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Program Overview


M.Tech in Computer Science and Engineering (CSE) with a specialization in Artificial Intelligence and Machine Learning program has been designed for students with sufficient background in computer science and engineering to develop into adept professionals. M.Tech in CSE is a graduate degree that builds skill and knowledge in advanced and current topics of computer science with a focus on AI topics. The degree is suitable for students with a bachelor’s degree in a computing-related field as well as students who want to demonstrate computer science expertise in addition to a degree in another field.

The curriculum has been designed to prepare students for highly prolific careers in the industry. Some of the job profiles include Application Analyst, Data Scientist, Data Analyst, Database Administrator, Information Systems Manager, IT Consultant, Multimedia Analyst.


Semester I
Course Code Type Course Title L T P Cr.
18CS601 FC Foundations of Computer Science Data Structures Algorithms 3 0 1 4
18MA611 FC Mathematics for Computer Science Linear Algebra Probability and Statistics 3 0 1 4
* SC Soft Core – I 3 0 1 4
* SC Soft Core – II 3 0 1 4
* SC Soft Core – III 3 0 1 4
18HU601 HU Amrita Values Program* * * * P/F
18HU602 HU Career Competency I* * * * P/F
*Non-Credit courses
Semester II
Course Code Type Course Title L T P Cr.
* SC Soft Core – IV 3 0 1 4
* SC Soft Core – V 3 0 1 4
* Elective Elective – I 3 0 0 3
* Elective Elective–II 3 0 0 3
* Elective Elective–III 3 0 0 3
18RM600 SC Research Methodology 2 0 0 2
18HU603 HU Career Competency II 0 0 2 1
Semester III
Course Code Type Course Title L T P Cr.
* Elective Elective –IV 3 0 0 3
* Elective Elective –V 3 0 0 3
18CS798 * Dissertation * * * 8
Semester IV
Course Code Type Course Title L T P Cr.
18CS799 * Dissertation * * * 12
Soft Core
Course Code Course Title L T P Cr.
18CS621 Foundations of Data Science 3 0 1 4
18CS622 Digital Signal and Image Processing 3 0 1 4
18CS623 Cloud and IoT 3 0 1 4
18CS624 Machine Learning 3 0 1 4
18CS625 Modeling and Simulation 3 0 1 4
18CS626 Computational Methods for Optimization 3 0 1 4
18CS627 Parallel and Distributed Data Management 3 0 1 4
18CS628 Computational Intelligence 3 0 1 4
18CS629 Modern Computer Architecture 3 0 1 4
18CS630 Deep Learning 3 0 1 4
18CS631 Advanced Algorithms and Analysis 3 0 1 4
Students have to select any five soft core subjects from the list given above.
Subject Core
Course Code Course Title L T P Cr.
18RM600 Research Methodology 2 0 0 2
Elective(Machine Learning and Data Science Stream)
Course Code Course L T P Cr
18CS701 Machine Learning for Big Data 3 0 0 3
18CS702 Applications of Machine Learning 3 0 0 3
18CS703 Statistical Learning Theory 3 0 0 3
18CS704 Natural Language Processing 3 0 0 3
18CS705 Information Retrieval 3 0 0 3
18CS706 Data Mining and Business Intelligence 3 0 0 3
18CS707 Semantic Web 3 0 0 3
18CS708 Data Visualization 3 0 0 3
18CS709 Computational Statistics and Inference Theory 3 0 0 3
18CS710 Networks and Spectral Graph Theory 3 0 0 3
Elective (High Performance Computing Stream)
Course Code Course L T P Cr
18CS731 Parallel and Distributed Computing 3 0 0 3
18CS732 GPU Architecture and Programming 3 0 0 3
18CS733 Reconfigurable Computing 3 0 0 3
18CS734 Data Intensive Computing 3 0 0 3
18CS735 Fault Tolerant Systems 3 0 0 3
18CS736 Computer Solutions of Linear Algebraic Systems 3 0 0 3
Elective (Live-in-Labs)
18CS737 Live-in-Labs * * * 3
Students can do Live-in-Labs course in lieu of an elective from II Semester or III Semester.
Elective (Networks and IoT Stream)
Course Code Course L T P Cr
18CS721 Sensor Networks and IoT 3 0 0 3
18CS722 Predictive Analytics for Internet of Things 3 0 0 3
18CS723 Wireless Sensor Networks 3 0 0 3
18CS724 Wireless and Mobile Networks 3 0 0 3
18CS725 Pervasive Computing 3 0 0 3
18CS726 IoT Protocols and Architecture 3 0 0 3
Elective (Computer Vision Stream)
Course Code Course L T P Cr
18CS711 Video Analytics 3 0 0 3
18CS712 Medical Signal Processing 3 0 0 3
18CS713 Content Based Image and Video Retrieval 3 0 0 3
18CS714 Pattern Recognition 3 0 0 3
18CS715 3D Modeling for Visualization 3 0 0 3
18CS716 Computer Vision 3 0 0 3
18CS717 Visual Sensor Networks 3 0 0 3
18CS718 Image Analysis 3 0 0 3


Duration : Two years

Eligibility Criteria

B. E. / B. Tech. (Computer Science, Information Technology, Electronics and Communication, Electrical and Electronics, Electronics and Instrumentation, Information Science), MCA, M. Sc. Computer Science, M. Sc. IT, M. Sc. Software Engineering

Program Overview

Program Educational Objectives (PEO)
  • Apply knowledge acquired and become prolific professionals in industry or research
  • Pursue lifelong learning in emerging computing paradigms to provide solutions for real world problems
  • Demonstrate high regard for professionalism, integrity and respect values in diverse culture, and have a concern for society and environment
Program Outcomes (PO)
  • Hone the knowledge-base and skillsets of computer science professionals in areas of research, development and innovation
  • Create people with technical competency in computer science to design and develop solutions for societal benefits
  • Provide opportunities to gather in-depth knowledge along with practical hands-on experience in Computer Science core areas as well as in subjects related to Artificial Intelligence and Machine Learning.
  • Develop professionals with high competency in recent and futuristic technologies
  • Facilitate students to demonstrate knowledge by good communication skills in terms of reports and publications
Program Highlights
  • Placement and internships in core companies like Cisco, IBM, Cerner, L & T Technology, Inside View, ThermoFisher Scientific, Bosch ,KPIT Technologies,, TCS-TRDDC, Lucid Imaging, Samsung, Tata Consultancy Services, Kodak ,Canon and organizations like ISRO, NPOL, Oracle, Zoho Corpoation etc
  • Opportunities for student exchange in premiere universities like KTH Sweden, Politecnico Di Milano– Italy, University of New Mexico-USA, RWTH – Aachen University Germany, University of York, University of Turku-Finland, Vrije University ,and other universities USA and Europe etc for a semester or a year.
  • Opportunities to work on live projects for Government of India and Industry, Research as a part of the curriculum resulting in scholarly publications and collaborative projects with Amrita Institute of Medical Sciences (Multi Specialty Hospital), Kochi
  • Innovative course structure enabling specialization in Big Data and Computational Intelligence, Networking, and High Performance Computing with specialized Mathematics Courses
  • Advanced courses in recent thrust areas like Enterprise Architecture, Parallel and Distributed Computing, Foundations of Data Science, Machine Learning for Big Data
  • Research as part of curriculum resulting in scholarly publications
  • Courses with focus on lab components providing expertise in technologies like Hadoop, R Programming, Data Analytics Tools
  • Regular workshops conducted by industry and academia: Workshop by TCS on Hadoop and Mapreduce, NS2 Workshop with sessions from experts from academia
MTech Program Fee 2022 (Per Semester)


Thrust Areas
  • Biometrics

  • Computer Vision

  • Signal Processing

  • Data Analytics

  • Evolutionary Computing

  • Next Gen Computing

  • Predictive Analytics & IoT

  • Human Computer Interaction

Smart Climate Monitoring for Large Scale Buildings

Company: Robert Bosch Engineering and Business Solutions Private Limited, Coimbatore

Air conditioning systems in large scale buildings contribute a major portion of the energy requirements. A centralized temperature monitoring system would result in the enhancement of air conditioning services in large scale buildings. Here we develop a centralized temperature monitoring scheme suitable for office environments. Wireless sensors are placed inside a compartmentalized office area, which collects the surrounding temperature data and sends it to the cloud. The application in the cloud will receive this data, store the data and present this data graphically to the end user. In order to reduce the redundant data as well as for making the sensor network energy efficient, we carry out a data analytics algorithm to identify the redundant sensors in the network based on data correlation.

Hybrid Localization Algorithm for Indoor Asset Tracking

Main focus of this research work is to design an efficient and scalable RFID based hybrid indoor localization algorithm that operates over long-range RFID readers. The major objectives of this work are to design an approach that is extensible to large environments with minimal calibration and to provide high accuracy. Asset tracking is important for resource utilization and recovery. It is a service that helps locate objects instantly by providing easy access of item locations without much manual effort. We design a hybrid localization algorithm to accurately estimate the position of an object within a finite indoor space. Our approach uses power level and signal strength parameters which are readily available without the requirement of additional hardware. Furthermore, our algorithm applies intelligent region elimination techniques, thereby avoiding the use of heavy calibration and computationally complex algorithms.

Securing Image Posts in Social Networking

The most unbeatable technology, Internet brings to people for communication is social networks. With the exponential growth of users in internet, there is an equivalent growth among internet users to regularly visit social websites for linking with their friends, sharing thoughts, photos, videos and even discuss about their day today activities. The fact these social networks are available to all the users for free, leads to various types of security issues. Image security has been a topic of research over decades. Enhancements to individual techniques and combinations proposed till date have offered different levels of security assurances. This work aim to present a technique for secure sharing of image posts in social network. The significant feature of the scheme lies in the selection of security technique based on image content, evaluation of peers with whom the image can be shared based on text classification, transliteration and tone analysis. The proposed scheme a cost effective solution as it does not require any additional hardware. The utility of the model is demonstrated by mapping the scheme with Facebook and analyzing its performance through simulation.

Facilities at a glance

  • Computer laboratory
  • Analytics Laboratory
  • Cognizant  lab
  • Wireless Sensor Lab
  • Application Lab
Amrita Vishwa Vidyapeetham, Amritapuri Campus, Kollam, Kerala

The technical excellence of the campus has made it a learning hub for students from all around the globe.


At Amrita, companies vie with each other to be the early birds for hiring,
thanks to the quality of students, past and present.




7.5 LPA


25 LPA



Deepak S.,
M. Tech. in Computer Science & Engineering (2017 – 19) | RSA, Dell EMC

The Computer Science MTech program in Amrita, with an emphasis on Machine Learning, was an amazing experience for me. It was refreshing to be part of an institution where you are graded based on how much you have understood rather than how much you have blindly memorized. The support and guidance I have received from the faculty were unparalleled. The encouragement to pursue genuine research is something that you don’t see often in other institutes. Opportunities such as dual degree and internships are exceptional and now that I have completed my course, I’m extremely glad that I chose to do my masters here.”

Arya Vijayan,
M. Tech. Computer Science and Engineering (2017-2019) | Dell EMC

MTech course in Computer Science at Amritapuri was based on the latest technologies from the industry covering all the major aspects. Focus was on individual employability skills, personal growth and development. My learning at Amrita truly made me grow both professionally and personally in my life. Through campus placement I got placed as an intern in DELL. I was also offered a permanent job in DELL after my internship completion. I am grateful to all my faculties and Amrita University for giving me such a big platform to develop my skills.”

Nellissery Cheryl Anto Jaya,
M. Tech. Computer Science and Engineering (2017-19) | Intel.

My internship at Intel was my first exposure to the corporate world. It was a wonderful learning experience. I honed my skills, interacted with different people and grew steadily in confidence. All this would not have been possible without the training that was imparted to us at Amrita. The constant guidance and support of my professors from Amrita paved the way for my success. Getting an offer from Intel as a software engineer was the icing on the cake.”

Krishnapriya S. ,
M. Tech. Computer Science and Engineering (2017-19) | GE Healthcare , SAP Labs

My 2 years of MTech at Amritapuri campus have been the defining periods of my life. During my second year of course work I got placed as an intern in GE Healthcare for 1 year which helped me in developing my technical and communication skills to a great extent. The close relation which Amrita University maintains with the industry has proved quite helpful in getting enough opportunities in terms of career. These two years of education in Amrita has shaped my thinking as a person, and I have extremely fond memories of my time here.”

Why Amrita


World University Rankings 2020


BRICS Rankings 2020


World University Rankings 2020


BRICS University Rankings 2020


India University Rankings 2021


Overall Rankings 2021
5th Best
University in India
Amrita Ranked No.1 in India Top 100 in The World
‘A++’ Grade

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