop B / Workshop A Digital systems lab Embedded Systems Lab
Cultural Education I Computer programming lab Data Structures lab Operating Systems Lab
  Cultural Education II Object Oriented Programming Lab Soft Skills I
Linear Algebra, Queuing theory  and Optimization Computer Networks Machine Learning and  Data Mining Elective VI
Environmental Studies Compiler Design Structure and Interpretation of Computer Programs Software project Management
Computer Organization and Architecture Software Engineering Project Based Elective Project Phase II
Theory of Computation Elective 2 Elective IV  
Database Management Systems Elective 3 Elective V  
Elective I Compiler Design Lab Machine Learning and  Data Mining Lab  
Computer Organization and Architecture Lab Computer Networks Lab Project Phase I  
Soft Skills II Open Lab Live in Labs  
Live in Lab Soft Skills III    


  • Computational Chemistry and Molecular Modelling
  • Spatiotemporal Data Management
  • Information Retrieval
  • Pattern Recognition
  • Information Coding Techniques
  • Software Quality Assurance
  • Semantic Web
  • Wireless Sensor Networks
  • Design Patterns
  • Computational Intelligence
  • Service Oriented Architecture
  • Real – Time Computing Systems
  • Scientific Computing
  • Cloud Computing and Services
  • Human Computer Interface
  • NAND2TETRIS: Building Computers from First Principles


  • Physics II
  • Advanced Databases
  • Parallel And Distributed Computing
  • Machine Learning
  • Embedded Programming
  • Natural Language Processing
  • Advanced Computer Architecture
  • Digital Watermarking
  • Computer Systems Engineering
  • Modelling and Simulation
  • Multimedia Databases
  • Distributed Embedded Systems
  • Biometrics
  • Wireless and Mobile Computing
  • Pervasive Computing


  • Advanced Database Management Systems
  • Principles Of Digital Image Processing
  • Enterprise Architecture
  • Wireless and Mobile Communication
  • Data Compression
  • Bioinformatics
  • Advanced Algorithms and Analysis
  • Intelligent Systems
  • Information Security
  • Cryptography
  • Computer Vision
  • Graph Theory and Combinatorics
  • Big Data Analytics
  • OS for Smart Devices (Android and IOS)
  • Intellectual Property


You can join this program at
Undergraduate (UG)
School of Engineering