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Academics


B.Tech (Artificial Intelligence and Machine Learning)

Dr. Swati Ahirrao

Dr. Shruti Patil
Phd(Computer Science), Head (Department of AI&ML),
Research Associate (SCAAI), Associate Professor (CS&AI)

Overview

Department of AI and ML in collaboration with Symbiosis Centre for Applied AI ( SCAAI) offers, program in B.Tech in Artificial Intelligence and Machine Learning with an intake of 120 , M.Tech in Artificial Intelligence and Machine Learning with an intake of 30 students. The primary aim of this centre is to spearhead the advancement and novel developments in various application areas and promotion of the advanced research and education in the field of Artificial Intelligence.

The department has very competent faculty to teach specialized courses and elective courses like Explainable AI, Generative Adversarial Networks, Multimodal AI and so on.

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.

Program Highlights:

  • Flexi credit Courses
  • Six month internship
  • Industry collaboration
  • Global Immersion Program
  • Special Diploma in Business management
  • Mentor- Mentee System and remedial teaching
  • Academic Curricula benchmarked with International Universities
  • Service learning activities
  • Industrial visits, Workshops, Technical events, Guest lectures
  • Learn Foreign languages
  • Tinker Lab
  • Best in class infrastructural facilities
  • Specialized Lab in AI, ML and data Science
  • Creative Thinking, Critical Thinking, Design Thinking, Entrepreneurship courses

The department has state of art computing facility as

  • High performance computing lab with Nvidia GPU
  • Data Analytics lab
  • IOT research lab
  • Computer Centre with machines in high configuration and licensed software required for teaching and research.

Department’s ongoing research and consultancy:

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. Sharnil Pandya received funding of 15,24,000 INR from DRDO for Ablation Studies on Reentry Capsule with Strong Coupling to flow dynamics (Parallel Computing using Python MPI libraries and building a supercomputer using Raspberry Pi) [On-going as CO-PI]

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.

Intake per Year

B Tech in Artificial Intelligence and Machine Learning
B Tech Program : 120
Departmental Brochure

Eligibility

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).


Know about the admission process for B.Tech

https://sitpune.edu.in/first_add_admission_procedure

FAQs

Admission FAQs - B.Tech (Artificial Intelligence and Machine Learning)

1.

What  is intake  for  B.Tech AI and ML?
 

The Intake for B.Tech AI and ML  is  120 students. 

2.

What  are the eligibility criteria for B.Tech AI and ML ?
 

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).

3.

What are  Infrastructure facilities  available for AI and ML?
 

GPU-  DGX (DL WS P2587 4V100/256GB 32G) Server 

HP IDS Z8 G4 Workstation G4 90 1125W APJ Chassis

4.

What  are  courses offered  for  B.Tech  AI and ML?
 

Please refer to the programme structure section from the website.www.sitpune.edu.in

5.

What  are employment opportunities after completion of B.Tech AI and ML?
 

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

6. 

Any prior knowledge of statistics and mathematics required for learning  Machine and deep learning?
 

No. We have incorporated the basics concepts of statistics and mathematics required for learning  Machine and deep learning.

7.

Any  Industry Collaborations for B.Tech  AI and ML   ?
 

Yes. We are in collaboration with Tech Mahindra (Makers Lab) for conduction of few courses. Collaboration with other companies is also in progress.

8.

What  are the possibilities of a placement in a good MNC company?
 

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.

9.

Will contemporary technologies such as IoT, Cyber Security be covered along with AI-ML courses?
 

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.

10.

Why are Artificial Intelligence technologies the talking point in the world today?
 

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.  

11.

What role AI will play in empowering industries?
 

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. 

12.

How B.Tech in CS and AI/ML are linked or different from each other?
 

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.

13.

How would you explain machine learning to a software engineer?
 

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.

14.

Why is AI a hot topic today?
 

A lot of things have aligned to make this an exciting time for major advancements in AI.

  • Processing power has improved at an amazing rate — there’s been a trillion-fold increase in performance over the last 60 years.
  • The cost of data processing has become more affordable.
  • There’s more data that needs to be analyzed because businesses

 are capturing more signals from customer interactions.

  • Application of AI has already improved consumer apps significantly — leading to further expectations in making life easier,  spurring the need for AI technical knowhow and R&D.

15. 

I have heard about AI.  What is it exactly?
 

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.

16.

Am I already using AI?
 

Yes. Almost everyone who has a computer, smartphone, or other smart device is already using AI to make life easier:

  • Siri and Cortana act as your personal assistants using voice  processing
  • Facebook recommends photo tags using image recognition
  • Amazon recommends products using machine learning algorithms
  • Waze suggests optimal driving routes using a combination of predictive models, forecasting, and optimisation techniques

17.

What are the key highlights of B.Tech  AI and ML?
 
  • Training by Industry
  • Consultancy projects
  • Latest Curriculum
  • Internship 

18. 

How much will be the fees for this course?
 

Please refer to the Admission section--->Related year/ course--->Fee structure from the website.www.sitpune.edu.in

19.

Whether a hostel facility is available?
 

Yes. Please refer to the infrastructure section from the website.www.sitpune.edu.in to view the hostel facilities.

20.

Whether the student will have an internship during this course?
 

Yes.



Programme/ Course Structure

PROGRAM OUTCOMES (PO)

Engineering Graduates will be able to:

  1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  2. 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.
  3. 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 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 modeling 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, and 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, such as, 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 a team, to manage projects and in multidisciplinary environments.
  12. 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)

  • PSO 1: 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.

  • PSO 2: 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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