CXOToday has engaged in an exclusive interview with Dr. Abhijit Dasgupta, SP Jain Global school of Management
- You have held key positions at education institutes throughout your professional career. What keeps you connected with the Education Sector and how has your experience been so far with the institute?
I have had experience as a Visiting Faculty at IIT Bombay, NIFT New Delhi, SPJIMR etc. during the last 25 years while I was having Leadership roles in Corporates in India / overseas. Since 2018, I am a full-time academic. Youthfulness and excitement to learn new things of students and the requirement to stay updated on the topics that I am teaching (among others) keeps me motivated – these are a couple of things that keeps me connected to the education sector. Till date it has been an intellectually satisfying experience for me.
- What interests you most in the areas of – Data Science right now?
My first engagement with Analytics started way back in 2003, when as a CIO, the organization that I was working with during that time, invested in SAS suite of products to generate effective business intelligence. I had been in touch with BI products and reporting long before that, but specifically there is a marked difference between Data Science and BI. In 2008, I had a client in MEA (I was working for a System Integrator during those days) who were looking at implementing Sports-Analytics for the athletics getting trained and that was a starting point for me in analytics, that that was probably the first time we used machine learning methods for prediction and prescriptions. Thereafter I had experience in media analytics (voice, video, text) while working for such clients.
In the last 20 years, data science has revolutionized itself and the evolution in technologies just in this space has been unprecedented. If you look at the innovation in tools, technologies, algorithms in just one field of computer science, I have not come across such massive changes in any other discipline. I think the innovations in Distributed Computing (Cloud Computing, Big-Data), Functional Programming, mainstreaming of algorithms such as k-means, vectoring of texts, and technologies helping image recognitions, speech recognitions etc. has moved the orbit way to high from where it all started in Statistics. In the process, I also witnessed high jacking of Regression techniques & KDD (a specialization area of Statistics) and renaming it as Machine Learning by computer scientists. It is the rapid change and innovations in Data Science that keeps me continuously engaged and interested in this field. These days, technologies like AutoML, TinyML, Zero Shot, Few Shot, Regenerative AI, Serverless Cloud are a couple of areas which I am finding quite intriguing.
- What should today’s data science students, in your opinion, learn more about if they want to succeed?
Now this is from my own personal experience. You don’t get anywhere in the data science field without a solid understanding in Coding. Students who are looking to join top companies engaged in data science, need to have real depth of understanding in data structures & algorithms. This is a major area of concern. Secondly, to succeed, students need to acquire skills and that is different from knowledge. Skills is ‘actionable knowledge’ and that is evidenced through hands-on knowledge of software products in the areas (such as SAS, Cloudera, Amazon, Palisade, TensorFlow, Tableau etc.). Top end coding skills supported by deep knowledge in two or three products would ensure success in seeking a position in a tier-1 company.
- How does the curriculum of SP Jain’s BDS course ensure that the students are being prepared for the future?
SP Jain’s BDS curricula integrates knowledge and skills and that’s one of the primary reasons why our students are highly competitive and likely more successful at their initial job-hunting.
- Why one should choose SP Jain School of Global Management to pursue their studies in Data Science?
Data Science could be taught from three points of view, viz., (a) Business Management (b) Statistics (c) Computer Science, and the order of difficulty is also exactly like that, Computer Science being the most difficult among the three. Interestingly, applied research output in the computer science field pertaining to data science vis-à-vis others are way higher. Every 6 months, we are finding newer research getting mainstreamed, the latest being ChatGPT AI engine. At SPJain, we teach Data Science from the point of view of computer science, which increases the rigour and skills level substantially. Next is an absolute focus on coding skills and top end market driven certified skills in AWS, Azure, SAS, Tableau, Spark et al. Interestingly, the faculty composition is also quite different including the teaching orientation. Our faculties are hired mostly with ivy-league education and that has no parallel in India (outside of old IITs), Thirdly, our Data Science programs are international leading to work rights in Australia, and therefore a student gets work rights in Australia and that does help to achieve a payback under 1 year after graduation.
- How do you try to bring in a practical approach towards subjects and make it industry oriented?
As I was mentioning earlier, it is the skills of a graduate that makes all the difference. For instance, one can study Regression in theory, but applying that to a machine learning level problem and solving that problem in a software environment is the key to success. This is the practical approach or lab orientation as we say. We provide the infrastructure (which are Cloud based), the data set (acquired from our industry / university associations), mentoring to the students whose course work would typically be 30% theory and 70% practical. Students also get to do internships (a minimum of 1 during the course, mostly 2) and that also provides a typical student with industry experience.
- What are the interventions and approaches you bring in apart from curriculum to train/teach the students?
We provide an international learning environment. Our faculties come from universities such as IITs, ISI, IISc, NYU, Columbia, Georgia Tech, Univ of Maryland College Park, etc., and they bring with them the skills orientation for teaching. Other part of the strategy is that we bring in leading technologists as a guest / visiting faculty (primarily from the United States) and put the students with them. When you have greatness in the classroom, it is likely, the perspectives drawn would be great altogether. We organize our workshops parallelly along the course track, where the hands-on workshop provides the lab environment for the course taught. For instance, we are probably the only Data Science program in this part of the world that teaches latest skills (in an workshop format) such as Microservices Engineering, Serverless Cloud, DevOps, MLOps, ML System Design, AWS/Azure Cloud, SAS etc. within the framework of the academic program. We also teach Competitive Coding all throughout the program apart from motivating the students to conduct research. Our UG students quite often publish with Elsevier, IEEE; and you will find our 1st year freshman students to be having a Hackerrank 5 star badge.
- What would you like people to know about your course they may not know?
Typical Indian parents & students community look at placements as a measure of success. Well, we do have a full-fledged placement team being a business school, but our endeavour is to skill a student at a level where s/he would not require assistance from us. In such a scenario, placement activities will only be requiring us to put a student across a recruiter and the student would find his way in. That’s the uniqueness, which I would like the audience to know. It should be noted, it is only the weak that needs support, the strong & capable ones can walk the path on her/his own, once we show them the way. That’s one of the reasons we do not advertise our 100% placement statistics, because they mean nothing without the quality of organization been shown alongside, and that we cannot do due to privacy and legal reasons.
- What do young people need to know before committing themselves to three years of Bachelor of Data Science?
I personally take most of the interviews (the last stage for an admit decision) and therein I try to find the motivation and preparation of the student to succeed. In my view, intelligence is one thing and that is God-gifted, but the ability to put your intelligence (aka use your brain) through disciplined hard work is quite another thing. Without hardwork one cannot achieve success (material or otherwise). Young people seeking to commit themselves to the program need to know success comes through hard work and no matter how intelligent you are, if you are not using your brain, you are unlikely going to be successful (in the way we define success for a university graduate)
- What are some of the biggest opportunities and challenges you see,in the AI sector both for higher education in general and for SP Jain Institute specifically?
Biggest challenge is that there are not enough faculties to teach AI. It’s a fairly complex and a very fast moving research based area. I see a lot of CVs stating AI qualifications, but a deep dive in such qualifications reveals that those are re-purposed (I hope you get the drift). That’s for the challenge. Opportunities are aplenty, but those are mostly in the Tier-1 companies; and I can vouch with certainty (with my experience as an investor and on the board of a few companies) that talents with right skills are just impossible to find these days.
- Any suggestions you would like to give to the current youth and the aspiring students? What would be your key message to someone graduating today?
Ofcourse ! The key message is a degree with a high GPA from a decent university will only give you an interview, but it is the skills that’s going to get you the job. I keep telling my students and mentees, look at an elephant – it has a beautiful tusk, and that’s for the show, but teeth beneath those beautiful tusks are the one that helps an elephant to eat. A degree is like the tusks, while skills are the teeth.
