SIES | GST

Total Intake 60

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.

Objectives

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.

Message from the Head of the Department

Greetings!

It is my pleasure to welcome you to the Department of Artificial Intelligence and Machine Learning at SIES Graduate School of Technology, Nerul.

Artificial Intelligence and Machine Learning are transforming every aspect of our lives, driving innovation across industries and creating unprecedented opportunities for the engineers of tomorrow. As one of the fastest-growing engineering disciplines, AI empowers us to solve complex problems, enhance decision-making, and build intelligent systems that positively impact society.

Our department is committed to providing a strong academic foundation complemented by experiential learning and industry exposure. The curriculum blends core computing concepts with emerging technologies such as Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Generative AI, Large Language Models (LLMs), Explainable AI, and Intelligent Automation.

Through state-of-the-art laboratories, project-based learning, hackathons, research initiatives, internships, industry certifications, and multidisciplinary innovation, students gain practical exposure to the latest AI tools and technologies. We encourage them to explore emerging domains, publish research, participate in national and international competitions, and develop solutions that address societal and industrial challenges.

Beyond technical excellence, we emphasize innovation, ethical AI, critical thinking, teamwork, and lifelong learning. At SIES GST, we strive to nurture future-ready professionals equipped with the knowledge, skills, and values to lead the next wave of technological transformation.

I invite you to be a part of this exciting journey of learning, innovation, and excellence.

Best Wishes,

Dr. Kalyani Nikhilesh Pampattiwar
I/C Head of the Department
Artificial Intelligence and Machine Learning
SIES Graduate School of Technology, Nerul

Vision

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

Mission

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

Program Educational Objectives (PEO)

Develop leadership abilities for professional advancement.
Pursue higher education to learn and advance their careers.
Promote services in the field of Artificial Intelligence Engineering through excellent technical and communication skills.

Artificial Intelligence and Machine Learning : PSO, POâ€™s & COâ€™s

Program Specific Outcomes (PSO)

Students are exposed to cutting-edge trends and technology to prepare them for challenging work in the industry, higher education, and professional careers.
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)

Engineering Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialisation to the solution of complex engineering problems.
Problem analysis: Identify, formulate, research literature, and analyse 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, process to meet the specifications with consideration for the public health and safety, and the cultural, societal, and environmental considerations.
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.
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.
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 the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of 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. Some of them are, 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 ateam, to manage projects and in multidisciplinary environments.
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)

Academic Year 2024-25

Artificial Intelligence and Machine Learning : Faculty

Name	Employee/ Unique ID	Date of Joining	Designation	Qualification	Status of Appointment
Dr.Arundhati Das	40601	09.07.2024	Assistant Professor	B.E (CSE), M.Tech, Ph.D (CSE)	Full Time
Ms.Jasmin Hirani	40604	01.08.2024	Assistant Professor	B.E (EXTC), M.Tech (VLSI), Ph.D*	Full Time
Dr.Bhagyalakshmi	40628	06.01.2025	Assistant Professor	B.E (ECE), M.Tech (VLSI Design & Testing), Ph.D (Machine Learning & WSN)	Full Time
Ms.Sumedha Maindalkar	40629	06.01.2025	Assistant Professor	B.E (CE), M.E (CE)	Full Time
Ms.Ketki Martand Kausadikar	40636	03.03.2025	Assistant Professor	B.E (EXTC), M.E (EXTC)	Full Time
Ms.Gilu K Abraham		01.08.2025	Assistant Professor	B.Tech (ECE), M.Tech (Comm. Engg)	Full Time
Mr.Jegan Nadar		18.08.2025	Assistant Professor	B.E (IT), M.S (CS)	Full Time