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M.Tech in Artificial Intelligence

Building Next-Generation Intelligent Systems

This specialization focuses on core areas of modern AI, including deep learning, natural language processing (NLP), computer vision, and reinforcement learning. Students gain expertise in developing sophisticated algorithms and models that enable machines to perceive, reason, and act intelligently, preparing them for cutting-edge roles in research and industry.

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Placement Records

Our M.Tech in Artificial Intelligence is built for specialists and researchers exploring advanced ML architectures, probabilistic reasoning and AI ethics through rigorous coursework, research projects and industry collaborations. We focus on developing professionals who design and deploy intelligent solutions to complex real-world problems.

93%

Thesis Completion Rate

90%

Advanced Certification Rate

2x

Industry-Sponsored Research Projects

3x

Internship Conversions

Your Future, Unfolded

The different career paths available for the program

M.Tech in Artificial Intelligence
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AI Research Scientist

MLOps Engineer

Generative AI Engineer

Computer Vision Specialist

NLP / Conversational AI Engineer

AI Ethics & Governance Analyst

AI Product Manager and many more

Certifications

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ServiceNow University

ServiceNow CSA & CAD certifications build advanced skills in AI-driven IT service management and enterprise workflow automation, preparing students for senior cloud solution roles.

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Amazon Web Services – ML Specialty

AWS ML Specialty certification validates expert-level skills in building and deploying scalable ML pipelines, bridging postgraduate academics with production-grade cloud engineering.

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Microsoft Azure AI Engineer Associate (AI-102)

Azure AI-102 equips students with specialised skills in Cognitive Services and Azure OpenAI, preparing them for senior AI engineering roles in enterprise environments.

Designed for Real-World Success

Our programs are built on an Outcome-Based Education (OBE) framework, ensuring that every concept connects to real-world application. With industry collaborations, and an active research culture, you gain hands-on experience alongside strong academic foundations.

Eligibility Criteria

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Academic Requirement

Candidates must have passed a 4-year Bachelor’s Degree in Engineering/Technology in the relevant branch from a recognized University.

Candidates must have secured a minimum of 50% aggregate marks in the qualifying undergraduate examination.

Entrance Test Requirement

Admission shall be based on merit through:

  • Graduate Aptitude Test in Engineering (GATE)

  • TS PGECET

  • Anurag Common Entrance Test (Anurag CET)

  • Qualifying Examination on merit

For Foreign / NRI category, admission shall be based on merit in GATE or marks secured in the qualifying examination.

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Future Pattern
Turning Degrees 
into Careers

Turning Degrees into Careers

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Frequently Asked Questions

It focuses on advanced concepts in artificial intelligence, machine learning, and intelligent systems.

Yes, it includes research-based learning along with practical implementation.

Yes, students work on real-world AI models and applications.

Basic knowledge of programming, mathematics, and data handling is beneficial.

It combines theoretical foundations, lab work, and research-driven projects.

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