Department of Computer Science & Engineering

in

AI and ML

Duration : 4 Years (Full Time) | Intake : 60 
 
 
 
 
Message from Head of the Department
 
Greetings from Department of Computer Science and Engineering (Artificial Intelligence and Machine Learning) of Siliguri Institute of Technology (SIT). Leading the department of Computer Science and Engineering (AI & ML), which strives to offer students a cutting-edge and excellent education in order to attain academic achievement, is a great honour for me. Faculties of the department are dedicated to ensuring that our students have the knowledge and skills in artificial intelligence, machine learning, and related fields that they need to succeed in our modern society. Department started its journey from the year of 2022. AI & ML has become a key tool for augmenting the human knowledge, which is an essential part of creation, discovery, and innovation. The Department's primary objective is to offer a healthy and strong platform to the students for developing their analytical and practical skills to utilize the same in real world problems.
 
Dr. Debajyoti Mishra
B.Tech., M.Tech., Ph.D (Engg.)
 
 
 
 

 
 
Facts and Figures
 
Duration: 4 Years B.Tech Degree Course under MAKAUT
 
Intake: 60
 
Number of Laboratories: 06
 
Departmental Coordinators:
Ms. Sucharita Das, Dr. Uddalak Mitra
 
 
 
 
 
 

Vision
 

The goal is to create skilled AI/ML experts who will improve engineering, science, and technology for the benefit of society, business, and academia by effectively applying artificial intelligence.

 

 

 
Mission
 
  • To provide high-quality values-based education in computer science and engineering (artificial intelligence & machine learning) and professional ethics, that meet international standards through creative teaching and learning techniques with a practical focus in order to achieve success in careers.
     
  • To encourage an innovative and research-focused culture in the area of computer science and engineering (artificial intelligence & machine learning), to overcome challenges in the real world and consequently include entrepreneurship skills for self-development.
     
  • To provide an environment that creates positive teacher–student relationships that can have long-lasting effects on the social, emotional, and academic development of youth.
     
 
 

 
 
PROGRAM EDUCATIONAL OBJECTIVES (PEO)
 

The Graduates of CSE (AI & ML) Learning will be able to:

  • Acquire in-depth understanding of CSE (AI & ML) that will enable them to pursue higher education or professional positions in the field of engineering.
     
  •  Utilize their expertise, resources, and experience to create new technologies, discover new methods of doing things, and solve technical challenges in a multidisciplinary work environment.
     
  • Adopt a lifelong learning mindset and be technologically adapted.
     
 
 

 
 
PROGRAM OUTCOMES (PO)
 

Engineering Graduates will be able to:

  • Engineering knowledge: Apply a thorough understanding of artificial intelligence, machine learning, and deep learning to the solution of challenging engineering challenges. This requires knowledge of mathematics, science, engineering foundations, and an engineering expertise.
     
  • Problem analysis: Utilizing the foundational principles of mathematics, statistics, the natural sciences, and artificial intelligence sciences, identify, create, study research material, and analyse difficult engineering problems to obtain validated conclusions.
     
  • Design/development of solutions: Designing complicated engineering problems' solutions as well as system elements or processes that satisfy the required requirements while taking into account public health and safety, cultural, socioeconomic, and environmental factors is essential.
     
  • Conduct investigations of complex problems: To come to reliable findings, use research-based knowledge and research techniques, such as experiment design, data analysis and interpretation, and information synthesis.
     
  • Modern tool usage: With an awareness of the constraints, develop, pick, and apply relevant methods, resources, and contemporary engineering and AI technologies, such as prediction and modelling, to complicated engineering processes.
     
  • The engineer and society: Assess societal, health, safety, legal, and cultural issues and the resulting obligations pertinent to the professional engineering profession by using reasoning informed by contextual knowledge.
     
  • Environment and sustainability: Demonstrate your understanding of the effects of professional engineering solutions in societal and environmental contexts as well as your understanding of the importance of sustainable development.
     
  • Ethics: Apply moral principles, and abide by the obligations, standards, and expectations of the engineering profession.
     
  • Individual and team work: Effectively perform on their own, as members or leaders of varied teams, and in multidisciplinary environments.
     
  • Communication: Being able to understand, interpret, and present clear instructions, understand and write effective reports and design documentation, and communicate effectively on complicated engineering operations with the engineering community and with society at large.
     
  • Project management and finance: Apply engineering and management principles to one's own work, as a team member and team leader, to manage projects, and in interdisciplinary settings. Demonstrate knowledge of and grasp of these principles.
     
  • Life-long learning: Recognize the need of autonomous learning and lifelong learning in the context of technological progress as a whole, and be prepared to do so.
     
 
 

 
 
PROGRAM SPECIFIC OUTCOMES (PSOs)
 

The PSOs of computer science and engineering (artificial intelligence & machine learning) program supported by the curriculum is given below. The students will be able to

  • PSO1: Apply basic science, engineering and mathematics including application appropriate to the field of artificial intelligence topics.
     
  • PSO2: Use programming language, algorithm principles, machine learning applications, data base analysis and management