Last Date to Apply for Final Phase of MTech Admissions - August 1, 2021
All courses are AICTE approved
GATE Candidates - Eligible for DIRECT Admissions
Non-GATE candidates - Online Interview Process
(NO Entrance exam required this year)
Contact MTech Team
Call Us Now: 9 AM - 6 PM
M. Tech. in Artificial Intelligence is a program offered at School of Engineering, Amrita Vishwa Vidyapeetham, Amritapuri campus.
As we see a tech revolution in all facets of life powered by Artificial Intelligence, Amrita Vishwa Vidyapeetham offers an M. Tech. program in AI at both Amritapuriand Coimbatore campuses to provide young engineers with a futuristic edge.
M. Tech. in AI will provide the students with an opportunity to learn both foundational and experimental components of AI and Machine Learning. The program will open various career opportunities involving innovation and problem solving using Artificial Intelligence (AI) and Machine Learning (ML) technologies as well as research careers in AI and ML.
Along with courses that provide specialization in AI, students will also have options to explore some applied domains such as computer vision, natural language processing, robotics, data analytics and computer security. This enables the M. Tech. in AI graduates to take up careers in R&D positions in Industry, academia and research laboratories. The 2-year postgraduate program is divided into 4 semesters, with each year containing 2 semesters. The course content provides the students with proper insight about the domain of Artificial Intelligence with a firm foundation in ‘Mathematics for Artificial Intelligence’. The carefully designed syllabus provides the students with deep knowledge in the core areas of Algorithm analysis and design, Modern Computer Architecture, foundations of Artificial Intelligence, Data Science and Machine Learning and Parallel and Distributed Data Management etc.
Highlights of the Specialisation
The Core courses give them sufficient expertise in the areas of Algorithm Analysis and Design, Modern Computer Architecture, Artificial Intelligence Foundations, Data Science and Machine Learning, Parallel and Distributed Data Management etc. Elective courses include various application domains of AI such as Robotics, Video/Image Analytics, Medical Signal Processing, Agents Based Systems, Data Mining and Business Analytics, Natural Language processing, Wireless Sensor Networks, Internet of things etc.
Once they complete the course, students get opportunities to get fully paid Internships and placement offers at MNCs and IT/ITES companies like Intel, Cerner, Robert Bosch, DELL etc. Also, they could publish quality research papers of the case studies/dissertations done as part of their M. Tech. program. Along with regular M. Tech, this program also provides opportunities to do Dual Degree Program (M. Tech from Amrita and MS from International universities) or One Semester/ One Year abroad programs offered by premiere universities like KTH (Sweden), Politecnico Di Milano (Italy), University of New Mexico (USA) and RWTH (Aachen University Germany).
Duration : Two years
Eligibility Criteria
- B.E./ B. Tech. (Computer Science, Information Technology, Electronics and Communication, Electrical and Electronics, Electronics and Instrumentation ), MCA, Msc Computer Science, Msc Software Engineering
Thrust Areas in Research
- Algorithm Analysis and Design
- Modern Computer Architecture
- Data Science and Machine Learning
- Parallel and Distributed Data Management
- Natural Language Processing
- Text Technologies for Data Science
- Data Analytics and Mining
- Big Data Management
- Data Visualization
- Internet of Things
Facilities & Infrastructure
- Smart Class Rooms
- High Performance Computing Lab with GPUs
- Machine learning Lab
- Top class faculty.
Curriculum
First Semester
| Course Code | Type | Course | L | T | P | Cr |
|---|---|---|---|---|---|---|
| 19AI601 | FC | Advanced Data structures and Algorithms | 3 | 0 | 1 | 4 |
| 19MA609 | FC | Mathematics for Artificial Intelligence | 3 | 0 | 1 | 4 |
| 19AI602 | FC | Foundations of Artificial Intelligence | 3 | 0 | 1 | 4 |
| SC | Soft Core I | 3 | 0 | 1 | 4 | |
| SC | Soft Core - II | 3 | 0 | 1 | 4 | |
| Elective | Elective I | 3 | 0 | 0 | 3 | |
| 19HU601 | HU | Amrita Values Program* | P/F | |||
| 19HU602 | HU | Career Competency I* | P/F | |||
| Total Credits | 23 | |||||
| *Non-credit course | 23 | |||||
Second Semester
| Course Code | Type | Course | L | T | P | Cr |
|---|---|---|---|---|---|---|
| SC | Soft Core - III | 3 | 0 | 1 | 4 | |
| SC | Soft Core - IV | 3 | 0 | 1 | 4 | |
| Elective | Elective - II | 3 | 0 | 0 | 3 | |
| Elective | Elective - III | 3 | 0 | 0 | 3 | |
| Elective | Elective - IV | 3 | 0 | 0 | 3 | |
| SC | Negotiated Studies | 2 | ||||
| 19RM600 | SC | Research Methodology | 2 | 0 | 0 | 2 |
| 19HU603 | HU | Career Competency II | 0 | 0 | 2 | P/F |
| Total Credits | 21 | |||||
Third Semester
| Course Code | Type | Course | L | T | P | Cr |
|---|---|---|---|---|---|---|
| 19AI798 | Dissertation | 10 | ||||
| Total Credits | 10 | |||||
Fourth Semester
| Course Code | Type | Course | L | T | P | Cr |
|---|---|---|---|---|---|---|
| 19AI799 | Dissertation | 12 | ||||
| Total Credits | 12 | |||||
| Total Credits | 66 | |||||
Foundation Courses
| Course Code | Course | L | T | P | Cr |
|---|---|---|---|---|---|
| 19AI601 | Advanced Data Structures and Algorithms | 3 | 0 | 1 | 4 |
| 19MA609 | Mathematics for Artificial Intelligence | 3 | 0 | 1 | 4 |
| 19AI602 | Foundations of Artificial Intelligence | 3 | 0 | 1 | 4 |
| Course Code | Course | L | T | P | Cr |
|---|---|---|---|---|---|
| 19RM600 | Research Methodology | 2 | 0 | 0 | 2 |
Elective (Live-in-Labs)
| Course Code | Course | L | T | P | Cr |
|---|---|---|---|---|---|
| 19AI797 | Live-in-Labs | 0 | 0 | 3 | 3 |
Students can do Live-in-Labs course in lieu of an elective from II Semester or III Semester
Soft Core
Students have to select any four soft core subjects from the list given below:
| Course Code | Course | L | T | P | Cr |
|---|---|---|---|---|---|
| 19AI611 | Foundation of Data Science | 3 | 0 | 1 | 4 |
| 19AI612 | Statistical Learning Theory | 3 | 0 | 1 | 4 |
| 19AI613 | Machine Learning | 3 | 0 | 1 | 4 |
| 19AI614 | Probabilistic Graphical Models | 3 | 0 | 1 | 4 |
| 19AI615 | Optimization Techniques | 3 | 0 | 1 | 4 |
| 19AI616 | Computational Statistics and Inference Theory | 3 | 0 | 1 | 4 |
| 19AI617 | Multi Agent Systems | 3 | 0 | 1 | 4 |
| 19AI618 | Computational Intelligence | 3 | 0 | 1 | 4 |
| 19AI619 | Deep Learning | 3 | 0 | 1 | 4 |
| 19AI620 | Reinforcement Learning | 3 | 0 | 1 | 4 |
| 19AI621 | Computer Vision | 3 | 0 | 1 | 4 |
| 19AI622 | Negotiated Studies | 2 | 0 | 0 | 2 |
Electives
| Course Code | Course | L | T | P | Cr |
|---|---|---|---|---|---|
| 19AI701 | Machine Learning for Big Data | 3 | 0 | 0 | 3 |
| 19AI702 | Applications of Machine Learning | 3 | 0 | 0 | 3 |
| 19AI703 | Representation Learning | 3 | 0 | 0 | 3 |
| 19AI704 | Applied Predictive Analytics | 3 | 0 | 0 | 3 |
| 19AI705 | AI in Natural Language Processing | 3 | 0 | 0 | 3 |
| 19AI706 | Introduction to Robotics | 3 | 0 | 0 | 3 |
| 19AI707 | Introduction to Game Theory | 3 | 0 | 0 | 3 |
| 19AI708 | Computational Linear Algebra | 3 | 0 | 0 | 3 |
| 19AI709 | Modeling and Simulation | 3 | 0 | 0 | 3 |
| 19AI710 | Advanced Algorithms and Analysis | 3 | 0 | 0 | 3 |
| 19AI711 | Information Retrieval | 3 | 0 | 0 | 3 |
| Course Code | Course | L | T | P | Cr |
|---|---|---|---|---|---|
| 19AI712 | Web Intelligence and Big Data | 3 | 0 | 0 | 3 |
| 19AI713 | Data Visualization | 3 | 0 | 0 | 3 |
| 19AI714 | Networks and Spectral Graph Theory | 3 | 0 | 0 | 3 |
| 19AI715 | Parallel and Distributed Data Management | 3 | 0 | 0 | 3 |
| 19AI716 | Cloud & Big Data Analytics | 3 | 0 | 0 | 3 |
| 19AI717 | Medical Signal Processing | 3 | 0 | 0 | 3 |
| 19AI718 | IoT Protocols and Architecture | 3 | 0 | 0 | 3 |
| 19AI719 | Parallel and Distributed Computing | 3 | 0 | 0 | 3 |
| 19AI720 | Modern Computer Architecture | 3 | 0 | 0 | 3 |
| 19AI721 | GPU architecture and Programming | 3 | 0 | 0 | 3 |
| 19AI722 | Image Analysis | 3 | 0 | 0 | 3 |
Placements & Internships
The course started in 2020, First Batch is ongoing.
Internships
The students of M. Tech. Computer Science and Engineering, Semester 2, 2018-2020 batch, secured prestigious internships at the following companies:
Namitha S. Nair
Dell EMC
Krishna Suresh
ABB
Shibu S. Narayanan
Dell EMC
Shilpa Joseph
Nokia
Arun Sandeep
Nokia
Gautham K. D.
Philips
Poojitha P. V.
Data Point Info Solution
Bhimavarapu Sumathi
Data Point Info Solution
Ashna Ann Babu
Nokia
Aiswarya k. P.
E & Y LTD
Akhil Sreekumar
Nokia
Industry Partners
Visit Department of Computer Science and Engineering (Amritapuri Campus) Website
Visit Department of Computer Science and Engineering (Coimbatore Campus) Website
Join Amrita M. Tech Artificial Intelligence @ Amritapuri campus or Coimbatore campus
If you wish to know more about the course please mail to,
mtech@amrita.edu
Related News
