Interview with Professor Ramanathan, IIITB


For the sixth article within the weekly sequence of Data Science Director’s Interview, we obtained in contact with Professor Chandrashekar Ramanathan, the Professor & Dean (Academics) & the Faculty-in-charge of Computing at IIITB. 

While the info science training market has soared over the previous few years, professor Ramanathan believes content material and construction of University programs ought to handle the altering panorama and {industry} necessities.

Professor Ramanathan is a college member at IIITB whose major focus areas embrace, information science, software program engineering, data convergence, semi-structured databases, and software growth. With over ten years of expertise in massive multinational organisations, he has co-authored a number of analysis papers on edge intelligence for industrial IoT, HDSanalytics, OAES, machine-readable ontology for instructing and so forth.

In this interview, he shared insights into the info science training market and the way universities can create a related industry-ready information science course.



Excerpts

AIM: Is India an essential marketplace for information science training? What’s IIITB’s contributions to this extremely promising sector?

Professor Ramanathan: The Indian data science market is in its progress part, and the Indian training market is working in the direction of assembly the potential alternatives and job choices within the nation. That being stated, we’ve got some strides to make to fulfil the promised numbers. The world is all the time trying as much as India for IT options, and I imagine this development won’t change within the close to future. This outlines the immense scope for progress so far as India’s information science training market is anxious.

IIITB realised the potential for providing on-line programmes early on. In 2016, we began providing on-line programs on Data Science. We additionally provided a Data Analytics programme titled ‘The Analytics Essentials’. This course began with a small batch of 30 college students, and subsequently, we partnered with Upgrad to extend this system’s attain. Here we provided two variations of this programme – Post Graduate Diploma in Data Science, meant for professionals new to this area, and Post Graduate Diploma in Machine Learning & AI, a complicated course designed for professionals working in analytics and associated areas. This program is carried out on-line and doesn’t compromise on educational rigour. Key components like common lectures, assignments, lab actions, tasks, and so forth., provided right here match the stature of these offered in all our on-campus applications. 

AIM: What form of challenges a college faces whereas instrumenting a knowledge science and analytics course?

Professor Ramanathan: ‘Relevance’ is a problem that universities and establishments face on a real-time foundation. Industry calls for and necessities are continuously altering, and it’s essential to ensure the course content material and construction handle the altering skilled setting. It turns into much more essential since most information science college students are professionals with related {industry} expertise. Therefore, when instructing working professionals, we’ve got to be cognizant of their work timing and make sure the content material is compact and simply understandable. 

AIM: What was the affect of the COVID pandemic on the info science training market? How can governments nudge extra college students to information science?

Professor Ramanathan: The pandemic and the work-from-home setting have offered the bandwidth and alternative for professionals to pursue on-line programs. Of course, with a number of information science programs and alternatives out there available in the market, it might virtually seem just like the skilled is being compelled to take the course. But I really feel the state of affairs has merely allowed extra time and readability to decide on to upskill.

In phrases of presidency — insurance policies like NEP are instilling important realisation that we have to encourage multidisciplinary environments. However, to deal with modern-day issues, we want a well-thought mixture of STEM and different disciplines. It will contextualise issues and options and assist our college students stand out.

AIM: What are the key obstacles information and analytics training faces in India?

Professor Ramanathan: One of the preliminary obstacles was the supply of information and data-enabled methods. Analytics can’t perform with out information. IT enablement through the years helps overcome that specific problem. Now, we’ve got a constantly updating repository that may be simply used for training.

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AIM: What’s your recommendation for aspiring information scientists? What does the long run seem like for somebody who pursues information science now?

Professor Ramanathan: Technological experience augmented by sturdy domain knowledge is essential for an aspiring information scientist. One ought to have a transparent understanding of the foundations and practices of the {industry} earlier than making use of technological points to it. Be it automotive, BFSI, manufacturing or ecommerce, you could be a good information scientist within the area if you happen to couple domain-specific data with technical competence.

Ideal candidates would have a level or background data of pc science or data expertise. Data science is huge and should not swimsuit everybody. Therefore, it’s critical to have a flair to grasp the info, see patterns, analyse from completely different views and current findings to swimsuit the end-user whereas additionally being open to understanding the area. 

AIM: What’s your projections for AI and BDA training?

Professor Ramanathan: AI and Big Data Analytics (BDA) training can be virtually second nature to no less than the pc science professionals. In the following 5 years, they are going to be required to have fundamental data and consciousness of the topic. This multiplied by the variety of graduates we produce every year will in all probability be the scale of the market.

AIM: How does an {industry} partnership add worth to the college programs?

Professor Ramanathan: Industry partnerships are essential to academic establishments. The two key elements of a data science course are the basic conceptual basis laid by extremely certified academicians and {industry} stalwarts with on-ground experience and visibility. Both be sure that the important thing takeaways are past theoretical data and embrace sensible insights and understanding.

AIM: Do you assume an expert diploma can have an edge over quite a few on-line programs and MOOCs out there for information science fanatics?

Professor Ramanathan: We see a number of college students method us with this query. We all the time illustrate to our college students that if their major motive is to study, it doesn’t matter what course format is being pursued. In such a situation, the person is left with the burden of discovering the proper course with enough content material and knowledge. On the opposite hand, an expert diploma programme is backed by a trusted establishment and brings content material curated to swimsuit {industry} necessities and ensures skilled partnerships to learn college students.


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