Our M.Tech programme prepares you to take up industrial job, research and development or academia.
Academics
M.Tech in Computer Science and Engineering (CSE) 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.
This M.Tech programme gives a specialized focus on areas of technology, aiming to develop skills and career prospects. The master's degree program offers an integrated course of study covering the theory, implementation and design of information, computing, communication and embedded systems.
This programme has specialized courses in the streams of Data Science, Computer Vision, IoT and High Performance Computing with significant focus on research. As a part of the programme during the period of study, students have the opportunity to intern at leading companies and R&D labs for a period of 6 months to one year. There are opportunities for the students to take up a semester or one year study at International Universities like Virje University, Netherlands, UC Davis, UNM for an exchange programme or to pursue a dual degree programme.
Graduates of this programme are well represented in Oracle, IBM, HP, Cerner, Intuit, and other major MNCs as well as in research in premier academic institutions in India and abroad. The graduates are competent to take up R&D positions in Industry, academia and research laboratories.
Programme 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.
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.
- 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.
- Wireless Sensor Networks Lab involved in developing solutions using IoT, smart meters for societal applications
- Mobile Application Development Lab actively works in developing applications using signal processing for mobiles.
- 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
Thrust Areas in Research
Biometrics
Computer Vision
Signal Processing
Security
Multidimensional Data Analytics
Data Analytics
Evolutionary Computing
Next Gen Computing
Predictive Analytics & IoT
Human Computer Interaction
Image Analysis and Pattern Recognition
Best Student Projects
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.
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.
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
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.
Internship Offered By
Center for International Programmes facilitates foreign internships with scholarship and higher education. Students can even opt for dual degree programmes.
Important: Direct admission and funding eligibility to partner International Universities in US, Europe to earn Dual Degrees- M. Tech. & M. S. in 2 years.
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 | |||
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 |
General Subjects Curriculum & Syllabus
Alumni Speaks
MTech(2015),
Informatica Business Solutions Pvt Ltd,
Bangalore
Informatica Business Solutions Pvt Ltd,
Bangalore
I chose M Tech at Amritapuri campus as it has the best infrastructure and resources. The programme helped me grow personally and professionally.
MTech,
CTS, Bangalore.
CTS, Bangalore.
Its a great school with the best infrastructure, highly qualified faculty and a wonderful student community.
MTech,
Infosys.
Infosys.
See Also
Eligibility Criteria
Applicants should have any of the following, scoring a minimum of 60% with a pass. Bachelor’s degree in Engineering / Technology (including the final year students awaiting the results) Master’s degree in any branch of Science / Mathematics / Statistics / Computer Applications Professional Society Examinations recognised by MHRD / UPSC / AICTE equivalent to B.E. / B.Tech / B. Arch.
