MPSTME Mumbai

Prof. Sarada Samantaray is the Faculty-Data Science Associate Dean Academic at Mukesh Patel School of Technology Management & Engineering, Mumbai. He has a rich industry experience and an academic background which brings together experiential learning for the students. Read here what he has to say in his interview.

Data Science is still a developing field, how do you arrange the curriculum to teach the students all-important skills?

“It is an emerging field going through numerous changes as technology rapidly changes”

To address that, we keep our faculty members updated on the recent development trend in these fields. We bring industry experts to deliberate with them to find industry requirements to keep our students up to date with the industry trends. We also involve industry experts and foreign university faculty members to share their experience and knowledge continuously. To add, we keep on upgrading our projects and research as per the worldwide trend.

What are the latest subjects that you are offering in your institute/dept. which will help students outperform and stand apart from the crowd?

“We keep a pace with the latest trends”

We keep it very simple. We try to make our students independent to learn (so that they can learn themselves with ever-changing technologies). We focus more on Machine Learning, Deep Learning, Neural Networks. Students learn to work on small ML, DL, and NLP projects with hand calculation, then with excel sheets before they go for massive projects in some programming language like Python. We try to make them understand the necessary mathematical calculations behind the algorithms. Students start feeling the nuts and bolts of the math behind ML, DL, and NLP algorithms before they go to TensorFlow, Keras, or SciPy libraries along with optimization techniques.

What are the factors that make this program the best for the students to opt?

“We provide a learning atmosphere where students can work on various possibilities”

We ensure our students are fundamentally strong in Programming, Data Structure, and Algorithm, Database Management Systems in the first two years of the program. Go for Predictive Modeling, Machine Learning, Neural Networks, Deep Learning, NLP, Big Data, and Computer Vision. I think ours is one of the B. Tech programs in India with six months of industry internships embedded in the program and a capstone project to get a realistic feel of industry projects related to data science.

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What are some key aspects that make Data Science distinct from the field of Computer Science?

“I believe nowadays people do not need an expert in a core subject like Computer Science”

We want computer science engineers to help the organization with useful strategies. In our Data Science program, we try to make our data science engineering graduate a strong problem solver, knowing a bit from every field, which is required. We, a bunch of industry-experienced faculty members, can do that with our altogether four decades of industry experience. And again, the critical point is to “stick to basics and keep it simple”, which also happens to be our mantra.

What are some valuable insights into the program that you are offering at your institute?

“There are multiple aspects that we bring indifferently in our learning”

We offer various learning factors for the students to explore their potential such as:

  • 6 months of industry internship to gain pragmatic learning.
  • One-semester capstone work
  • Visiting faculty from industries and Virginia Tech USA and last but not the least
  • Department commitment to overall students’ development.

How do you plan on setting a benchmark as you are one of the few colleges who have started this stream?

“Our ranking in the country has given us a hallmark of excellence”

Some industry reviewers have already ranked institute and university imparting such programs, and we are among the top 5 in India at this point. The feedback we are getting from the industry will play a crucial parameter in defining these programs' futures, and we are continually working on them with industries. The feedback from distinguished faculty visiting and taking in-person courses for our students each semester makes us believe that we are among the best without any doubt.

What were the challenges that you faced while inculcating this program in your curriculum?

“Challenges are a part of learning”

There are many challenges which we have faced on our way. To name a few:

  • New and futuristic programs without any trendsetter
  • Parents and students believe in newer programs like Data Science
  • Most importantly, getting faculty members (including visiting faculties from industries) for this Data Science Program
  • Infrastructure and labs
  • Convincing industry to hire from these newer programs.

What are the types of projects that the students are working on through this program?

“Our students learn from hands-on experience through projects”

There are many in machine learning, deep learning, NLP, finance, and marking areas. However, we did some projects with industries. The Mumbai High Court awarded one such project for a US company. It was massive data (3.7 TB) of mixed format. Many images/videos were illegally copied for commercial gain, and our tasks were to gather significant forensic shreds of evidence to prove beyond doubt that copying took place. We involved around 25 students and six faculty members to work training machines to search for evidence patterns. We did 6-8% manually, and then the rest was done by machine using Big Data, the Relativity, and NexLP software. Students also did a project to detect oral cancer from images for a UK company called TumorTrace. Both the projects were paid projects, and students earn stipends while studying. That gave a huge boost to students’ confidence.

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What are the benefits and career options after pursuing this course?

“We strongly believe no business in the world will run without Business Analytics”

Every industry/field will have to use it to stay relevant. That makes our life simple. There is a shortage of well-learned Data Scientists and Artificial Intelligence professionals globally, and it is going to remain. We try to make our students best to face this massive challenge by using different tools, concepts, and working industry problems using ML/DL models to stay ahead. We believe industries will come searching for these kinds of students for a win-win situation, and hence jobs should not be or is not a problem for deserving and learning students.