Counselling Code 2634

Artificial Intelligence and Data Science (AI &DS)

Artificial Intelligence and Data Science (AI & DS)

About the Department

B. Tech. in Artificial Intelligence and Data Science (AI &DS) is an undergraduate programme with advanced learning solutions imparting knowledge of advanced innovations like artificial intelligence, data science, machine learning and deep learning. The main goal of artificial intelligence and data science is to program computers to use example data or experience to solve a given problem.

Artificial Intelligence and Data Science is a new, exponentially growing field which consists of a set of tools and techniques used to extract useful information from data. This specialized course is specially designed to enable students to build intelligent machines, software, or applications with a cutting-edge combination of machine learning, analytics and visualization technologies.

This course aims at providing not only the core technologies such as artificial intelligence, data mining and data modeling but also gives intensive inputs in areas of machine learning and big data analytics. By this course, the students will gain cross-disciplinary skills across fields such as statistics, computer science, machine learning, and logic, data scientists and may have career opportunities in healthcare, business, eCommerce, social networking companies, climatology, biotechnology, genetics, and other important areas. The major focus of this programme is to equip students with statistical, mathematical reasoning, machine learning, knowledge discovery, and visualization skills.

Department Stats

Course Duration

04 Years

Semesters

08

Point of Contact

Head of the Department

Placement Coordinator

HOD’s Message

hodpic

Dr.Sreedhar

Professor and Head

Educational Qualification  : M.Tech.,Ph.D.
Teaching Experience         : 16 Years
Industry Experience          :  Nil

As the Head of the Department, I feel privileged to be leading a team of committed, talented and experienced faculty members. AI & DS is the most conspicuous technology that is instrumental in transforming the facet of industry and mankind. This course is specially designed to enable students to build intelligent machines, software, or applications with a cutting-edge combination of Machine Learning, Deep Learning, Analytics and Visualization technologies.

Our department aims to produce skilled professional in the domain of AI and DS and enable them to excel professionally. It also provides state of the art laboratory facilities to the students to get better practical exposure and strong ties with industry, research organizations and the community at large.

Vision & Mission

Our Vision

To promote quality education with industry collaboration and to enable students with intellectual skills to succeed in globally competitive environment

Our Mission

• To educate the students with strong fundamentals in the areas of Artificial Intelligence and Data Science.
• Provide multi-disciplinary research and innovation driven academic environment to meet the global demands.
• Foster the spirit of lifelong learning in students through practical and social exposure beyond the classroom.

Programs Outcomes & Objective

Program Outcome describe the knowledge, skills and attitudes the students should have at the end of a four year engineering program.

Engineering Graduates will be able to:

  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 of 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 to societal and environmental contexts, and demonstrate the knowledge of, and 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 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. Lifelong learning: Recognize the need for and have the preparation and ability to engage in independent and lifelong learning in the broadest context of technological change.

Program Specific Outcomes are statements that describe what the graduates of a specific engineering program should be able to do.

  1. Ability to implement innovative, cost effective, energy efficient and eco-friendly integrated solutions for existing and new applications using Internet of Things.
  2. Graduates will possess the additional skills in network security and IT infrastructure in Cyberspace
  3. Develop, test and maintain software system for business and other applications that meet the automation needs of the society and industry

List of Laboratory

Python Programming Lab
Computer Practices laboratory
Programming and Data Structures Lab
Intelligent Systems Laboratory
R Programming Laboratory
Data mining Tools Laboratory
Object Oriented Programming lab
RDBMS Lab
Machine Learning Laboratory
Data Analytics Laboratory
Security Lab

Proposed Artificial Intelligence Labs

AI & Deep Learning Lab
Machine Learning Lab
Cyber Physical Systems Lab
Business Intelligence Lab
High Performance Computing Lab
Robotics and Drone Lab

Additional Labs for Advanced Learning

Centre of Excellence for IOT
Centre of Excellence for Big Data

Value Added Courses