M. Tech. Computer Science and Engineering (Artificial Intelligence)

Duration
2 Years Full-Time Program
Eligibility

Eligibility Norms for Admission to B. Tech Programs: 

Candidates seeking admission to B.Tech. Program should have passed the Pre-University / Higher Secondary /or any equivalent 10+2 examination from an approved State / Central govt. board or from an international board like University of Cambridge "A" level certificate or certificate from International Baccalaureate (IB), Geneva, etc., with a minimum of 45% marks in Physics and Mathematics as compulsory subjects along with either Chemistry / Biotechnology / Biology / Electronics /Computer as an additional subject, and with 55% aggregate for SOCSE & 50% aggregate for SOE of total marks in the Qualifying Examination. Candidates should have appeared in any national / state level / Presidency University entrance examination viz. CET, Comed – K, JEE and such others.   

Eligibility Norms for Admission to B. Tech Programs (Lateral)  

A candidate who has passed any diploma examination or equivalent examination and obtained a minimum of 60% aggregate is eligible for admission to B. Tech Programs (Lateral Entry). Candidate should have appeared in any state level entrance examination. 

APPLY NOW
M. Tech. Computer Science and Engineering (Artificial Intelligence)

Programme Overview

The Master of Technology in Computer Science and Engineering (Specialization in Artificial Intelligence) is a postgraduate program that explores AI algorithms and their applications across sectors like healthcare, finance, agriculture, retail, and more. The program emphasizes emerging trends in AI and machine learning (ML) and aims to address research challenges while bridging the gap between theory and practice. It focuses on developing real-world applications to solve practical problems. Gartner highlights the growing demand for AI/ML skills, influencing company infrastructure decisions. Career opportunities include roles such as AI/ML engineer, big data analyst, NLP engineer, UX designer, AI researcher, and robotics/computer vision engineer.

Course Curriculum

  • 01Advanced Engineering Mathematics - MAT6001
  • 02English for Employability - ENG5001
  • 03Artificial Intelligence - CSE5005
  • 04Knowledge Engineering and Expert Systems - CSE5006
  • 05Machine Learning Algorithms - CSE5007
  • 06Discipline Elective – I - CSEXXXX
  • 07Discipline Elective – II - CSEXXXX
  • 08Seminar – I - SEM5001
  • 01Deep Learning - CSE6001
  • 02Natural Language Processing Techniques - CSE6002
  • 03Discipline Elective – III - CSEXXXX
  • 04Discipline Elective – IV - CSEXXXX
  • 05Discipline Elective – V - CSEXXXX
  • 06Open Elective – I - XXXXXXX
  • 07Open Elective – II - XXXXXXX
  • 08Seminar – II - SEM5002
  • 01Dissertation/Internship – I - PIP6001
  • 01Dissertation/Internship – II - PIP6002

Programme Educational Objectives

After two years of successful completion of the program, the graduates shall be:

PEO 01: To prepare graduates who will be successful professionals in industry, government, academia, research, entrepreneurial pursuit and consulting firms.

PEO 02: To prepare graduates who will contribute to society as broadly educated, expressive, ethical and responsible citizens with proven expertise.

PEO 03: To prepare graduates who will achieve peer recognition as individuals or in a team through demonstration of good analytical, research, design and implementation skills.

PEO 04: To prepare graduates who will thrive to pursue life-long reflective learning to fulfil their goals.

Programme Outcomes (POs)

On successful completion of the Program, the students shall be able to:

PO 1: An ability to analysis, manage and supervise engineering systems and processes with the aid of appropriate advanced tools.

PO 2: An ability to design a system and process within constraints of health, safety, security, economics, manufacturability to meet desired needs.

PO 3: An ability to carry out research in the respective discipline and publish the findings.

PO 4: An ability to effectively communicate and transfer the knowledge/ skill to stakeholders.

PO 5: An ability to realize the impact of engineering solutions in a contemporary, global, economic, environmental, and societal context for sustainable development.

Programme Specific Outcomes

Upon completion of the M. Tech. in AI program, students shall be able to:

PSO 01: [Problem Analysis]: Identify, formulate, research literature, and analyze complex engineering problems related to AI and ML principles and practices, Programming and Computing technologies reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

PSO 02: [Design/development of Solutions]: Design solutions for complex engineering problems related to AI and ML principles and practices, Programming and Computing technologies and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, cultural, societal and environmental considerations.

PSO 03: [Modern Tool usage]: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modelling to complex engineering activities related to AI & ML principles and practices, Programming AI and ML Computing & analytics with an understanding of the limitations.

Student handbook

Coming soon...

Program Regulations

Coming soon...

Download Brochure

Coming soon...

USP

Coming soon...

Career Opportunities

  • Core AI Roles

    Machine Learning Engineer: Design and implement machine learning models for tasks like recommendation systems, fraud detection, and predictive analytics.

    Data Scientist: Analyze and interpret complex datasets to uncover trends and insights.

    AI Research Scientist: Conduct research in AI subfields like deep learning, reinforcement learning, and natural language processing.

    Computer Vision Engineer: Develop algorithms for image and video analysis, such as facial recognition and autonomous vehicles.

    Natural Language Processing (NLP) Specialist: Focus on language-related AI applications, like chatbots, translation systems, and sentiment analysis.

  • AI in Industry-Specific Roles

    Robotics Engineer: Work on AI-driven robots for automation in manufacturing, healthcare, or logistics.

    AI Product Manager: Oversee the development and deployment of AI-powered products.

    Autonomous Systems Engineer: Design AI for self-driving cars, drones, or delivery bots.

    Healthcare AI Specialist: Develop diagnostic tools, treatment planning systems, and health monitoring devices using AI.

  • Cross-Disciplinary and Emerging Roles

    AI Ethics Consultant: Address ethical concerns and biases in AI systems while ensuring compliance with global regulations such as GDPR.

    AI Consultant: Provide AI-driven solutions to organizations for process optimization and innovation.

    Edge AI Developer: Focus on deploying AI models on edge devices like IoT gadgets for real-time processing.

    AI-Blockchain Developer: Work on integrating AI with blockchain for secure data-driven applications.

  • Academic and Research Roles

    AI Lecturer/Professor: Teach AI and machine learning courses in academic institutions.

    Research Scientist: Work with ISRO, DRDO, or CSIR on AI-related research projects.

  • Entrepreneurship

    AI Startup Founder: Launch startups focused on innovative AI applications in fields like fintech, edtech, or Healthtech.

Your Next Move Awaits

Begin an extraordinary journey with Presidency University.