Artificial Intelligence & Machine Learning

The Department of Artificial Intelligence & Machine Learning at BTI offers a four-year B.E. programme with an AICTE-approved intake of 120 seats. This forward-looking programme bridges computer science, statistics and cognitive science, training students to design intelligent systems, develop predictive models and deploy AI solutions across industries from healthcare to finance and autonomous systems.

Head of the DepartmentDr. M.A.Dorairangaswamy

Laboratories7 specialised labs

Experience35 Years

Apply for Admission

Vision

To enhance the technical knowledge of aspiring minds in the field of AI& ML by imparting good Academics and Research and for meeting the challenges in industry and society.

Mission

M1: To establish an efficient academic ecosystem by promoting innovation in advanced concepts like Artificial Intelligence and Machine Learning for addressing global needs.
M2: To nurture future generation of AI& ML engineers with technical expertise, taking societal challenges.
M3: To create an active learning environment that imparts interdisciplinary knowledge, making student excelling the research

Department at a Glance

AICTE Approved Intake120 seats
Affiliated to VTU, Belagavi; Established 2020
7 Specialised Laboratories including GPU / Deep Learning Lab
HODDr. M.A.Dorairangaswamy, 35 Years Experience
3 Design Patents from Government of India
Department magazineAkashavanI MangaL (launched Dec 2024)
Student associationBtAIans
11 student start-ups with BTI Incubation Centre
6 Google Brand Ambassadors from AIML department

PROGRAM EDUCATIONAL OBJECTIVES (PEOs)

PEO 1: To demonstrate strong technical expertise in Artificial Intelligence, Machine learning, Computer Vision, Cloud computing, Block chain Technology, enabling them to Design, Develop and implement innovations solutions for real world challenges.
PEO 2: To develop good foundation in core concept of the Artificial Intelligence and Machine Learning with the attitude to provide higher education by meeting industry requirements.
PEO 3: To exhibit professional ethics, effective communication, Leadership qualities contributing multidisciplinary excellence in their careers
PEO 4 : To develop technical knowledge and research skills, for establishing startups and become entrepreneurs.
PEO 5 : To address societal, environmental and global challenges by designing sustainable and efficient AI based systems which improves quality of the life.

PROGRAM SPECIFIC OUTCOMES (PSOs)

PSO1: Graduates will demonstrate proficiency in AI& amp; ML by applying principles of mathematics, Science and Engineering along with technical expertise
PSO2: Graduates will be equipped with proficiency in Artificial Intelligence employing the principles of Artificial Intelligence, Machine Learning, Computer Vision, Cloud Computing, Block chain Technology to cater technical growth.
PSO3: Graduates will develop proficiency in analytical skills, research and innovation contributing effectively as per the industry requirements by delivering effective socio-economic skills for the advancement in technology.

PROGRAM OUTCOMES (POs)

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 modelling 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 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.

Department