B.Tech in Artificial Intelligence

B.Tech. in Artificial Intelligence

Prof. A. Thomas

Head ,Artificial Intelligence

Mobile: 9822222544

E-mail: achamma.thomas@raisoni.net

B. Tech./B.E. in Artificial Learning is an undergraduate programme with advanced learning solutions imparting knowledge of advanced innovations like machine learning, often called deep learning and artificial intelligence.

This specialisation is designed to enable students to build intelligent machines, software, or applications with a cutting-edge combination of machine learning, analytics and visualisation technologies. The main goal of artificial intelligence (AI) and machine learning is to program computers to use example data or experience to solve a given problem. Many successful applications based on machine learning exist already, including systems that analyze past sales data to predict customer behaviour (financial management), recognize faces or spoken speech, optimize robot behaviour so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data.

This programme discusses AI methods based in different fields, including neural networks, signal processing, control, and data mining, in order to present a unified treatment of machine learning problems and solutions.


Vision of the Department

To Achieve excellent standards of quality-education by using the latest tools, nurturing collaborative culture and disseminating customer oriented innovations to relevant areas of academia and industry towards serving the greater cause of society.

Mission of the Department

  • To develop professionals who are skilled in the area of Artificial Intelligence and Machine learning.
  • To impart quality and value based education and contribute towards the innovation of computing, expert system, Data Science to raise satisfaction level of all stakeholders.
  • Our effort is to apply new advancements in high performance  computing hardware and software.

Program Specific Outcomes

PSO 1:
Apply the skills in the areas of Health Care, Education ,Agriculture, Intelligent Transport, Environment, Smart Systems & in the multi-disciplinary area of Artificial Intelligence and Machine Learning.
PSO 2:
Demonstrate engineering practice learned through industry internship to solve live problems in various domains. Software applications for problem solving.

Program Outcomes

Demonstrate engineering practice learned through industry internship to solve live problems in various domains. Software applications for problem solving.

  1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  2. Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences
  3. Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
  4. Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
  5. Modern tool usage: Create, select, 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.
  6. The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
  7. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and the need for sustainable development.
  8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  10. Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
  11. Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
  12. Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.



Admission Enquiry/ARF 2019-20

Admission at GHRCE