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Application ends on 17 Oct 2021 - APPLY NOW
Application ends on 17 Oct 2021 - APPLY NOW
Application ends on 17 Oct 2021 - APPLY NOW
program overview

Prepare for a Career in M. Tech.

M.Tech in Computer Science & Engineering (Machine Learning) programme 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. 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 industry. Some of the job profiles include: Application analyst, Data Scientist, Data analyst, Database administrator, Information systems manager, IT consultant, Multimedia analyst.

About

M.Tech in Computer Science & Engineering (Machine Learning) programme 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. 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 industry. Some of the job profiles include: Application analyst, Data Scientist, Data analyst, Database administrator, Information systems manager, IT consultant, Multimedia analyst.

It is a reality that that computer technology has revolutionized the modern world. Technologies that we now use for granted – Internet, mobile phones, medical technology, would not be possible without the major developments made in the field of computing.

Curriculum

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
Total Credits 20
*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
Total Credits 20
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
Total Credits 14
Semester IV
Course Code Type Course Title L T P Cr.
18CS799 Dissertation 12
Total Credits 12
Total Credits: 66
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
Total Credits: 65
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

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

 

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.

 

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

 

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
Eligibility

Admission

Eligibility

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

Duration

Two years

Program Overview

Program Objectives
  • Hone the skill of computer science professionals in areas of research and innovation.
  • Develop experts with high professional competence in recent and futuristic technologies.
  • Create man power with technical competency in computer science to design and develop solutions for the societal problems.
  • 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 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)
  • Ability to independently carry out research investigation and development work to solve practical problems
  • Ability to write and present a substantial technical report/document
  • Students should be able to demonstrate a degree of mastery over the area
  • Ability to design and develop computing solutions using emerging computing paradigms to interdisciplinary problems following standard practices, tools and technologies
  • Ability to demonstrate commitment to Professional Ethics.
Program Highlights
  • Placement and internships in core companies like Cisco, IBM, Cerner, L & T Technology, Inside View, ThermoFisher Scientific, Bosch ,KPIT Technologies, 1000Looks.com, 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
Eligibility Criteria
  • B.Tech. (Computer and Information Science)
  • B.Tech. or B.E. (Computer Engineering)
  • B.Tech. or B.E. (Computer Science and Engineering)
  • B.Tech. or B.E. (Electrical and Electronics Engineering)
  • B.Tech. or B.E. (Electrical Engineering)
  • B.Tech. or B.E. (Electronics and Communication Engineering)
  • B.Tech. or B.E. (Electronics and Instrumentation Engineering)
  • B.Tech. or B.E. (Electronics Engineering)
  • B.Tech. or B.E. (Information Science and Engineering)
  • B.Tech. or B.E. (Information Technology)
  • M.Sc. in Computer Science
  • M.Sc. in Information Technology
  • M.Sc. in Software Engineering
  • MCA

Duration : Two years

Thrust Areas in Research

. 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

Abstract
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

Abstract
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

Abstract
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.

Placements

Excellent placement record of 88 % for the eligible students combining all three campuses in 2021 Batch

Students who are eligible and opt for placements could potentially have multiple job offers.Placements have always been excellent at Amrita. An array of companies visit Amrita for placement of M.Tech Students.Corporate & Industry Relations, has developed industry-academia association through frequent visits, interactions with the top management and facilitation of Faculty Development Programmes, Student Visits, Industrial Training, and Project Guidance under Corporate Action Plan.

  • Over 200 companies visit the campus every year.
  • Dream option available for placed students to go for higher packages / better job profiles.
  • More than 400 industrial tie-ups
  • Highest CTC/Salary: Rs. 75 Lakhs
  • Placement and six month Internships at Multinational Companies such as Google, Microsoft, Intel, Cisco, ABB, Wipro, Alcatel-Lucent, Cerner, Bosch, Honeywell, TCS, Zoho etc.

Fee Structure

Will be updated soon

Program Fees for the year 2019-2021
Campus Tuition Fees
per sem
Tuition Fees
Total
Hostel & Mess
Per Year
* * * *

Facilities & Infrastructure

 

Fully equipped computer laboratory exclusively for PG students Amrita Multi Dimensional Data Analytics Laboratory to support projects in Pervasive computing, Big Data Analytics, Web Science etc

Cognizant Innovation lab focusing on Robotics, Artificial Intelligence and Security, Image Analysis, Video processing and computer vision.

Facilities

Wireless Sensor Networks Lab involved in developing solutions using IoT, smart meters for societal applications

Facilities

Mobile Application Development Lab actively works in developing applications using signal processing for mobiles.

Why Amrita

The top reasons to choose Amrita for your career

601-800th

World University Rankings 2020

141

BRICS Rankings 2020

801–1000th

World University Rankings 2020

168th

BRICS University Rankings 2020

5th

India University Rankings 2020

12th

Overall Rankings 2020
ranking
5th Best
University in India
ranking
Amrita Ranked No.1 in India Top 100 in The World
ranking
Topmost
‘A++’ Grade

Testimonials

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.”

Placements

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

Admissions Apply Now