About AI&DS

The Department of Artificial Intelligence & Data Science (AI &DS) was started in the year 2023. AI & DS Department has well qualified and dedicated faculty members with excellent teaching and research skills. Our faculty members are working in wide variety of research areas and expertise in Data Analysis, Data exploration and Visualization in the specialization of machine Learning, Deep learning, AR/VR Cyber Security, Embedded Systems, Internet of Things, Networking and Big Data Analytics. Faculty members are encouraged to carry out research activities by setting up industry linked labs and getting funded projects from Government and NGOs. They are also encouraged to carry out industrial consultancy projects.

The department of AI & DS has well established laboratories with good computing facilities, software tools and applications to provide practical exposure to students. The following labs are set up in the Department in line with technology trends: Artificial Intelligence & Machine Learning (AI & ML) Laboratory, Deep Learning Laboratory, Python Programming laboratory, networking laboratory, Cloud and Data Analytics laboratory. We conduct Value Added Courses, Hands-on workshops and Technical Talks throughout the academic year in order to bridge the gap between the industry and the institute and which will help the students to enhance their skills. Our students regularly participate in curricular, co – curricular and extra – curricular activities and win Prizes and Awards. Students are encouraged and motivated to do Mini Projects, Online Courses such as NPTEL, IBM Online Course, Udemy, Udacity and Internships which are very much helpful during campus recruitment season. Our faculty members trained our students in aptitude, soft skills and communications from second year onwards for placement drive. Our students are studying mandatory certification courses in every semester from first onwards. Our recruiters include top companies such as Amazon, Accenture, CTS, TCS and Zoho.

PROGRAM EDUCATIONAL OBJECTIVES (PEOs)

PEO1. Utilize their proficiencies in the fundamental knowledge of basic sciences, mathematics, Artificial Intelligence, data science and statistics to build systems that require management and analysis of large volumes of data.

PEO2. Advance their technical skills to pursue pioneering research in the field of AI and Data Science and create disruptive and sustainable solutions for the welfare of ecosystems.

PEO3. Think logically, pursue lifelong learning and collaborate with an ethical attitude in a multidisciplinary team.

PEO4. Design and model AI based solutions to critical problem domains in the real world.

PEO5. Exhibit innovative thoughts and creative ideas for effective contribution towards economy building.

PROGRAM OUTCOMES (POs)

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 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 B.TECH. ARTIFICIAL INTELLIGENCE AND DATA SCIENCE 2 solutions in 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 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.

PROGRAM SPECIFIC OUTCOMES (PSOs)

At the end of the program, the students will be able to:

1. evolve AI based efficient domain specific processes for effective decision making in several domains such as business and governance domains.
2. arrive at actionable Foresight, Insight, hindsight from data for solving business and engineering problems
3. create, select and apply the theoretical knowledge of AI and Data Analytics along with practical industrial tools and techniques to manage and solve wicked societal problems
4. develop data analytics and data visualization skills, skills pertaining to knowledge acquisition, knowledge representation and knowledge engineering, and hence be capable of coordinating complex projects.
5. able to carry out fundamental research to cater the critical needs of the society through cutting edge technologies of AI.

To shape the thoughts of the Artificial Intelligence and Data Science technocrats as leaders of the future, instilling in them a strong sense of holistic values and a tenacious determination to tackle real-world problems, all while building on their technical brilliance.

• To ignite the potential of exceptional talents, moulding them into the driving force of tomorrow’s Artificial Intelligence and Data Science revolution.
• To equip them with technical mastery and relentless drive to lifelong learning to resolve real-world challenges.
• To inspire generations of responsible innovators, their impact echoing through a future enriched by positive change.