Vidya Academy of Science & Technology

A unit of Vidya International Charitable Trust

Accredited by NAAC with "B++" grade

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Admissions 2026

Artificial Intelligence & Machine Learning

Phone / Email

04885287751

04885287752

aimlhod@vidyaacademy.ac.in

About

Artificial Intelligence and Machine Learning (AI & ML) is an emerging area which expands its boundaries to a variety of fields. AI & ML has now proven high impact in different sectors like healthcare, security, entertainment, education, autonomous transportation, intelligent robots, space exploration, speech processing, stock trading and many more. The department of Artificial Intelligence and Machine Learning (AIML) is established with a vision to emerge as a premier center for education and research in Artificial Intelligence and Machine Learning. The department currently offers a 4 year B.Tech programme in the engineering stream under the affiliation of KTU. The current intake to this programme is 60. This programme covers the fundamentals of computer science courses along with industry oriented courses pertaining to AI and ML. This course is best suited for students seeking to build expertise in Artificial Intelligence and Machine Learning and emerging technologies.

Career opportunities in Artificial Intelligence and Machine Learning are Data Scientist, Machine Learning Engineer, Research Scientist, Business Intelligence Developer, Product Manager, Robotics Scientist and many more. The faculty members are highly motivated and devoted in delivering the highest quality professional education to students, and strive to excel in their research areas. Our initiatives will definitely mould the students in such a way that they face the external world with prompt technical, interpersonal and problem-solving skills.

VISION

To be a center of excellence in artificial intelligence and machine learning education, research, and innovation, nurturing competent professionals capable of developing intelligent, ethical, and sustainable solutions for societal and industrial advancement.

MISSION

M1: Provide quality education in artificial intelligence and machine learning through effective teaching-learning practices, enabling students to acquire strong technical knowledge, analytical skills, and problem-solving abilities.

M2: Promote research, innovation, entrepreneurship, and interdisciplinary collaboration in emerging AI technologies to address industrial and societal challenges.

M3: Develop professionally competent graduates with ethical values, leadership qualities, lifelong learning abilities, and a commitment to societal well-being in a technology-driven world.

Vission and Mission

HOD

Dr. Jeeva K A

M.Tech, Ph.D

Professor & HOD

jeeva@vidyaacademy.ac.in

Ext : 149

Previous Experience :- 18 years of Teaching

Areas of Interest :- Secure signal processing, Cryptography, Image processing

PEOPLE

Dr. Jeeva K A

HOD

Ms. Sreemol V C

Trade Instructor

Diploma

sreemol848@vidyaacademy.ac.in

PEOs, POs & PSOs

Knowledge and Attitude Profile (WK)

WK1: A systematic, theory-based understanding of the natural sciences applicable to the discipline and awareness of relevant social sciences.

WK2: Conceptually-based mathematics, numerical analysis, data analysis, statistics and formal aspects of computer and information science to support detailed analysis and modelling applicable to the discipline.

WK3: A systematic, theory-based formulation of engineering fundamentals required in the engineering discipline.

WK4: Engineering specialist knowledge that provides theoretical frameworks and bodies of knowledge for the accepted practice areas in the engineering discipline; much is at the forefront of the discipline.

WK5: Knowledge, including efficient resource use, environmental impacts, whole-life cost, re-use of resources, net zero carbon, and similar concepts,that supports engineering design and operations in a practice area.

WK6: Knowledge of engineering practice (technology) in the practice areas in the engineering discipline.

WK7: Knowledge of the role of engineering in society and identified issues in engineering practice in the discipline, such as the professional responsibility of an engineer to public safety and sustainable development.

WK8: Engagement with selected knowledge in the current research literature of the discipline, awareness of the power of critical thinking and creative approaches to evaluate emerging issues.

WK9: Ethics, inclusive behavior and conduct. Knowledge of professional ethics, responsibilities, and norms of engineering practice. Awareness of the need for diversity by reason of ethinicity, gender, age, physical ability etc. with mutual understanding and respect, and of inclusive attitudes.

PEOs

PEO1: Graduates will demonstrate strong foundations in basic sciences, mathematics, computing, and Artificial Intelligence to develop analytical thinking, solve complex problems, and pursue successful careers in AI and related domains.

PEO2: Graduates will pursue research, higher education, innovation, and entrepreneurial ventures by applying emerging AI technologies to solve industrial and societal challenges.

PEO3: Graduates will demonstrate professional ethics, leadership, effective communication, teamwork, and lifelong learning to adapt to technological advancements and contribute responsibly to society.

PSOs

PSO1 Apply the principles of Computer Science, Mathematics, Artificial Intelligence, and Machine Learning to analyse, design and develop software systems for solving complex engineering problems.

PSO2 Analyse structured and unstructured data using statistical, data analytics, Artificial Intelligence, and Machine Learning techniques to develop ethical solutions for real-world applications.

PSO3 Integrate Artificial Intelligence, Machine Learning, and modern computing technologies with software engineering principles to develop AI based solutions through multidisciplinary approach.

Program Outcomes (POs)

The graduates of Artificial Intelligence & Machine Learning will be able to:
01. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals and Artificial Intelligence and Machine Learning specialization to the solution of complex engineering problems.
02. Problem analysis: Identity, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
03. Design/development of solutions: Design solutions for complex engineering problems, design system components or processes that meet the specified needs with appropriate consideration for public health and safety, cultural, societal and environmental considerations.
04. 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.

PO5: Engineering Tool Usage: Create, select and apply appropriate techniques, resources and modern engineering & IT tools, including prediction and modelling recognizing their limitations to solve complex engineering problems. (WK2 and WK6)

PO6: The Engineer and The World: Analyze and evaluate societal and environmental aspects while solving complex engineering problems for its impact on sustainability with reference to economy, health, safety, legal framework, culture and environment. (WK1, WK5, and WK7).

PO7: Ethics: Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national & international laws. (WK9)

PO8: Individual and Collaborative Team work: Function effectively as an individual, and as a member or leader in diverse/multi-disciplinary teams.

PO9: Communication: Communicate effectively and inclusively within the engineering community and society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations considering cultural, language, and learning differences

PO10: Project Management and Finance: Apply knowledge and understanding of engineering management principles and economic decision-making and apply these to one’s own work, as a member and leader in a team, and to manage projects and in multidisciplinary environments.

PO11: Life-Long Learning: Recognize the need for, and have the preparation and ability for i) independent and life-long learning ii) adaptability to new and emerging technologies and iii) critical thinking in the broadest context of technological change. (WK8)

Sustainable Development Goals (SDGs)

SDG 1 - No Poverty: End poverty in all its forms everywhere.

SDG 2 - Zero Hunger: End hunger, achieve food security and improved nutrition and promote sustainable agriculture.

SDG 3 - Good Health and Well-being: Ensure healthy lives and promote well-being for all at all ages.

SDG 4 - Quality Education: Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all.

SDG 5 - Gender Equality: Achieve gender equality and empower all women and girls.

SDG 6 - Clean Water and Sanitation: Ensure availability and sustainable management of water and sanitation for all.

SDG 7 - Affordable and Clean Energy: Ensure access to affordable, reliable, sustainable and modern energy for all.

SDG 8 - Decent Work and Economic Growth: Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all.

SDG 9 - Industry, Innovation and Infrastructure: Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation.

SDG 10 - Reduced Inequalities: Reduce inequality within and among countries.

SDG 11 - Sustainable Cities and Communities: Make cities and human settlements inclusive, safe, resilient and sustainable.

SDG 12 - Responsible Consumption and Production: Ensure sustainable consumption and production patterns.

SDG 13 - Climate Action : Take urgent action to combat climate change and its impacts.

SDG 14 - Life Below Water : Conserve and sustainably use the oceans, seas and marine resources for sustainable development.

SDG 15 - Life on Land : Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss.

SDG 16 - Peace, Justice and Strong Institutions: Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels.

SDG 17 - Partnerships for the Goals: Strengthen the means of implementation and revitalize the global partnership for sustainable development.

PEOs

COs

COURSE OUTCOMES

ACTIVITIES

AY 2026-27

AY 2025-26

AY 2024-25

AY 2023-24

AY 2022-23

Faculty Info

Syllabus

KTU 2024 Syllabus

S1S2 BTech (2024 )

S3 to S8 BTech (2024)

KTU 2019 Syllabus

S1 & S 2 B.tech(2019)

INFRASTRUCTURE

LIBRARY

Nearly 100 books related to various disciplines are available. Both staff and students can hire books from here.

DATA SCIENCE / MACHINE LEARNING LAB

The Data Science and Machine Learning Laboratory is designed to provide students with hands-on experience in Data Science, Machine Learning, Artificial Intelligence, and programming. The laboratory consists of 72 high-performance computer systems equipped with modern software, development tools, and high-speed internet to support practical learning, research, and project development.

Key Features:

72 High-performance computer systems
Windows and Ubuntu operating systems
LCD Projector
High-speed Wi-Fi and LAN connectivity
Whiteboard and presentation facilities

INTERNET OF THINGS (IoT) LAB

The Internet of Things (IoT) Laboratory provides students with practical exposure to the design and implementation of IoT-based systems using *ARIES VEGA development boards*. Through hands-on experiments, students learn to interface sensors, LEDs, buzzers, switches, and other peripheral devices, develop basic programming skills using Python and embedded programming, and understand Linux commands and device communication. The laboratory enables students to acquire, process, and transmit sensor data for monitoring and control applications while introducing concepts such as automation, networking, and cloud connectivity. Overall, the IoT Laboratory bridges theoretical concepts with real-world applications and equips students with the skills required to develop intelligent systems for smart homes, healthcare, industrial automation, environmental monitoring, and smart city solutions.

Email :-aimlhod@vidyaacademy.ac.in

Phone :- 04885287751 / 04885287752 Ext : 176

Achievements

AIML students make mark at 24-hour National Hackathon

AIML students make mark at 24-hour National Hackathon YODHA

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AIML Students Shine in KTU S4 University Examination

The Department of Artificial Intelligence and Machine Learning (AIML), Vidya Academy of Science & Technology, proudly congratulates the...

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9+ SGPA in S6 University Examinations

The Department of Artificial Intelligence and Machine Learning (AIML), Vidya Academy of Science & Technology, proudly congratulates Sanmaya...

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Google Gemini Campus Ambassador recognition

Vidya student achieves prestigious Google Gemini Campus Ambassador recognition

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Placed students

From Classrooms to Careers! The Department of Artificial Intelligence & Machine Learning at Vidya Academy of Science and Technology...

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