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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.
| Course Code | Type | Course | L | T | P | Cr |
|---|---|---|---|---|---|---|
| 21AI601 | FC | Advanced Data Structures and Algorithms | 3 | 0 | 2 | 4 |
| 21MA613 | FC | Linear Algebra and Probability | 2 | 1 | 0 | 3 |
| 21AI602 | FC | Computational Methods for Optimisation | 2 | 1 | 0 | 3 |
| 21AI603 | FC | Foundations of Artificial Intelligence | 3 | 0 | 2 | 4 |
| 21AI604 | FC | Machine Learning | 3 | 0 | 2 | 4 |
| 21HU601 | HU | Amrita Values Program∗ | * | * | * | P/F |
| 21HU602 | HU | Career Competency I | * | * | * | P/F |
| Total Credits | 18 | |||||
∗Non-credit course
| Course Code | Type | Course | L | T | P | Cr |
|---|---|---|---|---|---|---|
| SC | Soft Core – I | 3 | 0 | 2 | 4 | |
| SC | Soft Core – II | 3 | 0 | 2 | 4 | |
| Elective | Elective – I | 2 | 0 | 2 | 3 | |
| Elective | Elective – II | 2 | 0 | 2 | 3 | |
| 21AI698 | SC | Case Study | 0 | 0 | 4 | 2 |
| 21RM618 | SC | Research Methodology | 2 | 0 | 0 | 2 |
| 21HU603 | HU | Career Competency II | 0 | 0 | 2 | 1 |
| Total Credits | 19 | |||||
| Course Code | Type | Course | L | T | P | Cr |
|---|---|---|---|---|---|---|
| 19AI798 | E | Elective – III | 2 | 0 | 2 | 3 |
| 21AI723 | E | Negotiated Studies/Online Course | 3 | 0 | 0 | 3 |
| 19AI798 | * | Dissertation Phase I | * | * | * | 10 |
| Total Credits | 16 | |||||
| Course Code | Type | Course | L | T | P | Cr |
|---|---|---|---|---|---|---|
| 21AI799 | * | Dissertation Phase II | * | * | * | 16 |
| Total Credits | 16 | |||||
| Total Credits | 69 | |||||
| Course Code | Course | L | T | P | Cr |
|---|---|---|---|---|---|
| 21AI601 | Advanced Data Structures and Algorithms | 3 | 0 | 2 | 4 |
| 21MA613 | Linear Algebra and Probability | 2 | 1 | 0 | 3 |
| 21AI602 | Computational Methods for Optimisation | 2 | 1 | 0 | 3 |
| 21AI603 | Foundations of Artificial Intelligence | 3 | 0 | 2 | 4 |
| 21AI604 | Machine Learning | 3 | 0 | 2 | 4 |
| Course Code | Course | L | T | P | Cr |
|---|---|---|---|---|---|
| 21AI631 | Foundation of Data Science | 3 | 0 | 2 | 4 |
| 21AI632 | Statistical Learning Theory | 3 | 0 | 2 | 4 |
| 21AI633 | Probabilistic Graphical Models | 3 | 0 | 2 | 4 |
| 21AI634 | Computational Statistics and Inference Theory | 3 | 0 | 2 | 4 |
| 21AI635 | Multi Agent Systems | 3 | 0 | 2 | 4 |
| 21AI636 | Computational Intelligence | 3 | 0 | 2 | 4 |
| 21AI637 | Deep Learning | 3 | 0 | 2 | 4 |
| 21AI638 | Reinforcement Learning | 3 | 0 | 2 | 4 |
| 21AI639 | Computer Vision | 3 | 0 | 2 | 4 |
| 21AI640 | Data Engineering | 3 | 0 | 2 | 4 |
| 21AI641 | Mining of Massive Datasets | 3 | 0 | 2 | 4 |
| 21AI642 | Natural Language Processing | 3 | 0 | 2 | 4 |
| 21AI643 | Cloud and Big Data Analytics | 3 | 0 | 2 | 4 |
| 21AI698 | Case Study | 0 | 0 | 4 | 2 |
| 21RM618 | Research Methodology | 2 | 0 | 0 | 2 |
| Course Code | Course | L | T | P | Cr |
|---|---|---|---|---|---|
| 21AI701 | Machine Learning for Big Data | 2 | 0 | 2 | 3 |
| 21AI702 | Applications of Machine Learning | 2 | 0 | 2 | 3 |
| 21AI703 | Representation Learning | 2 | 0 | 2 | 3 |
| 21AI704 | Applied Predictive Analytics | 2 | 0 | 2 | 3 |
| 21AI705 | Artificial Intelligence for Robotics | 2 | 0 | 2 | 3 |
| 21AI706 | Introduction to Game Theory | 2 | 0 | 2 | 3 |
| 21AI707 | Modeling and Simulation | 2 | 0 | 2 | 3 |
| 21AI708 | Information Retrieval | 2 | 0 | 2 | 3 |
| 21AI709 | Web Intelligence and Big Data | 2 | 0 | 2 | 3 |
| 21AI710 | Data Visualization | 2 | 0 | 2 | 3 |
| 21AI711 | Networks and Spectral Graph Theory | 2 | 0 | 2 | 3 |
| 21AI712 | Parallel and Distributed Data Management | 2 | 0 | 2 | 3 |
| 21AI713 | Medical Signal Processing | 2 | 0 | 2 | 3 |
| 21AI714 | Parallel and Distributed Computing | 2 | 0 | 2 | 3 |
| 21AI715 | Modern Computer Architecture | 2 | 0 | 2 | 3 |
| 21AI716 | GPU Architecture and Programming | 2 | 0 | 2 | 3 |
| 21AI717 | IoT for AI | 2 | 0 | 2 | 3 |
| 21AI718 | Neuroevolution | 2 | 0 | 2 | 3 |
| 21AI719 | Quantum Artificial Intelligence | 2 | 0 | 2 | 3 |
| 21AI720 | Knowledge Graphs | 2 | 0 | 2 | 3 |
| 21AI721 | Integer Programming: Theory and Computations | 2 | 0 | 2 | 3 |
| 21AI722 | Data Pre-processing and Feature Engineering | 2 | 0 | 2 | 3 |
| 21AI723 | Negotiated Studies/Online Course | 3 | 0 | 0 | 3 |
Duration: Two years
B.E./ B. Tech. (Computer Science, Information Technology, Electronics and Communication, Electrical and Electronics, Electronics and Instrumentation ), MCA, MSc Computer Science, MSc Software Engineering
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).
At Amrita, companies vie with each other to be the early birds for hiring,
thanks to the quality of students, past and present.
The top reasons to choose Amrita for your career
Email
mtech@amrita.edu
