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PG Program

M.Tech- AI&ML

M.Tech · VTU Affiliated · AIEMS Bengaluru

Artificial Intelligence & Machine Learning
Department of CSE

A two-year postgraduate program built around the systems shaping 2026’s technology economy — generative AI, agentic systems, deep learning, and applied machine learning — taught with VTU’s revised CBCS & OBE scheme.

2 Yrs
Full-Time PG
4 Sem
Semesters
VTU
2026 CBCS-OBE
AICTE
Approved Norms

What you’ll build, in order

  • Foundations in advanced data structures, math, and data science management
  • Generative AI, deep learning architectures, and advanced ML systems
  • Specialised electives — Agentic AI, NLP, Reinforcement Learning, Computer Vision
  • Major project & internship translating research into deployable systems
Why This Program

AI & ML talent is the most contested hire in engineering right now

Every sector — from banking to agritech to healthcare — is restructuring around AI-native workflows. This program is designed to put you on the inside of that shift, not on the sidelines of it, with a curriculum revised for the realities of 2026’s AI stack: generative models, agentic systems, and production-grade ML.

Built on the newest VTU scheme

This M.Tech follows VTU’s 2026 Scheme of Teaching and Examinations under CBCS & OBE — including Generative AI and Agentic AI as named, credited courses, not bolt-on workshops.

Specialization, not generic CSE

Where a general CSE M.Tech samples everything, this specialization concentrates Semester II entirely on Generative AI, Deep Learning, Advanced ML, and Advanced Algorithms.

Electives map to real job families

Agentic AI, NLP, Reinforcement Learning, AI for Fintech, Healthcare Analytics — each elective corresponds to an active hiring category in 2026’s AI job market.

Research-readiness built in

A mandatory Research Methodology & IPR course and a Minor/Skill Development Project mean you graduate with a defensible research footprint, not just coursework.

Industrial Relevance

Where this degree is actually used

The subjects in this program aren’t abstract — each one is the technical backbone of a hiring category currently active across product companies, GCCs, startups, and research labs in Bengaluru and beyond.

Generative AI

Enterprise GenAI & LLM Engineering

Prompt pipelines, RAG systems, fine-tuning, and applied generative AI — the fastest-growing AI hiring segment of 2025–26.

Agentic Systems

Autonomous Agent Development

Multi-step, tool-using AI agents are replacing single-shot automation across SaaS, support, and operations tooling.

Computer Vision

Vision-Driven Automation

Manufacturing QC, surveillance, retail analytics, and autonomous systems all run on advanced computer vision pipelines.

NLP

Conversational & Document AI

Chatbots, document intelligence, and search are being rebuilt on transformer-based NLP across every industry vertical.

FinTech

Fraud Detection & Risk Models

Banks and fintechs run real-time fraud detection and credit-risk ML pipelines — a direct line to the Data Analytics for Fraud Detection elective.

HealthTech

Clinical & Diagnostic AI

AI for Healthcare Analytics underpins diagnostic imaging, patient risk scoring, and hospital operations software.

AgriTech

Precision Agriculture AI

Crop monitoring, yield prediction, and sustainability analytics — a growing applied-AI sector directly covered in the curriculum.

Explainable AI

Responsible & Auditable ML

As regulation catches up with AI, interpretable, auditable models are becoming a hard requirement in finance, health, and government deployments.

VTU Scheme 2026 · CBCS & OBE

The full course structure

Semester-wise breakdown as prescribed by Visvesvaraya Technological University, Belagavi, for M.Tech (CSE) with specialization in Artificial Intelligence and Machine Learning. Semester I is common to all CSE specializations; Semester II is where the AI & ML specialization fully takes shape.

Total Credits: 20
Total Marks: 700
Common to all CSE specializations
CodeCourse TitleTypeCredits
1MCS101Advanced MathematicsPCC3
1MCS102Advanced Data Structures and ApplicationsPCC3
1MCS103Data Science and ManagementPCC3
1MCS104xIntegrated Professional Core Course – I (choice: Advanced DBMS / Computer Networks / Operating Systems / Big Data Analytics)IPCC4
1MCS105xProfessional Elective Course – I (AI for IoT / AI for Cyber Security / Advanced Computer Vision / Fraud Detection Analytics)PEC3
1MCS106xProfessional Elective Course – II (Software Engineering & Web Apps / Blockchain / Mobile & Web Security / Data Engineering)PEC3
1MCSL107xProfessional Core Courses Lab (Software Testing / Computer Vision / Advanced Data Structures / Microservices)PCCL1
1MRMI108Research Methodology and IPR (Online — VTU Centre for Online Education)NCMC
Professional Electives in Semester I are common across all CSE specializations — students select the option most aligned with their specialization track.
Total Credits: 22
Total Marks: 800
Specialization: AI & Machine Learning
CodeCourse TitleTypeCredits
1MCAM201Generative AI and ApplicationsIPCC4
1MCAM202Deep Learning ArchitecturesPCC3
1MCAM203Advanced Machine LearningPCC3
1MSCS204Advanced AlgorithmsPCC3
1MXXX205xProfessional Elective Course – III (Agentic AI & Applications / Evolutionary ML / AI for Agritech & Sustainability / AI for Fintech)PEC3
1MXXX206xProfessional Elective Course – IV (Reinforcement Learning / AI for Healthcare Analytics / NLP / Explainable AI & Interpretable ML)PEC3
1MCAML207Advanced Machine Learning Lab (AEC Lab)PCCL1
1MCAMS208Minor Project / Skill Development ProjectPCC2
This is the defining semester of the specialization — Generative AI is taught as a 4-credit Integrated Professional Core Course with an embedded lab component, evaluated through both CIE and SEE.
Internship + Major Project Phase
SemesterFocus AreaComponent
Semester IIIOpen Elective, Internship / Industry Exposure, Major Project — Phase I (Literature Survey & Problem Identification)Project
Semester IVMajor Project — Phase II (Design, Implementation, Publication & Viva-Voce)Project
As per VTU norms, the final two semesters are weighted heavily toward independent research, an industry internship, and a major project — giving you a portfolio-ready body of work, often leading to publications, before graduation.
Choose Your Depth

Eight electives. Four hiring categories. You choose two.

Across PEC-III and PEC-IV in Semester II, you shape your own specialization within AI & ML — pick the pair that matches the career you’re building toward.

PEC-III

Agentic AI and Applications

PEC-III

Evolutionary Machine Learning

PEC-III

AI for Agritech and Sustainability

PEC-III

AI for Fintech

PEC-IV

Reinforcement Learning

PEC-IV

AI for Healthcare Analytics

PEC-IV

Natural Language Processing

PEC-IV

Explainable AI and Interpretable ML

Learning Outcomes

What you can do at the end of four semesters

Build & Deploy AI Systems

  • Design and fine-tune generative AI applications and RAG pipelines
  • Architect deep learning models for vision, text, and structured data
  • Engineer end-to-end ML pipelines from data to deployment

Reason Like a Researcher

  • Apply advanced algorithms and mathematics to novel problems
  • Conduct structured literature surveys and original research
  • Write and defend IEEE-style technical papers

Apply AI to Real Domains

  • Build domain-specific AI for fintech, healthcare, or agritech
  • Build autonomous, tool-using AI agents
  • Design explainable, auditable, and responsible ML systems
Where This Leads

Career destinations this degree is built for

M.Tech (AI & ML) graduates are positioned for roles that simply didn’t exist a decade ago, alongside traditional software and data career tracks.

Machine Learning Engineer
AI / LLM Application Developer
Data Scientist
Computer Vision Engineer
NLP / Conversational AI Engineer
AI Research Associate
MLOps / AI Platform Engineer
AI Product / Solutions Consultant
Doctoral Research (Ph.D.)
Sem I–II

Build core ML, deep learning & GenAI fluency through coursework and labs

Sem III

Apply skills in an industry internship and begin your major project research

Sem IV

Complete and defend your major project — often with a publishable paper

Graduate

Step into an AI/ML role, a startup, or a Ph.D. with a real portfolio behind you

Eligibility

B.E./B.Tech in CSE, ISE, AI&ML or allied branches

Affiliation

VTU Belagavi · AICTE Approved

Duration

2 Years · 4 Semesters · Full-Time

Full Admission Details →

Start the AI & ML career you’ve been planning

Seats for M.Tech (AI & Machine Learning) at AIEMS Bengaluru are limited each year. Talk to our admissions team to check eligibility and reserve your seat.