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Praxis was set up in 2007 to become a trusted and influential educational institution with a mission to create industry ready global contributors. 'Praxis' – the translation of theory into practice – has been the guiding philosophy of the institution and has enabled its evolution into a contemporary, industry-facing Business School.
Praxis runs a one-year full-time Data Science program in Kolkata and Bangalore, and online programs in data science for working professionals. In addition, Praxis offers a two-year Full-Time AICTE Approved Post Graduate Diploma in Management from its Kolkata campus, and is launching a one-year full-time program in cybersecurity this year.
Praxis has two key strengths: a high-quality faculty team with impeccable academic pedigree and significant corporate experience, and an intimate industry connect. This enables the design and delivery of programs that are contemporary, relevant and effective. The Praxis one-year Data Science program has been consistently ranked second among Data Science programs in the country by a prominent publication like India Today and forums like Analytics Vidhya and Analytics India Magazine.
Praxis practices a learning-centered pedagogy, combining the methods of lectures, case-discussions, labs and projects in delivering its programs. The learning of concepts and techniques is contextualized with the help of real-world business problems.
The Post Graduate Program in Data Science with ML and AI (Formerly known as PGP in Business Analytics) aims at equipping students with the tools, techniques, and skills to enable them to grow into the role of Data Scientists.
The program comprises 500+ hours of in-class learning that covers the following:
• Technology Skills: An understanding of a wide range of tools and technologies (Python, R, SAS, Tableau, Hadoop, Spark, etc.) that are commonly used to extract, analyze and visualize data.
• Techniques: Knowledge of statistics, econometrics, applications of AI like machine learning and deep learning, optimization techniques and the ability to create predictive models.
• Domain Knowledge: A fair understanding of business functions like marketing, finance, operations and the application of Analytics in various verticals.
• Communication Skills: The ability to tell an effective story.
In addition, students engage in a Capstone Project that presents them with an opportunity to work on a near-real-world problem and use the tools, techniques they have learned to create sophisticated models.
The methodology emphasizes 'learning by doing' in which students apply concepts of statistics, machine learning, neural networks, AI, deep learning, etc. to a set of near real-world projects obtained from a variety of sources. Faculty use data available from Kaggle competitions to create assignments and student solutions are benchmarked against global leader-boards.
The class learns the principles of Big Data using Hadoop/ Spark and Python; migrating and porting machine learning applications from their laptops to the Amazon AWS platform to understand how to leverage the power of large clusters.
Domain analytics modules give students a foundation in the principles of functional domains like finance, human resources and marketing and in verticals like retail and telecom so that they can relate to the "business end" of business analytics.
Finally, a comprehensive, practice-based course in business communication prepares the students to 'tell the story' of the business problem and the consequent analytics solution – a skill all data scientists need.
Prof. Charanpreet Singh is one of the founders of the institute, and his primary role is to build an institution that understands and addresses the changing needs of both its primary stakeholders – students and industry. He had a remarkable 12-year journey so far. Praxis started as a business school in 2007 and as early as 2011 it started a full-time program in business analytics. There were two drivers for this decision:
• The institute leaders knew they had to differentiate themselves.
• They realized that the industry would need people with analytics skills in large numbers.
As part of the decision-making body at Praxis, Prof. Charanpreet tried to ensure that the institute keeps its intent honest. Every decision the institute makes has to be good for the students and the industry they are training them to join. This intent has driven frequent updating of the curriculum to keep it always relevant; selection and retention of high-quality faculty; forging of strong relationships with the industry. As a result, Praxis has been recognized as a top data science program for the last 8 years – despite the entry of many top institutes in this domain.
Praxis runs a solid, rigorous, serious program that responds with agility to changing technologies and business requirements. Some of its advantages are:
Full-time program
This ensures Praxis has candidates who are serious about Data Science, and ready to devote all their time to learning the concepts, applying them to business problems, experimenting with multiple techniques, and engaging in a strong, campus-based analytics ecosystem.
First-mover advantage
Praxis pioneered full-time teaching in Analytics in 2011. This affords the advantages of a deep understanding of the analytics education domain, industry expectations and what it takes to create effective analytics professional.
Robust industry association
Practitioners are involved in design and delivery, and ICICI Bank and PwC offer specific knowledge support. Praxis has created strong relationships with organizations seeking trained resources and has a wonderful group of loyal recruiters.
The comprehensive and topical curriculum delivered by top-class faculty
An experienced, well-qualified and committed faculty team helps Praxis deliver relevant content in collaboration with industry practitioners. Praxis, very simply, has the most experienced faculty in Data Science in the country, because the institute pioneered Data Science teaching.
The Praxis selection process and placement program
Praxis has put in place a comprehensive placement program that matches candidate competence to industry opportunity culminating in a consistent well-above 90% placement rate. The institute has created a fair selection process that lets in applicants who demonstrate the ability to think analytically and have a passion for problem-solving.
The strong and upwardly mobile alumni base
In the last 8 years, Praxis alumni who have performed with distinction in the corporate sector and given the young age of this industry, are already holding senior positions in their respective analytics teams. This network provides immense strength and guidance to succeeding batches.
Praxis is clearly the pioneer in the field of formal education in analytics in the country. The institute has contributed significantly in raising primary awareness and demand for analytics education and has been an early contributor of trained resources to the industry.
Over the years, Praxis has kept its focus on the full-time program, and has made changes to its content, methodology, assessment techniques, etc. to plug the gap between what it teaches and what the industry wants. Praxis is proud to be playing a critical role in the growth and enhancement of the Data Science education, and showing the way to new entrants in this field.
Talking about turbulent times, Prof. Charanpreet said it all boils down to the challenges Praxis faces in meeting the fundamental objective of the program – to get the right student, impart the right education and find them the right career opportunity.
A fallout of the massive buzz around analytics is that everyone is chasing an analytics career. As a responsible institute, Praxis has to put in filters in place so that it only let in those who have an aptitude for numbers and technology.
The domain is nascent and evolving rapidly – it's a challenge to get the right set of teachers who are fundamentally sound and eager to learn and adapt. The institute has been particularly fortunate in this respect so far but this is the key area that needs to be addressed for survival and growth.
Recruiters are getting to understand the domain better with time – full-stack Data Science JD's are being replaced with more reasonable sets of expectations. Visibility of a clear career path has been a challenge in attracting the best talent – but this is also being addressed with the evolution of the CDO and similar positions. Also, enterprises are happy to recruit from a standalone 9-month program as long as they get the talent they want.
Prof. Charanpreet believes that the data science industry is becoming more and more mission critical to most businesses – it helps industries make better decisions. Some of the drivers of growth for this industry are – significant increase in generation and collection of data (fuelled by IoT and mobile devices), advances in AI and big data technologies and techniques, adoption of cloud-computing and, most importantly, the realization by businesses that data is the new oil, and the basis on which they will have to compete in the marketplace.
The demand for data scientists is poised for exponential growth. According to a March 2019 article at knowledge@Wharton, there has been a 15-20 times growth in the demand for data scientists in non-tech traditional areas like education, marketing, banking, healthcare, and manufacturing to name a few.
As businesses invest more in AI and Big Data technologies, the biggest hurdle they face is the availability of capable, well-trained data scientists. Prof. Charanpreet thinks the data science education industry will grow on several fronts:
1. Undergraduate degree programs will introduce courses addressing the areas of AI, ML, DL, etc. as part of their regular curriculum – this has just started to happen.
2. Universities and colleges will launch postgraduate programs in this area – this is already happening.
3. There will be a large number of players offering part-time skills development courses for time-poor professionals.
4. There will be a spike in corporate training in this area – as businesses realize that data science is moving from the realm of the geeks to the desks of the managers.
"In terms of content, the future belongs to artificial intelligence. Subjects like artificial neural networks, deep learning, and cognitive learning will become increasingly important," he asserts.
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