HomeEducationBridging Academia and Industry: SP Jain's Prof Abhijit Dasgupta on Collaborative Curriculum Development

Bridging Academia and Industry: SP Jain’s Prof Abhijit Dasgupta on Collaborative Curriculum Development

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Speaking to TechGraph, Prof Abhijit Dasgupta, Director Bachelor of Data Science discussed SP Jain School of Global Management’s collaborative efforts with industry partners to align the Bachelor of Data Science curriculum with current job market trends. He also talked about the institution’s commitment to enhancing employability through regular curriculum updates, ensuring students are equipped with the latest skills and knowledge demanded by the industry.

Read the complete interview:

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TechGraph: Can you provide an overview of the current demand for Bachelor of Data Science program graduates in the job market, particularly in industries relevant to big data and analytics?

Prof Abhijit Dasgupta: As of our last review in May 2023, the demand for graduates with a Bachelor of Data Science (BDS) degree is on the rise and projected to continue growing. In India According to McKinsey, there will be a shortage of more than 150,000 data scientists in 2024, which has led to an increase in demand for data science jobs and wages.

According to Indeed, data science, data analysis, and machine learning engineering are among the highest-paying job roles based on data science.

The sector showed 64% growth in demand, and around 2000 positions, on average, are open on recruitment portals like Indeed, LinkedIn, and Glassdoor; at any point in time. In India, the average salary is estimated at around Rs 14.50 lacs, in Australia about A$ 93,500 and in the US, it is about US$108,000. As of today, every industry sector is relevant to big data & analytics; and companies worldwide are slowly adopting data science to improve their business.

TechGraph: How do you prepare students to meet the demands of the rapidly evolving job market in data science and analytics?

Prof Abhijit Dasgupta: Preparing students for a career in data science requires a multifaceted approach that combines theoretical knowledge with practical skills and real-world experience. Theoretical fundamentals are required to be supported by product-specific skills.

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Some of the training areas are (a) Foundational Knowledge in mathematics, statistics, and computer sciences (b) Programming Skills in Python, SQL et al with some emphasis on working with APIs, and therein training is imparted in JavaScript, RestAPIs, JSON, developing APIs in Flask, etc. (c) Coding & Problem Solving: training students to solve problems in data structures & algorithms (d) Machine Learning & AI: imparting skills training on PyTorch, SK Learn, TensorFlow, SAS (d) Data Visualization in React-REDUX, PowerBI, Tableau (e) Technologies for Data at Scale, like Distributed computing, Cloud computing, distributed databases, NoSQL, Kafka, Spark, CI-CD frameworks, and to some extent functional management knowledge/domain skills to make a student ready for a job.

TechGraph: What specific skills or knowledge areas do employers often seek when hiring graduates from your program, and how does your curriculum address these requirements?

Prof Abhijit Dasgupta: This depends largely on the employer and their immediate objectives in using data sciences, and therefore there is no cookie-cutter approach here. Typically, if a student is well versed in the ML algorithms, and databases, comfortable working with PyTorch/TensorFlow, and can fetch and write into the big-data stack of the project; that is considered reasonable. Of course, he has to know Python well and his coding skills have to be top-class.

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Prof Abhijit Dasgupta: There is no shift, but adoption: this is how I would like to characterize the industry. They are learning, and academia is quite ahead of what the industry in general is.

TechGraph: Sustaining high placement rates is crucial for the reputation and success of any academic program. What strategies does your institution employ to ensure that graduates consistently secure fulfilling and relevant positions in the field of data science?

Prof Abhijit Dasgupta: The placement rate of an institution is reflective of the factor of employability, and employability depends on skills. We keep on updating our syllabus, especially the skills part to make the students employable.

Prof Abhijit Dasgupta: We primarily collaborate with big-tech companies and universities that are at the forefront of innovation in this area. In our experience, the industry does adopt the technologies supported by bell-weather companies (and they are mostly in the USA).

TechGraph: Lastly, do you support students in building their professional networks and gaining exposure to potential employers throughout their time in the Bachelor of Data Science program?

Prof Abhijit Dasgupta: At a college-grad level, networking does not work as much in India as it would in the USA. However, the institution must be well networked to attract the companies to recruit their students. Professional Networking works at a later stage of the career somewhere with at least 3 years of experience. At the level of a college grad, one has to get assisted by the institution or search for jobs / open positions on LinkedIn, Glassdoor, and other job portals.

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Krishna Mali
Krishna Mali
Founder, CEO & Group Editor of TechGraph.
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