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M.Tech in Artificial Intelligence (AI)(M.Tech)

Course Duration

4 Semesters
(2 Years)

Eligibility Criteria

B E/B.Tech. in CSE/ISE/TE/ECE/EEE/IT/MCA/M.Sc in Computer Science or Mathematics or Information Science or Information Technology with a minimum of 50% (45% in case of SC/ST) marks in aggregate of any recognized University/Institution or AMIE or any other qualification recognized as equivalent thereto.

Overview

Artificial Intelligence (AI) plays a vital role in our daily lives and as the usage of AI is increasing, there is a huge demand for researchers and scientists who can understand AI and develop AI-driven technologies.

The M.Tech in Artificial Intelligence programme offers students an opportunity to acquire knowledge on both foundational and experimental components of AI and Machine Learning. Apart from the specialization in Artificial Intelligence, students also have an opportunity to explore some applied areas like natural language processing, computer vision, robotics, and software analysis.

Artificial Intelligence emphasizes mainly the building of intelligent computational processes for the benefit of both creating artificial machines/devices and enhancing the understanding of human intelligence.

FUTURE OF PURSUING M.TECH

Students who pursue this programme will be able to innovate using Artificial Intelligence (AI) and Machine Learning (ML) technologies.

They can pursue research careers in AI, ML, and, in general, Computer Science areas.

Artificial Intelligence, sometimes known as Machine Intelligence, is the intelligence exhibited by machines, as compared to natural intelligence.

Course Curriculum

01Optimization Techniques

02Advanced Machine learning (Innovation)

03Python for Artificial Intelligence (Innovation)

04Applied Statistics

05Neural Networks

06Random Process and Linear Algebra

07Research Methodology (Innovation and Intellectual Property)

01

  • Agile Software Development (Entrepreneurship)
  • Digital Image Processing and Computer vision
  • Modern Databases

02

  • Data Visualization Techniques
  • Big Data Analytics (Entrepreneurship)
  • Deep Learning and Reinforcement Learning (Innovation and Entrepreneurship)

03

  • Fuzzy Logic and Probabilistic Graphs
  • Robotic Process Automation (Innovation and Entrepreneurship)
  • Game Theory

04

  • Web Mining (Entrepreneurship)
  • Natural Language Processing (Entrepreneurship)
  • Virtual and Augmented Reality (Innovation and Entrepreneurship)

05

  • Knowledge Representation and Reasoning
  • Internet of Things (Innovation)
  • Modern Databases

06Predictive Analytics using R Lab

07Mini Project (Innovation and Intellectual Property)

01

  • Swarm and Evolutionary Computation
  • Digital Signal Processing
  • Multi Agent Systems

02Open Elective

03Project Phase-1 (Innovation and Intellectual Property)

04Internship/Global Certification

01Internship/Global Certification

Programme Educational Objectives (PEOs)

Graduates of M.Tech. (Artificial Intelligence) will be able to:

PEO-1

Demonstrate skills as an Artificial Intelligence professional.

PEO-2

Engage in active research for professional development in the field of Artificial Intelligence.

PEO-3

Pursue entrepreneurship.

Programme Outcomes (POs)

On successful completion of the programme, graduates of M.Tech. (Artificial Intelligence) will be able to:

PO 1

Demonstrate in-depth knowledge of specific discipline or professional area, including wider and global perspective, with an ability to discriminate, evaluate, analyse and synthesise existing and new knowledge, and integration of the same for enhancement of knowledge.

PO 2

Analyse complex engineering problems critically, apply independent judgment for synthesizing information to make intellectual and/or creative advances for conducting research in a wider theoretical, practical and policy context.

PO 3

Think laterally and originally, conceptualize and solve engineering problems, evaluate a wide range of potential solutions for those problems and arrive at feasible, optimal solutions after considering public health and safety, cultural, societal and environmental factors in the core areas of expertise.

PO 4

Extract information pertinent to unfamiliar problems through literature survey and experiments, apply appropriate research methodologies, techniques and tools, design, conduct experiments, analyze and interpret data, demonstrate higher order skill and view things in a broader perspective, contribute individually/in group(s) to the development of scientific/technological knowledge in one or more domains of engineering.

PO 5

Create, select, learn and apply appropriate techniques, resources, and modern engineering and IT tools, including prediction and modeling, to complex engineering activities with an understanding of the limitations.

PO 6

Possess knowledge and understanding of group dynamics, recognize opportunities and contribute positively to collaborative-multidisciplinary scientific research, demonstrate a capacity for self-management and teamwork, decision-making based on open-mindedness, objectivity and rational analysis in order to achieve common goals and further the learning of themselves as well as others.

PO 7

Demonstrate knowledge and understanding of engineering and management principles and apply the same to one’s own work, as a member and leader in a team, manage projects efficiently in respective disciplines and multidisciplinary environments after consideration of economical and financial factors.

PO 8

Communicate with the engineering community, and with society at large, regarding complex engineering activities confidently and effectively, such as, being able to comprehend and write effective reports and design documentation by adhering to appropriate standards, make effective presentations, and give and receive clear instructions.

PO 9

Recognise the need for, and have the preparation and ability to engage in life-long learning independently, with a high level of enthusiasm and commitment to improve knowledge and competence continuously.

PO 10

Acquire professional and intellectual integrity, professional code of conduct, ethics of research and scholarship, consideration of the impact of research outcomes on professional practices and an understanding of responsibility to contribute to the community for sustainable development of society.

Programme Handbooks

Programme Specific Outcomes

Graduates of M.Tech. (Artificial Intelligence) programme will be able to:

  • PSO-1: Isolate and solve complex problems in the domains of Artificial Intelligence using latest hardware and software tools and technologies, along with analytical and managerial skills to arrive at cost effective and optimum solutions either independently or as a team.
  • PSO-2: Implant the capacity to apply the concepts of Artificial Intelligence, Deep Learning & Reinforcement Learning, Game Theory, Neural Networks, Machine learning, Fuzzy Logic and Probabilistic Graphs etc. in the design, development of software.
  • PSO-3: Review scholarly work by referring journals, define a new problem, design, model, analyze and evaluate the solution and report as a dissertation in the area of Artificial Intelligence.

Career Opportunities

  • Public and private sectors
  • Job Role: Computer Scientist
  • Robotic Scientist
  • Game Programmer
  • Software Engineer or as Developer for AI machines
  • Pursue higher studies
Fee
  • Indian / SAARC Nationals₹ 1000
  • NRI Fee₹ 2000
  • Foreign NationalsUS$ 50
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