Dr. Shruti Patil
BTech Gold Medalist (Computer Science),
MTech (IT) , Phd(Computer Science),
Head (Department of AI&ML),
Research Associate (SCAAI),
Associate Professor (CS&AI)
The technology of Artificial Intelligence and Machine learning is at the forefront of developing intelligent solutions to real-life problems. As our technology-laden society increasingly relies on digital data, machine learning is crucial for most of our current and future applications. Engineers with AI expertise would be needed in all the crucial domains such as Healthcare, Industry 4.0, Finance, Agriculture, Security, Law, and Environment Management in the near future. The Department of Artificial Intelligence and Machine Learning is established at SIT, Pune in 2021 to spearhead the development of globally competent engineers with AI knowledge and expertise in applying AI to challenging projects. The department, in collaboration with Symbiosis Centre for Applied AI (SCAAI), offers, programs in B.Tech (AI&ML) with an intake of 120 and M.Tech (AI&ML) with an intake of 30 students. A degree in this program is valuable and will make the student industry-relevant with apt knowledge and effectual interpersonal skills and communication skills.
The department has very competent faculty to teach specialized courses and elective courses like Explainable AI, Generative Adversarial Networks, and Multimodal AI.
The faculty is actively engaged in research and publications and has recognized projects to their credit in collaborations with industry, international universities, and research labs of high repute. The students have actively engaged in application-based projects as well as research projects with industry, R&D labs, research centers as well as international universities.
The programs offer the opportunity for the overall development of the students via Global immersion program, internships, industry co-teaching, certificate programs, workshops and project based teaching-learning pedagogy.
The department is also collaborated with Tech Mahindra (Makers Lab) for conducting specialized modules in Natural Language Processing, Computer Vision and also for research projects and internships.
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BTech Program Intake : 120 seats Brochure Link |
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Program Highlights
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Curriculum Highlights
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Department Best Practices
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Ingolstadt University, Germany
Indiana University Purdue University, Indianapolis, U.S.A
Nanyang Technological University,Singapore
Leibniz University,Germany
Berlin School of Law andEconomics
Telecom Ecole De Management,Paris
University of Adelaide,Australia
University of Malta,Malta
King Mongkut’s University,Thailand
University of Malaya,Malaysia
Ritsumeikan University, Japan
Hanyang University, SouthKorea
Western University, Canada
RUDN University, Russia
High performance computing lab with Nvidia GPU
Data Analytics and Visualization lab
Apple lab for multimedia and analytics
Deep Learning Lab with i7 machines and higher processing power
Computer Centre with machines in high configuration and licensed software required for teaching and research.
Dr. Ketan Kotecha, received, DUO- INDIA Professor fellowship under Asia - Europe Meeting (ASEM-DUO) with Brunel University, UK, 2020
Dr. Ketan Kotecha received, two Research grants worth INR 1.66 crores under Promotion of Academic and Research Collaboration(SPARC) scheme by MHRD, Govt of India, in collaboration with Arizona State University USA and University of Queensland, Australia
Dr.Shruti patil, Prof Pooja Kamat and Dr.Shilpa Gite received grant of 10 lakhs from Symbiosis International University for “Attention Span estimation using artificial intelligence in education 4.0”
Prof Prachi Kadam received grant of 10 lacs for building and leveraging indian food image data set for Calorie Calibration of Indian dietary
Prof Vijayshri Khedkar received grant of 10 lacs for Machine Learning Based Vibration Response Analysis of different Plates using Cymatics.
Passed Standard XII (10+2) or equivalent examination with Physics and Mathematics as compulsory subjects along with one of the Chemistry/ Biotechnology/ Biology/ Technical Vocational subject/ Computer Science/ Information Technology/ Informatics Practices/ Agriculture/ Engineering Graphics/ Business Studies from any recognised Board with a minimum of 45% marks or equivalent grade (40% marks or equivalent grade for Scheduled Caste/ Scheduled Tribes).
Direct Second Year Admission
Diploma Course/ Diploma in vocational Course from any recognized Polytechnic College as per AICTE norms.
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Passed Diploma in Vocational stream in the same or allied sector as per AICTE norms.
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Passed BSc Degree from a recognized university as defined by UGC [Obtained at least 45% marks (40% in case of candidate belonging to SC/ST category) and passed H.S.C with mathematics as a subject as per AICTE norms.
Know about the admission process for B.Tech
https://sitpune.edu.in/first_add_admission_procedure
Admission FAQs - B.Tech (Artificial Intelligence and Machine Learning)
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1. |
What is intake for B.Tech AI and ML? |
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The Intake for B.Tech AI and ML is 120 students. |
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2. |
What are the eligibility criteria for B.Tech AI and ML ? |
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B.Tech AI and ML Passed Standard XII (10+2) or equivalent examination with Physics and Mathematics as compulsory subjects along with one of the Chemistry/ Biotechnology/ Biology/ Technical Vocational subject/ Computer Science/ Information Technology/ Informatics Practices/ Agriculture/ Engineering Graphics/ Business Studies from any recognised Board with a minimum of 45% marks or equivalent grade (40% marks or equivalent grade for Scheduled Caste/ Scheduled Tribes). |
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3. |
What are Infrastructure facilities available for AI and ML? |
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GPU- DGX (DL WS P2587 4V100/256GB 32G) Server HP IDS Z8 G4 Workstation G4 90 1125W APJ Chassis |
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4. |
What are courses offered for B.Tech AI and ML? |
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Please refer to the programme structure section from the website.www.sitpune.edu.in |
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5. |
What are employment opportunities after completion of B.Tech AI and ML? |
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There are huge opportunities for different positions after successful completion of undergraduate and postgraduate programmes. Some of these opportunities are listed here a) Data Engineer b) Data Analyst c) Business Analyst d) Machine Learning Engineer e) Deep Learning Engineer f) Data Scientist g) AI Scientist |
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6. |
Any prior knowledge of statistics and mathematics required for learning Machine and deep learning? |
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No. We have incorporated the basics concepts of statistics and mathematics required for learning Machine and deep learning. |
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7. |
Any Industry Collaborations for B.Tech AI and ML ? |
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Yes. We are in collaboration with Tech Mahindra (Makers Lab) for conduction of few courses. Collaboration with other companies is also in progress. |
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8. |
What are the possibilities of a placement in a good MNC company? |
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Symbiosis institute of technology is associated with eminent companies such as google, Microsoft, amazon, and many more. So students have very good opportunities to get placed in such companies for their bright future endeavors. |
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9. |
Will contemporary technologies such as IoT, Cyber Security be covered along with AI-ML courses? |
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In the given curriculum, we have given opportunities to students to stream themselves or acquire the specializations in various areas such as Embedded-AI(AI + IoT), Cyber Physical Systems(IoT + AI + Security), etc. |
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10. |
Why are Artificial Intelligence technologies the talking point in the world today? |
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In ancient times, devices such as desk computers were not capable of doing high-level computations which were required to run machine learning applications. However, now, along with the availability of machines, these algorithms are capable of doing high-level computations and automate various processes. Furthermore, current algorithms such as chatbots are intelligent enough to handle communication with clients, perform critical tasks, banking transactions, etc. |
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What role AI will play in empowering industries? |
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In recent times, with the advent of technologies such as Industry 4.0, Healthcare 4.0, smart cities, smart buildings, etc, AI has a major role to play in changing the functioning of current industries. However, decision making roles will still be handled by humans with the help of AI tools. |
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12. |
How B.Tech in CS and AI/ML are linked or different from each other? |
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If we talk about software engineering, the sub-problem solutions are correct, however, it is not the same in machine learning — you find errors and the aggregate results can be dismay. In a nutshell, the world needs software engineers as much as they need machine learning engineers. Both the job roles need to work symbiotically with each other. Machine learning needs you to have a solid foundation in mathematics and statistics. However, software engineering is usually the default route most people often fall victim of. But the degree definitely prepares you for the bigger picture. Also, being a software engineer does not prevent you from becoming a machine learning engineer. Machine learning engineers think on these lines —space of models, deployment, and the impact. In a nutshell, the world needs software engineers as much as they need machine learning engineers. Both the job roles need to work symbiotically with each other. |
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13. |
How would you explain machine learning to a software engineer? |
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Software engineering is about developing programs or tools to automate tasks. Machine learning is all about automating automation! Machine learning is about finding the optimal instructions to automate a task. Machine learning algorithms are instructions for computers to learn other instructions automatically from data or experience. Therefore, machine learning is the automation of automation. |
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14. |
Why is AI a hot topic today? |
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A lot of things have aligned to make this an exciting time for major advancements in AI.
are capturing more signals from customer interactions.
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15. |
I have heard about AI. What is it exactly? |
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Artificial Intelligence (AI) is the concept of having machines “think like humans” — in other words, performing tasks like reasoning, planning, learning, and understanding language. While no one is expecting parity with human intelligence today or in the near future, AI has a big application in our day to day lives. The brain behind artificial intelligence is a technology called machine learning, which is designed to make our jobs easier and more productive. |
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16. |
Am I already using AI? |
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Yes. Almost everyone who has a computer, smartphone, or other smart device is already using AI to make life easier:
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17. |
What are the key highlights of B.Tech AI and ML? |
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18. |
How much will be the fees for this course? |
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Please refer to the Admission section--->Related year/ course--->Fee structure from the website.www.sitpune.edu.in |
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19. |
Whether a hostel facility is available? |
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Yes. Please refer to the infrastructure section from the website.www.sitpune.edu.in to view the hostel facilities. |
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20. |
Whether the student will have an internship during this course? |
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Yes. |
1) Joint Aston-SIT AL/ML Hackathon
Joint Aston-SIT AL/ML Hackathon was successfully completed during 16th – 18th May 2022 at Symbiosis Institute of Technology, Lavale, Pune.
This Hackathon is part of the Industry-inspired Transnational Education in Artificial Intelligence / Machine Learning project.
This project is supported by a Going Global Partnerships ± Exploratory Grant from the British Council. The Going Global Partnerships ± Exploratory Grant supports collaboration and innovation in teaching and learning and Transnational Education in Higher Education.
Dr. Amit Chattopadhyay from Aston was present for this event at SIT. Dr. Swati Ahirrao moved for Aston in this duration for Hackathon event.
2)International Faculty Guest lecture
Dr. Geoarge Ghinea from Brunel University delivered a lecture to AIML students on the “Applications of Machine Learning for Emotion detection”
3) Industry Tech Talks and Workshops for Students
The BTech and MTech students were given exposure to the latest AIML industry work via seminars and workshops by an eminent industry professional
Engineering Graduates will be able to:
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 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 the 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.
To apply the concepts of Artificial Intelligence and Machine Learning with practical knowledge in analysis, design and development of intelligent systems and applications to multi-disciplinary problems.
To provide a concrete foundation to the students in the cutting edge areas Artificial Intelligence and Machine Learning and excelling in the specialized areas like Natural Language Processing, Computer Vision, Reinforcement Learning, Internet of Things, Cloud computing, Data Security and privacy etc.
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GA 1 |
Scholarship: research, inquiry and lifelong learning |
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GA 2 |
Global citizenship: ethical, social and professional understanding |
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GA 3 |
Eco-literate: sensitivity towards a sustainable environment |
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GA 4 |
Employability: equipped with skills, attributes, leadership and entrepreneurial qualities that society needs; being capable of making a contribution to society through earning a living |
| Introduction to Python Programming | |
| CO 1 | Determine the data types of values and use indentation, comments in writing Python programs |
| CO 2 | Understand the built-in functions in Python and apply control structures |
| CO 3 | Create and manipulate items in lists and to perform string operations |
| CO 4 | Use methods associated with dictionaries and manipulate items in tuples |
| CO 5 | Demonstrate the use of built-in functions to navigate the file system and Create regular expressions that match text patterns |
| CO 6 | Demonstrate the implementation of instance variables, methods, and constructors with object oriented concepts |