Computer Science And Engineering (AIML)

Computer Science And Engineering (AIML)

Eligibility

B. Tech. (Regular)

Passed 10+2 examination with Physics and Mathematics as compulsory subjects along with one of the Chemistry / Biotechnology / Biology / Technical Vocational subject Obtained at least 45% marks

Admission Process

Message from HoD

“AI & ML will be a great transformer, improving the efficiency of many sectors … and enabling the creation of higher-value services that can lead to overall economic growth.”

By: Dan Ayoub, General Manager of Mixed Reality Education at Microsoft

Machine Learning (ML) is a fascinating field of Artificial Intelligence (AI) research and practice where we investigate how computer agents can improve their perception, cognition, and action with experience.
Machine Learning is about machines improving from data, knowledge, experience and interaction. It utilizes a variety of techniques to intelligently handle large and complex amounts of information build upon foundations in many disciplines, including statistics, knowledge representation, planning and control, machine vision and natural language processing.

In Artificial Intelligence and Machine Learning Department of Inderprastha Engineering College, we study and research the theoretical foundations of the field of Machine Learning, as well as on the contributions to the general intelligence of the field of Artificial Intelligence.
In addition to their theoretical education, all of our students get hands-on experience with industrial real time problems related to data set.

Prof. (Dr.) Kumud Kundu

HoD (Officiating)

VISION

To achieve 3600standard of quality education by using latest tools, techniques and technology (T3) for student oriented innovations to relevant areas such as academia, R&D and industry which help to filling gap and towards serving the greater cause of society.

MISSION

  • To develop industry professionals who are skilled in the area of Artificial Intelligence and Machine Learning.
  • To impart skills in the upgradation of value-based courses and contribute towards the innovation of knowledge based expert system to raise satisfaction level of all stakeholders.

Our efforts to apply and demonstrate practical leaning through internship to solve live problems in various domains.

COURSE OUTCOMES

  • To apply basic principles of AI /ML in solutions that require problem solving, inference, perception, knowledge representation, and learning.
  • To demonstrate and understanding of various applications of AI techniques in intelligent agents, expert systems and other machine learning models.
  • To learn proficiency in applying scientific method to models of machine learning.
  • To understand state space and its searching strategies.
  • To apply the machine learning concepts in real life problems such as societal implications.