Prof. S Sudhindra of Tapmi Explains How PG Programme L.E.A.D. Helps In Creating Exceptional Leaders In The Digital Age
The Data Science field in India has matured beyond the “data analysis” stage. Organisations and analytics firms have been providing solutions to the business problems of their clients for a few years now. For instance, companies like Mu Sigma overcoming data availability constraints through the introduction of emerging technologies such as the IOTs and robotics. Data Science as a field has moved beyond the hype cycle long ago and is here to stay.  A practitioner can be future proof only through constant exposure to newer technologies and learnability. According to our study, a demand-supply gap exists with 97,000 analytics job openings available which are hard to fill. To fill this gap, T.A. Pai Management Institute (TAPMI) and Mu Sigma have joined hands to bring an industry-relevant analytics and decision sciences 11-month programme for executives and IT professionals known as Leadership through Analytics and Decision Sciences (L.E.A.D.). To gain more insights on the current Data Science scenario and understand how L.E.A.D. programs are helping the enthusiasts to become future-ready, Analytics India Magazine caught up with Prof. S Sudhindra, who is a Professor of Operations and Information Science and the Program Chair, Post Graduate Program in Leadership through Analytics and Decision Science (L.E.A.D.). “We put a high premium on learnability both during the selection process and subsequently during the program – this is non-negotiable.” – Prof. S Sudhindra, Professor of Operations and Information Science Tell us how has the journey in training the next generation of data science professionals been? For the institute, this has been an innovative and enriching experience. Normally institutions educate students whose future job profiles are not clear. Here we have a cohort whose placements are already decided and therefore the pedagogy – cases, assignments, and datasets – can be customized. At the same time, the students come from diverse backgrounds such as IT, manufacturing, finance, and even social sciences. This brings a richness of thinking to the classroom. It has been a pleasurable journey for everyone concerned. How the PG Program in L.E.A.D. can help to breed future-ready leaders? The L.E.A.D. program pedagogy ensures that the students learn to define the problem using first principles and come up with creative solutions. They are exposed to the cutting-edge analytics tools – but the rich ecosystem enables the creation of new tools whenever needed.  Our aim is not to create students who are future-ready, but those who create the future. Towards this, we have a rich mixture of courses such as system dynamics, design thinking, and a whole lot of management courses to augment analytics learning. How the last two batches of PG in LEAD went off, what are your expectations from the third batch? The first two batches have been a resounding success. The trainers at Mu Sigma and the faculty at TAPMI have both given us excellent feedback. The unique model of TAPMI faculty taking some courses during the Mu Sigma phase and Mu Sigma trainers visiting Manipal during the TAPMI phase to conduct workshops and hackathons has ensured a high degree of integration between classroom and practice and the students have enjoyed the learning process. As Data Science continues to evolve as a discipline, can you cite how LEAD has kept abreast of these developments to stay relevant in the market and maintain a competitive edge? There are two ways an academic institution such as TAPMI can make its programs keep abreast of evolving technologies: first is by tightly integrating with the practitioners. L.E.A.D. program has total and seamless integration with the best in the Data Science industry. The second is by taking part in the evolution process itself.  Our collaboration with Mu Sigma includes joint research, collaborative case development between the faculty of TAPMI and the practising experts at Mu Sigma. These will ensure that we do not just keep abreast of the evolution: our students and faculty also are the part of that evolutionary process. Can you share what contributed to the success of TAPMI and LEAD Program? Collaboration with an industry leader, Mu Sigma, in all aspects of the program, makes LEAD a powerful program. There is no equivalent model existing in India so far. The quality of students that this program has attracted so far has also contributed to our success. The top management of TAPMI is completely committed to the success of this program: all the resources of TAPMI such as the Bloomberg terminals and other laboratories are fully available to the students and the TAPMI’s best faculty take the courses. Many data analytics programs in India do not do well because they are not fulltime. LEAD, being a fully residential program ensures that the students are fully immersed in the learning experience. How the L.E.A.D. program can be differentiated from the other Data Science programs available in the market? In a normal Data Science program, in general, the students learn how to carry out analytics tasks. In the L.E.A.D. program, the students learn to lead teams in solving business problems through analytics and decision sciences, using a patented process called the Art of Problem Solving (AoPS).  In order to prepare the students for this, they are taught a variety of managerial courses in addition to the analytics and decision sciences courses. The outcome is a set of students who are competent in using analytical tools and are equally adept at understanding the business contexts and provide innovative solutions. A key aspect of the LEAD program is its placement.  Can you share details on that? Yes.  Every student who graduates in the first attempt will be offered a job at Mu Sigma.  The first batch is about to graduate with 22 students, and we are confident that every student will join Mu Sigma.  Please note that Mu Sigma, being a highly successful analytics company with a large number of Fortune 500 clients has a huge requirement of talented and skilled data scientists in its leadership roles.  Hence we wish to increase the batch sizes in the coming batches to meet the ever-increasing demand of Mu Sigma. For the benefit of readers, tell us- what is the typical profile of students who join L.E.A.D. program? The program is open to a student with 2 – 6 years of work experience. The students need not have an IT or analytics background.  In fact, we are looking for students from diverse backgrounds to enable multiple perspectives in problem-solving. It is important for the students to have an aptitude for learning analytics – they need to master several tools and languages such as “R” and Python. As a leading voice in academia, what more can be done to encourage students to take up STEM-related courses? TAPMI, while being a B-School, understands the importance of STEM in the country’s development. The introduction of this program is one major step towards operationalizing our commitment towards science and technology. B-Schools in India must introduce business-relevant STEM courses from the fields of AI and machine learning, IoT, and other emerging technologies as these have immense applicability in Operations, finance, marketing, and even HR.
The Data Science field in India has matured beyond the “data analysis” stage. Organisations and analytics firms have been providing solutions to the business problems of their clients for a few years now. For instance, companies like Mu Sigma overcoming data availability constraints through the introduction of emerging technologies such as the IOTs and robotics.  […]
AIM caught up with Prof S Sudhindra, Professor of Operations and Information Science and the Program Chair, Post Graduate Program in Leadership through Analytics and Decision Science (L.E.A.D.), TAPMI to gain more insights on the current Data Science scenario and understand how L.E.A.D. programs are helping the enthusiasts to become future-ready.
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["AI", "machine learning", "ML", "data science", "analytics", "Aim", "RAG", "Python", "R", "Go"]
A Technical Journalist who loves writing about Machine Learning and Artificial Intelligence. A lover of music, writing and learning something out of the box.