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AI is an assemblage discipline that covers everything related to making machines more intelligent. Machine Learning (ML) is a subset of AI and is commonly used along with AI. ML refers to an AI system that gets smarter over time by the self-learn-based algorithm. This course introduces modern AI and ML with equal prominence on introductory concepts and applies them to real-world problems. The course will explore the foundation of modern AI and pay adequate attention to the current innovation in machine learning techniques such as deep learning. The course provides AIML knowledge through lectures, hands-on sessions, case studies, and real-world projects.


The offered course intends to enclose

  • Ability to acclimatize and innovate tools and systems in the domains of Artificial Intelligence and Machine Learning.
  • Ability to explore research areasand pursue higher education in reputed institutions with AI Specialization.
  • Inculcate ethical and social responsibility to provide solution in the field of Computer Science and Engineering with AI/ML Specialization.

Future Prospects in AIML

On successful completion of AIML graduation students can choose specialization to pursue higher studies in domains like Expert Systems, Natural Language Processing, Neural Networks, Robotics, Fuzzy Logic Systems, etc. Many universities at Global, National and Local level offer specialized courses in M.S., M.Tech, M.E., MBA, and PG Diploma for AIML undergrads.

The course is a stepping stone to participate in digital India initiative by exploring and conducting research in AI based solutions in the domain of smart cities and Smart vehicles and many more.

Students with capitalist reflect can productizethe necessitate solutions in interdisciplinary domains.This course prepares students to explore domain such as Robotics, Expert Systems, Smarter and efficient solutions to the society in the domain of Healthcare, Agriculture etc.


Impart prime content education to develop technically proficient and socially responsible engineers in the emerging branches of AI.


  1. To provide students with a comprehensive education to prepare them for the rigors in the domain of AI.
  2. To establish a platform for academics, innovation, professional growth, and social interaction. 
  3. To encourage the capacity for lifelong learning necessary for career advancement. 
  4. To help build relationships with alumni and industry for the betterment of students' overall growth.

Artificial Intelligence and Machine Learning : PSO, PO’s & CO’s

Program Specific Outcomes (PSO)

  1. Students are exposed to cutting-edge trends and technology to prepare them for challenging work in the industry, higher education, and professional careers.
  2. Practice skills learnt in the field of Artificial Intelligence, Data Mining. Machine Learning, Cloud Computing, Optimization, Networking and Security, Deep Learning to different domains such as Healthcare, Education, Agriculture, Finance, Social Media etc.

Program Outcomes (POs)

  1. Engineering Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialisation to the solution of complex engineering problems.
  2. Problem analysis: Identify, formulate, research literature, and analyse 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, process to meet the specifications with 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 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. Some of them are, 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 ateam, to manage projects and in multidisciplinary environments.
  12. Lifelong Learnings: Recognise the need for, and have the preparation and ability to engage in independent and lifelong learning in the broadest context of technological change.

Course Outcome (CO)

Artificial Intelligence and Machine Learning : Faculty

Name Date of Joining Designation Qualification Status of Appointment
Ms. Rohini Gaikwad 15.02.2022 Assistant Professor B.E, M.E (CE) Full Time
Ms.Sneha Tapre 08.07.2022 Assistant Professor B.E, M.E (CE) Full Time
Ms.Pragati Akre 01.12.2022 Assistant Professor B.E (CE), M.E (IT) Full Time
Ms.Kajal Salekar 01.02.2023 Assistant Professor B.E (IT), M.E (IT) Full Time
Ms.Monali Deshmukh 15.02.2023 Assistant Professor B.E (CSE), M.E (CE) Full Time
Ms.Priyanka Dhavale 24.08.2023 Assistant Professor B.E (EXTC), M.E (Digital Systems) Full Time
Ms.Sushma Rathi 01.01.2024 Assistant Professor B.E (CE), M.Tech (CSE) Full Time
Ms.Smrithy C. S. 01.01.2024 Assistant Professor B.E (ECE), M.E (Comm.Systems) Full Time
Tejali Mhatre 02.01.2024 Assistant Professor B.E, M.E (IT) Full Time
Pranita Pingale 02.01.2024 Assistant Professor B.E, M.E (IT) Full Time
Manosha Shasikaran 08.01.2024 Assistant Professor B.E (ECE), M.E (EXTC) Full Time
Ms.Deepali Ganesh Jagtap 16.01.2024 Assistant Professor B.E (Electronics), M.E (Digital Systems) Full Time
Ms.Shubhangi Amit Deshmukh 16.01.2024 Assistant Professor B.E (EXTC), M.E (Digital Systems) Full Time
Ms.Supriya Ingale 19.01.2024 Assistant Professor B.E (Instrumentation Engg), M.E (Instrumentation & Control Engineering) Full Time
Mr.Hrishikesh Vichore 29.01.2024 Assistant Professor B.E (IT), M.S (Data Science) Full Time

Artificial Intelligence & Machine Learning : Technical Staff

Name Designation
Prasad Tambe Lab Attendant

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