Vision & Mission

Vision

To produce competent professionals in the field of AI & ML with excellent knowledge, technical skills and righteous values contributing to the growth of society.

Mission

• Empower our AI and Machine Learning community to lead with expertise and innovation.
• Position our department as a global hub for AI excellence through collaborative research and education.
• Connect academia and industry seamlessly to address real-world challenges in AI and Machine Learning.
• Cultivate a culture of continuous learning and innovation within our community.

Programme Educational Objectives (PEOs):

The graduates of AI and ML program will be able to:

• PEO 1:Graduates will proficiently apply AI and Machine Learning techniques to creatively address complex challenges, showcasing advanced problem-solving skills.
• PEO 2:Alumni will lead with ethical considerations, ensuring responsible AI development and contributing positively to societal and industry standards.
• PEO 3:Program completers will excel in interdisciplinary collaboration, effectively communicating and integrating AI solutions across diverse domains.

Programme Outcomes (POs):

• PO1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
• PO2. 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.
• PO3. 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.
• PO4. 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. 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.
• PO6.Theengineer 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.
• PO7. 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.
• PO8.Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
• PO9.Individual and teamwork:Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
• PO10. 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.
• PO11. 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.
• PO12. 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.

Programme Specific Outcomes (PSOs):

• PSO 1: Graduates will demonstrate proficiency in designing and implementing advanced AI and Machine Learning algorithms, showcasing the ability to develop innovative solutions for complex real-world problems.m.
• PSO 2:Program graduates will exhibit a strong foundation in interdisciplinary collaboration, effectively applying AI and Machine Learning techniques to diverse domains, fostering a holistic approach to technological solutions knowledge.

Infrastructure & Facilities:

The Department is well equipped with Cutting-Edge laboratories & facilities for trending technologies such as Deep and Machine learning Applications, Mobile Application Development, Algorithmic Implementations etc

Departmental Committees:

Board of Studies (BOS)

Board of Examiners (BOE)

Department Undergraduate Committee (DUGC)

Department Advisory Committee (DAC)

Programme Advisory Committee (PAC)

Industry- Academia Interaction

Memorandum of understandin MOU

AQMENZ AUTOMATION PRIVATE LIMITED:

Department of AI & ML has signed an MOU with AQMENZ AUTOMATION PRIVATE LIMITED. The objective is to establish a comprehensive collaboration aimed at enhancing industry-academia interaction through specialized training programs, internships, and placement opportunities. This strategic partnership will facilitate the development of a robust talent pipeline by offering students and professionals hands-on experience in the field of industrial automation. AQMENZ will provide state-of-the-art training modules and resources, enabling participants to acquire practical skills and industry knowledge. The internship program will allow trainees to work on real-world projects under the mentorship of experienced professionals, bridging the gap between academic learning and industry requirements. Furthermore, AQMENZ commits to offering placement support to successful trainees, thereby contributing to their career advancement and addressing the industry's demand for skilled automation experts. This MoU underscores a mutual commitment to fostering innovation, enhancing employability, and promoting sustained industry growth.

GIGA SKILL:

NMIT has partnered with Giga Skill through a Memorandum of Understanding (MoU) to offer extensive training, internship, and placement opportunities in the fields of machine learning and data science. This collaboration aims to bridge the gap between academic learning and industry requirements by providing participants with hands-on training programs that are designed and delivered by industry experts. The MoU includes a structured internship program where trainees will gain practical experience by working on real-world projects, thus enhancing their technical and professional skills. Additionally, AQMENZ and Giga Skill will work together to provide robust placement support, helping successful trainees to secure promising positions in the tech industry. This partnership reflects a mutual commitment to nurturing talent, fostering innovation, and preparing a skilled workforce for the future demands of the industry.