B. Tech CSE (Artificial Intelligence and Machine Learning) | Sanjivani University (Best Private University)

About Us

The Department of Artificial Intelligence and Machine Learning at Sanjivani University is committed to excellence in education and research in AI and ML. We aim to give students a strong foundation in these technologies, preparing them to innovate and solve complex problems in various domains.

Our faculty members are renowned experts in AI and ML, bringing a wealth of knowledge and experience from both academic and industry backgrounds. They are dedicated to providing a comprehensive, hands-on education that equips students with the skills necessary to excel in a rapidly evolving technological landscape.

Programs Offered

Undergraduate Programs

B.Tech CSE specialization in Artificial Intelligence and Machine Learning

Postgraduate Programs

M.Tech in Artificial Intelligence
Ph.D. in AI and ML

Features of Department

IBM-Powered Syllabus

Our curriculum is powered by IBM, ensuring that our syllabus is aligned with industry standards and technological advancements. This collaboration provides our students with access to cutting-edge tools, resources, and real-world scenarios, enhancing their learning experience and preparing them for the demands of the global tech industry.

Research Areas

Our research encompasses a wide range of advanced topics within AI and ML, including:

NASSCOM: Partnering with NASSCOM to ensure our curriculum and research initiatives align with industry needs and trends.
CareerTiQ: Collaborating with CareerTiQ to provide our students with enhanced career guidance, job placement support, and industry connections
IBM: Partnering with IBM to integrate their expertise and resources into our programs, offering students access to cutting-edge technologies and real-world applications.

These collaborations help us offer internships, workshops, and placement opportunities that bridge the gap between academia and industry, ensuring our students are well-prepared for successful careers in the tech sector.

Facilities and Labs

Our department is equipped with modern facilities and labs designed to support both theoretical and practical work:

Advanced Computing Labs with high-performance GPUs
AI and ML Research Labs
Data Science and Analytics Labs
Robotics and Automation Labs

Industry Collaboration and Placement

We have signed Memorandums of Understanding (MOUs) with prominent industry organizations, including:

Advanced Computing Labs with high-performance GPUs
AI and ML Research Labs
Data Science and Analytics Labs
Robotics and Automation Labs

We promote interdisciplinary research and collaboration, working with industry leaders and research institutions to drive impactful innovations and discoveries.

Faculty

Our faculty members are distinguished professionals with extensive expertise in AI and ML. They are committed to mentoring students, guiding research initiatives, and contributing to the academic community through publications, conferences, and collaborative projects.

Student Life

The department fosters an engaging and dynamic student community, offering:

AI and ML Clubs and Societies
Workshops and Seminars
Hackathons and Competitions
Industry Visits and Networking Events

Join us at Sanjivani University and be a part of the future of AI and ML!

Vision & Mission

Vision of Department of AIML

To empower students globally and to be recognized as artificial intelligence and machine learning professionals driving industry innovation and impacting societal needs through cutting-edge technology.

Mission of Department of AIML

To transform professionals to become proficient in Artificial Intelligent methodologies and tools for global needs.
To collaborate with industry to exhilarate novel research and development in Artificial Intelligence & Machine Learning.
To foster cutting-edge innovation in Artificial Intelligence and Machine Learning leading the way in advancing technological solutions for sustainable development.

Program Outcomes (POs)

Engineering Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
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.
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 public health and safety, and cultural, societal, and environmental considerations.
Conduct Investigation 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.
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.
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.
Environment and Sustainability: Understand the impact of professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
Individual And Team Work: Function effectively as an individual and as a member or leader in diverse teams and in multidisciplinary settings.
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.
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.
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)

PSO1: Graduates will master fundamental and advanced AI and machine learning techniques, proficiently using tools like Python, R, IBM Watson, and TensorFlow to design and implement solutions for complex problems.
PSO2: Graduates will integrate AI techniques across diverse domains, applying them to robotics, cloud computing, and automation to develop innovative solutions for real-world challenges.
PSO3: Graduates will understand the ethical implications of AI, ensuring their solutions are developed with a focus on quality, safety, and responsible use.

Program Educational Outcomes (PEOs)

PEO1: Graduates will demonstrate a strong foundation in artificial intelligence and machine learning principles, enabling them to develop innovative solutions to complex problems in various industries and contribute to advancements in AI technologies.
PEO2: Graduates will apply ethical considerations and responsible practices in the development and deployment of AI systems, ensuring that their work addresses societal impacts, promotes fairness, and upholds privacy and security standards.
PEO3: Graduates will exhibit effective communication, teamwork, and leadership skills, collaborating with multidisciplinary teams and stakeholders to drive successful AI projects and contribute to the advancement of technology and research in diverse.

Department Profile