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Program Overview

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.

Attention Please !

Amrita Vishwa Vidyapeetham has not appointed any Agent or Third-Party Client for securing admission in any programme. Students are hereby requested to contact only the toll-free number on our website for any admission related queries.

– Issued In Public Interest By Directorate Of Admissions And Academic Outreach

Curriculum

Semester I Semester II Semester III Fourth Semester Foundation Courses Soft Core Electives

Semester I

Course Code	Type	Courses	L T P	Credit
24AI601	FC	Foundations of Artificial Intelligence	3-0-2	4
24MA603	FC	Mathematical Foundations of Computing	3-1-0	4
24AI602	FC	Machine Learning	3-0-2	4
	SC	Soft Core – I	3-0-2	4
24RM605	FC	Research Methodology	2-0-0	2
22AVP103	HU	Mastery Over Mind (MAOM)	1-0-2	2
23AVP601	HU	Amrita Values Program∗		P/F
23HU601	HU	Career Competency I	0 0 3	P/F
		Total Credits		20

*Non-credit course

Semester II

Course Code	Type	Courses	L T P	Credit
	SC	Soft Core – II	3-0-2	4
	SC	Soft Core – III	3-0-2	4
	SC	Elective – I	2-0-2	3
	E	Elective – II	2-0-2	3
	E	Elective – III	2-0-2	3
24AI698	FC	Case Study	0-0-4	2
23HU611	HU	Career Competency II	0 0 3	1
		Total Credits		20

Semester III

Course Code	Type	Courses	L T P	Credit
	E	Elective – IV	2 0 2	3
	E	Elective – V	3 0 0	3
24AI798		Dissertation Phase I		10
		Total Credits		16

Fourth Semester

Course Code	Courses	Credit
24AI799	Dissertation Phase II	16
	Total Credits	16

Foundation Courses

Course Code	Courses	L T P	Credit
24AI601	Foundations of Artificial Intelligence	3-0-2	4
24MA603	Mathematical Foundations of Computing	3-1-0	4
24AI602	Machine Learning	3-0-2	4
24RM605	Research Methodology	2 0 0	2
24AI698	Case Study	0 0 4	2

Soft Core

Course Code	Courses	L T P	Credit
24AI631	Foundations of Data Science	3-0-2	4
24AI632	Advanced Algorithm Design	3-0-2	4
24AI633	Probabilistic Graphical Models	3-0-2	4
24AI634	Computational Statistics and Inference Theory	3-0-2	4
24AI635	Computational Intelligence	3-0-2	4
24AI636	Deep Learning	3-0-2	4
24AI637	Reinforcement Learning	3-0-2	4
24AI638	Mining of Massive Datasets	3-0-2	4
24AI639	Generative AI	3-0-2	4

Electives

Course Code	Courses	L T P	Credit
24AI731	Machine Learning for Big Data	2 0 2	3
24AI732	Applications of Machine Learning	2 0 2	3
24AI733	Evolutionary Machine Learning	2 0 2	3
24AI734	Applied Predictive Analytics	2 0 2	3
24AI735	Federated Learning	2 0 2	3
24AI736	Explainable AI	2 0 2	3
24AI737	Artificial Intelligence for Robotics	2 0 2	3
24AI738	Data Visualization	2 0 2	3
24AI739	Stochastic Modeling	2 0 2	3
24AI740	Networks and Spectral Graph Theory	2 0 2	3
24AI741	Parallel and Distributed Data Management	2 0 2	3
24AI742	Medical Signal Processing	2 0 2	3
24AI743	Computer Vision	2 0 2	3
24AI744	Natural Language Processing	2 0 2	3
24AI745	GPU Architecture and Programming	2 0 2	3
24AI746	Artificial Intelligence for IoT	2 0 2	3
24AI747	Quantum Artificial Intelligence	2 0 2	3
24AI748	Blockchain Technology	2 0 2	3
24AI749	Artificial Intelligence for Bioinformatics	2 0 2	3
24AI750	Cloud and Big Data Analytics	2 0 2	3

* Students can take Electives from other M.Tech branches in place of any one elective. Students can select online courses in place of Elective IV and Elective V as per the university norms with the consent and approval from the department.

Curriculum and Syllabus

2024 Curriculum & Syllabus

2021 Curriculum & Syllabus

Admission

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

Program Overview

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).

Thrust Areas in Research