Department of Artificial Intelligence & Data Science
B. Tech. in Artificial Intelligence and Data Science (AI &DS) with intake of 60 started in 2021, offered by the Computer Science and Engineering Department 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.
VISION:
To promote quality education with industry collaboration and to enable students with intellectual skills to succeed in globally competitive environment.
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.
Programme Educational Objectives (PEO)
Program Educational Objectives describe the career and professional accomplishments in five years after graduation that the program is preparing graduates to achieve.
Graduates will have solid basics in Mathematics, Programming, Machine Learning, Artificial Intelligence and Data Science Fundamentals and Advancements to solve technical problems.
Graduates will have the capability to apply their acquired knowledge and skills to solve the issues in real world Artificial Intelligence and Data Science sectors and to develop feasible and viable systems.
Graduates will have the potential to participate in life-long learning through professional developments for societal needs with ethical values.
Programme Outcomes (POs)
Program Outcome describes the knowledge, skills and attitudes the students should have at the end of a four year engineering program.
Engineering Graduates will be able to:
Engineering Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals and an engineering specialization to the solution of complex engineering problems.
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.
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.
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.
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.
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.
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.
Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
Individual and team work: Function effectively as an individual and as a member or leader in diverse teams, and in multidisciplinary settings.
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.
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.
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.
Programme Specific Outcomes (PSOs)
Program Specific Outcomes are statements that describe what the graduates of a specific engineering program should be able to do.
Ability to implement innovative, cost effective, energy efficient and eco-friendly integrated solutions for existing and new applications using Internet of Things.
Graduates will possess the additional skills in network security and IT infrastructure in Cyberspace
Develop, test and maintain software system for business and other applications that meet the automation needs of the society and industry
HOD Message
Mr. A Ravindar Kumar
HOD
As the Head of the Department, I feel privileged to be leading a team of committed, talented and experienced faculty members. Artificial Intelligence and Data Science 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 Artificial Intelligence and Data Science 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.
Department also takes the initiative to improve the soft skills, analytical capabilities and verbal communication of the students so that they can face the competition in the corporate world confidently. The excellent infrastructure, experienced team of faculty dedicates to strengthen effective teaching learning process ensuring quality education.
Teaching Faculty – AI & DS Department
Mr.A Ravindra Kumar
M.Tech.,(PhD), Associate Professor & HoD
Dr. Eduru Nagarjuna
M.Tech., PhD, Professor
Mr. K S Ranjith
M.Tech., (PhD), Assistant Professor
Mr. D Prabhu Kumar
M.Tech., Assistant Professor
Mr. K V Ravi Kumar
MCA., Assistant Professor
Mr. B Rajesh
M.Tech., Assistant Professor
Mr. B MAHESH KUMAR
M.TECH, ASSISTANT PROFESSOR
Mr. B Praveen Kumar
M.Tech.,, Assistant Professor
Mrs. B H Chandana Reddy
M.Tech., , Assistant Professor
Mr. H B Althaf Hussain
M.Tech.,, Assistant Professor
Mrs. R Suganya Subathra
M.Tech., Assistant Professor
Mrs. A Rekha
M.E., Assistant Professor
Non Teaching Faculty – AI & DS Department
Mr. P. Sathish
B.Com, Lab Assistant
Faculty Achievements
2024-2025
Sl.No.
Faculty Name
Achievement
Attachment
1
Mr. A Ravindra Kumar
Deep Learning Techniques for Beginners - Book Published
2023-2024
Sl.No.
Faculty Name
Achievement
Attachment
1
Mr. Ranjith K S
Indian Patent Published
Student Achievements
Alumni
GATE qualified students
Internships
Meritorious Scholarships
Faculty
Student
Workshop
Academic Year 2023-2024
Sl.No.
Date
Activity Details
Attachment
1
15 Nov 2023 to 20 Nov 2023
A five days workshop on “FRONT-END WEB DESIGNING & DEVELOPMENT”
Academic Year 2022-2023
Sl.No.
Date
Activity Details
Attachment
1
24 Nov 2022 to 28 Nov 2022
A FIVE DAY WORKSHOP ON ARTIFICIAL INTELLIGENCE IN INDUSTRY
2
18 Apr 2023 to 20 Apr 2023
A three day Workshop on "Machine Learning & IoT"
Others
Academic Year 2023-2024
Sl.No.
Date
Activity Details
Attachment
1
21 Nov 2023 to 21 Nov 2023
“FRONT-END WEB DESIGNING & DEVELOPMENT” One Day Hackathon
Academic Year 2022-2023
Sl.No.
Date
Activity Details
Attachment
1
19 Apr 2023 to 19 Apr 2023
A ONE DAY NATIONAL LEVEL TECHNICAL SYMPOSIUM RAIDS '23', MITS
2
30 Apr 2023 to 28 May 2023
COMMUNITY SERVICE PROJECT
Academic Year 2021-2022
Sl.No.
Date
Activity Details
Attachment
1
19 Oct 2022 to 19 Oct 2022
FLASHMOB EVENT 2022
AI & DS LAB
CP LAB
JAVA LAB
MOU Activities
MEMORANDUM O UNDERSTANDING
Memorandum of Understanding on Monday, 09th October,2023 between Mother Theresa Institute of Engineering and Technology, Dept. of Artificial Intelligence & Data Science and Airbaclabs Pvt. Ltd.,