Overview
Department Student Association (AAIE)
The Association of Artificial Intelligence Educatee (AAIE) serves as a dynamic platform
for students to explore, learn, and innovate in the field of Artificial Intelligence and Machine
Learning. AAIE plays a crucial role in bridging the gap between academic knowledge and
industry demands by organizing technical workshops, seminars, hackathons, and expert talks.
The association fosters a collaborative learning environment, encouraging students to work
on real-world projects, engage in research, and develop problem-solving skills. By providing
opportunities for networking with industry professionals, internships, and hands-on training,
AAIE helps students enhance their technical proficiency and career prospects. Through its
initiatives, the association aims to cultivate leadership, teamwork, and a passion for AI,
empowering students to excel in their professional journeys and contribute to advancements
in AI and ML technologies.
Being a member of AAIE provides students with invaluable opportunities to grow both
academically and professionally. Membership grants access to exclusive technical sessions,
industry interactions, and mentorship programs that enhance learning beyond the classroom.
Students can collaborate with like-minded peers on innovative projects, participate in coding
challenges, and gain recognition for their contributions in AI and ML domains. Additionally,
AAIE membership fosters a strong sense of community and professional networking, which
proves beneficial for securing internships, research collaborations, and job opportunities. By
being an active part of the association, students develop essential skills such as teamwork,
leadership, and critical thinking, all of which are crucial for a successful career in the ever-
evolving field of artificial intelligence.
Vision
To be a centre of excellence in Artificial Intelligence and Machine Learning with quality education and research, responsive to the needs of industry and society.
Mission
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To achieve academic excellence through innovative teaching-learning practice.
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To inculcate the spirit of innovation, creativity and research.
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To enhance employability through skill development and industry-institute interaction.
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To develop professionals with ethical values and social responsibilities.
Program Outcomes (PO)
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Engineering Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
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Problem Analysis: Identify, formulate, review research literature, and analyse complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences and engineering sciences.
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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.
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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 for complex problems.
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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.
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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.
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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.
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Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
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Individual and Team Work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
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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.
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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.
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Life-long 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 Educational Objectives (PEO)
Graduates will be
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PEO1: Competent professionals in the field of Artificial Intelligence and Machine Learning to pursue careers in diverse fields and higher education.
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PEO2: Proficient in designing innovative solutions to real life problems that are technically sound, economically viable and socially acceptable.
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PEO3: Capable of working in teams and adapting to new technologies as per the society needs with ethical values.
Programme Specific Outcomes (PSO)
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PSO1: Hardware and hardware-software co-design: Ability to identify, design, simulate, analyse and develop AI and ML models, using modern engineering tools and programming languages.
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PSO2: Domain specific skills: Ability to work in the field of AI /ML Engineer, Data Scientist, Business Analyst, Product Analyst, Research Scientist and Robotics Professional.
Program Specific Outcomes (PSOs)
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PSO1: Programming and software development skills:
Ability to employ modern computer languages, computing environments, and standard practices for analyzing, designing, and developing optimal solutions to deliver quality software products.
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PSO2: Domain specific skills:
Ability to apply techniques to develop computer-based solutions in various domains like Artificial Intelligence, Machine Learning, Network Engineering, Image Processing, Web Technologies, and Data Sciences.
Career Scope
