In an age where reskilling has become a necessity and looming challenge, there is one institute that has been helping India’s professionals make a complete transformation into a data scientist and gain specific competencies in data science, machine learning and artificial intelligence. Founded in 2011, International School of Engineering (INSOFE) has the first mover advantage in India — being one of the earliest institutes to be set up in Hyderabad. Dr. Dakshinamurthy V Kolluru, founder president of INSOFE is an acclaimed academician and a thought leader. Dr Kolluru along with his illustrious team members has been playing a pivotal role in helping tech industry adopt AI and ML by providing corporate training and consulting services to global majors across several verticals.
INSOFE functions like an innovation ecosystem by addressing the three critical gaps in the Indian tech landscape – building a robust talent pipeline, promoting cutting-edge research in collaboration with the tech industry and sharing in-house expertise by training leading tech companies across the globe.
Over the last few years, one of the most important contributions of INSOFE has been training the next generation of data scientists who are now working at companies ranging from dynamic startups to Fortune 500 companies. INSOFE has a full-fledged department of Career Development and Placements, which has been helping companies hire the right talent and their students the right jobs. In the last 10 months, 440+ different companies have interviewed their students with an average of around 7 interviews per day.
Another key advantage of INSOFE over other institutes is its key centrality in the data science discipline, that has brought it global academic recognition. For the last few years, it has been consistently ranked alongside global universities like Stanford and Columbia for its flagship Big Data Certificate Program, making it one of the most sought-after data science institutes offering hands-on education of international standards. Besides the global recognition, INSOFE’s affiliations with the Language Technologies Institute of Carnegie Mellon University, Rennes School of Business and Siegal Lifelong Learning of Case Western Reserve have been a big draw for students from India and abroad who enroll in the full-time courses.
The strength of the institute lies in its faculty, with 14 full-time faculty and 7 adjunct faculty members holding PhDs from top global universities and decades of industry experience in US and India. The faculty members have filed scores of patents and hundreds of publications and developed multiple products which were incubated in INSOFE in the areas of Machine Learning, Blockchain, IoT, NLP, etc. For example, the faculty and students at INSOFE are working on a wearable device for learning driver behavior and are also building a robot with AI capabilities baked in.
Analytics India Magazine spoke to Dr. Dakshinamurthy V Kolluru to understand how INSOFE has been at the forefront of data science education and has built a robust in-house R&D practice with academicians working on real-world problems.
AIM: What was your vision for starting INSOFE?
Dr Kolluru: The cofounders of INSOFE were educated in India and then in the US. What we found there during our Masters was that there was more of an applied learning environment which was not happening in India. We decided to give such an education in India. This led to the inception of INSOFE.
Our vision was to create a place that provides cutting-edge transformative education of international standards. In the past 7 years, we believe we have been able to do that successfully.
We realized in the past few years that when it comes to application of high-end knowledge, even the industry is lagging behind. So, we decided to take this application-based knowledge to the industries and hence we have modified our vision now to help industry adopt AI and ML. We started as an institute which gives US-like classroom experience but now we are taking it to the corporate sector.
AIM: Throughout these years, a unique aspect of INSOFE has been its global reach with students and corporates from US, Middle East and Europe enrolling in the courses? What is that one key aspect that attracts students from abroad?
A: The reason behind our global identity is that if you take universities like MIT and Stanford, there the focus is on pushing R&D boundaries. On the other hand, we have been primarily an industry focused education institute. What we do is to pick up a new technology which is 6 months or 1-year old, simplify it such that industry can use it and benefit from it and then teach it to the industry. So, our emphasis has not just been doing R&D but actually taking it to the industry.
For example, recently there have been great advancements in how Text Mining is done and we already have the knowledge and gained industry level expertise on how to build the latest generation chatbots. The aim of INSOFE is to make knowledge available for the industry to implement easily.
And the second thing that we do is to implement a technology in the industry. For example, different roles in industry should learn technologies differently; an engineer should learn how to implement it and a CEO should learn how to develop a culture of acceptance for the technology. We pioneered the concept of role-based AI education and designed curriculum in AI and Machine Learning for each of the roles within an organization (CXO, non-tech managers, tech leads, engineers and citizen data scientists). Corporates worldwide are loving this unprecedented customization.
That is one of the reasons behind our global reputation and why we get invited by universities and corporates worldwide to help their students and employees. This is also the reason why quite a few students across the globe have travelled to take our courses despite the fact that we have never marketed these programs outside Hyderabad, Bengaluru and Mumbai.
AIM: INSOFE’s strength also lies in its faculty which also works on the R&D side. Can you tell us how they have been instrumental in shaping the talent pipeline in India?
A: The single biggest differentiator of INSOFE is its faculty and a strong in-house team of nearly 50 data scientists. They are on par with the best in the world. We have 21 faculty members of which 14 are full-time. All faculty come from top universities and are hands-on. They did their PhDs in top institutes and worked in top companies in key roles such as research, consulting, product development and at CXO level.
By design, we interact a lot with the industry, we keep ourselves constantly updated and work with the industry to solve key, business-related problems. Our robust connection with industry is what makes us different from others. If you take top institutes in India, most of the time goes into R&D, whereas here we solve problems which bother industry.
AIM: Is there any particular Indian example/use case that you can share?
A: More than a single use case, we work on average with 7 companies per month. More than 50% of them are repeat business. This shows how much they find the programs beneficial. Some of the Indian examples are (i) one of the largest steel manufacturers to train 4000 of their employees in Data Science, (ii) one of the largest ecommerce players where we have trained right from the founder, top leadership team and practicing data scientists, (iii) many software engineers from the Indian R&D centre of one of the world’s biggest IT companies, (iv) senior scientists of Indian defense labs, among many others.
AIM: As a thought leader, can you share how the analytics ecosystem in India has evolved and the shift towards emerging technologies – machine learning and deep learning?
A: In fact, we were the first to recognize this. Organisations used to treat AI and ML as specialisation of computer science even 4-5 years ago. Now they have recognised that it is not a mere specialisation of one branch but it is a way of solving a problem, making decisions and automating it. Yes, programming is a tool but it has nothing to do with specialisation in computer science.
The purpose of ML is not advanced research but how to take day-to-day decisions.
Organisations are now saying it is not enough if we have 20 people who do AI. They are asking how every engineer is practising AI and ML in the right way. They are treating it more as a quantitative MBA rather than a specialization in M.Tech. So that has been the fundamental shift. Earlier only a few companies were looking at AI and ML to solve some very specific problem. Now, almost every company is looking at how to learn and use AI & ML in every aspect of their functioning.
AIM: How important is it for educational institute to stay updated on the latest developments to educate the next generation?
A: EXTREMELY. I believe educational institutions should not just be updated but should be ahead. When I go to colleges, I get asked to make students ready for the industry. We always believe that industry should train to make them ready. But once you have done your post-graduation, you should be ahead of the industry and be ready to take things forward.
MITs and Stanfords are respected because they are a few steps ahead and the companies are looking up to them to learn. That is what INSOFE is trying to establish. We want to push the R&D boundaries and that is our primary passion and motivation here.
AIM: Can you describe INSOFE’s journey from inception to where it stands today as a global leader in data science education?
We have made our program evolution timeline accessible to everyone and here is link: https://www.insofe.edu.in/assets/insofe_pdf/Program%20Evolution_PDF.pdf
AIM: How has your personal journey been so far in the industry since you set up INSOFE?
A: When we started INSOFE, we had to go and tell the industry of the importance of AI and ML but today most organisations believe that AI and ML is relevant. They not only want to be trained but also work together in building the prototype. INSOFE is one of the very few institutes which delivers both education and consultation.
We do 4-day training programme for engineers and then we sit with the management to understand what type of prototype we need to build, and the next 5 months are spent on that.
Having built a strong globally reputed institute with completely Indian roots in India makes this journey worthwhile.
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