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Home > Artificial Intelligence (AI) and Data Science

Total Intake 120

With the exponential growth in data, Artificial Intelligence and Data Science (AI & DS) has emerged as one of the most, dynamic, and productive careers in technology. It deals with scientific methodologies, processes, and techniques drawn from different domains like statistics, cognitive science, computing and information science to extract knowledge from structured and unstructured data. The Artificial Intelligence and Data Science program is designed to prepare students to gain practical knowledge of data analytics methods and apply it in interdisciplinary domain. It is designed to inculcate computational thinking to solve practical problems. The program covers variety of topics related to Statistics, Data Mining, Machine Learning, and Artificial Intelligence to equip the students with knowledge of data analysis techniques and data-centric computation to address problems that require large data.

Objectives

The offered program intends to develop

  • Understanding on collecting, categorizing, strategizing, analysing and interpretation of data in making various intelligent decisions in business applications.
  • Development of data driven solutions, data visualization tools and techniques to analyse big data.
  • Solving various computational and real-world problems using the concepts of machine learning and deep learning model.

Future Prospects in AI & DS

On successful completion, AI & DS graduate 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 AI & DS undergraduates.

Availability of enormous data and need to solve existing problems, in domains such as, Healthcare, Agriculture, Smart city, Smart Vehicles to name a few, there are ample opportunities for entrepreneurship. We, at SIESGST provide support to promote entrepreneurship by conducting awareness sessions and mentoring students.

Students with Research aptitude can also pursue it in interdisciplinary domain. Graduate students having an adequate amount of research experience along with an exceptionally great academic background can pursue a PhD.

Message from the Head of the Department

Artificial Intelligence (AI) and Data Science (AI&DS) has emerged as one of the most transformative disciplines of the 21st century, revolutionizing the way we live, work, and innovate. With the exponential growth of data and advancements in intelligent technologies, AI&DS has become the driving force behind digital transformation across industries, enabling data-driven decision-making, automation, and intelligent problem-solving.

The Department of Artificial Intelligence & Data Science at SIES Graduate School of Technology is committed to nurturing future-ready engineers who possess strong analytical abilities, technical competence, and ethical values. Our curriculum is carefully designed to provide students with a comprehensive foundation in Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Big Data Analytics, Cloud Computing, and emerging technologies. Through a balanced blend of theoretical concepts, hands-on laboratory experience, industry-oriented projects, internships, and research opportunities, we strive to prepare students to address real-world challenges with confidence and creativity.The department emphasizes experiential learning through industry collaborations, Centers of Excellence, technical workshops, hackathons, research initiatives, and innovation-driven activities. We encourage students to develop critical thinking, entrepreneurial spirit, and lifelong learning habits that enable them to adapt to the rapidly evolving technological landscape.

Our dedicated faculty members are committed to fostering academic excellence, research culture, and holistic personality development. Alongside technical expertise, we focus on instilling professional ethics, leadership qualities, teamwork, and effective communication skills, ensuring that our graduates emerge as responsible professionals and global citizens.

At SIESGST, we envision our department as a center of excellence in Artificial Intelligence and Data Science, producing competent engineers, innovative researchers, and socially responsible technologists who contribute meaningfully to society and the nation's digital transformation. We welcome aspiring students to be a part of this exciting journey of learning, innovation, and excellence.


Dr. Arathi Boyanapalli
I/C HOD AI&DS Department
Associate Comp. Engg. Department.
SIES Graduate School of Technology, Nerul, Navi Mumbai.

Vision

To provide quality Education in the field of Artificial Intelligence and Data Science to provide sustainable solution for the society

Mission

  1. To impart quality Education to meet the challenges in the field of Artificial Intelligence and Data Science.
  2. To inculcate modern technology usage to fulfil the needs of the society.
  3. To nurture lifelong learning skills to develop professional growth and meet industry expectations. 

Program Educational Objectives (PEO)

  1. Apply Artificial Intelligence and Data Science skill to solve challenging and multi-disciplinary domain.
  2. Imbibe students for life long learning skill and research to adapt rapidly evolving skill in Artificial Intelligence and Data Science. 
  3. Inculcate entrepreneurship and leadership skills for professional growth.


Artificial Intelligence and Data Science : PSO, PO’s & CO’s

Program Specific Outcomes (PSO)

  1. To analyse and apply logical and computational skills to solve Artificial Intelligence and Data Science problems.
  2. Implement Artificial Intelligence and Data Science techniques such as data analysis, machine learning, data mining, neural networks and design efficient algorithms using emerging technologies in the field.

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)

  • Course Outcome 2021-22
  
    Academic Year 2024-25




Artificial Intelligence and Data Science : Faculty

Name Employee/Unique ID Date of Joining Designation Qualification Status of Appointment
Ms. Rohini Gaikwad 40521 15.02.2022 Assistant Professor B.E, M.E (CE) Full Time
Ms.Deepali Ganesh Jagtap 40585 16.01.2024 Assistant Professor B.E (Electronics), M.E (Digital Systems) Full Time
Ms.Megha Jain 40592 18.06.2024 Assistant Professor B.E (IT), M.E (CSE) Full Time
Ms.Shiney Varghese 40631 20.01.2025 Assistant Professor B.E (EEE), M.E (Power Electronics and Drive) Full Time
Dr.Neethu Anna Sabu 40633 31.01.2025 Assistant Professor B.Tech (ECE), M.Tech (VLSI & Embedded Sys), Ph.D (Low Power VLSI Design) Full Time
Dr.Vidya Keshwani 40634 05.02.2025 Assistant Professor B.E, M.E (EXTC), Ph.D (Electronics) Full Time
Ms.Darshana Wajekar 40639 02.06.2025 Assistant Professor B.E (IT), M.E (CE) Full Time
Ms.Krishna Kartika 40640 05.06.2025 Assistant Professor B.Tech (IT), M.Tech (CSE) Full Time
Mr.Akshay Jadhav 01.07.2025 Assistant Professor B.E, M.E (Electronics), Ph.D* Full Time

Artificial Intelligence & Data Science : Technical Staff

Name Designation
Mr.Vinod Patil Lab Assistant
Mr.Anil Chaudhari Lab Attendant

Artificial Intelligence & Data Science: Laboratories

Data Science Lab
Security Lab
Programming Lab
Project Lab


Artificial Intelligence and Data Science : Student Development Programs

Purpose SIESGST ACM Student Chapter

  1. The Chapter is organized and will be operated exclusively for educational and scientific purposes to promote the following:
    • An increased knowledge of and greater interest in the science, design, development, construction, languages, management and applications of modern computing
    • Greater interest in computing and its applications
    • A means of communication between persons having an interest in computing
  2. The Chapter will serve students at SIES Graduate School of Technology and other interested persons in the community.
  3. The Chapter is chartered by ACM.

 

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