Introduction
As you read this, freshly generated terabytes of would have been collected this second and stored in huge database management systems. With new devices & instruments of data collection, it has become increasingly essential for organizations to make use of data and bring innovation, productivity and better decision making. After all, data is useless until it is processed & explored.
To deal with this deluge of structured & unstructured data, companies are constantly looking out for Big Data Experts to utilize this data. But, the shortage of these resources is daunting and frustating for these companies.
In order to address this gap, SP Jain School of Global Management has proudly announced their Big Data and Analytics Program. Like always, we started getting queries about the program from our readers. Hence, we decided to meet their Director of the program – Dr. Mahendra Mehta. Here is a brief summary of our discussion with him:
AV: How did the program come into being? Do you see a lot of demand from your employers in this area already?
Dr. Mahendra Mehta
It hardly needs to be re-asserted that Big Data is poised to register high growth numbers in terms of employment opportunities in the next 10-15 years. We have observed that companies are struggling to fulfill the demand of data science professionals in their ranks. Almost all major universities in the US have initiated a master’s level program in big data and analytics. But what about an Indian student or professional who wishes to acquire the pertinent skill set for a career in big data?
A number of universities and institutes in India are offering a program in big data, however we realized that there is no program that is intensive and that focused on covering the fundamentals as well as the essential skill sets required to be employed as a data science professional.
We conceived the Big Data and Analytics Program at SP Jain School of Global Management as an intensive program which incorporates the essential concepts, knowledge and skill sets of Big Data which are highly sought by companies today. We do not want to create just tool experts who are adept at mechanical usage without knowing the fundamentals inside the box. Nor, do we want them to be theoretical masters with no practical skill sets. Therefore, we have laid equal emphasis on theoretical concepts, practical tools as well as hands-on case studies.
AV: Who is the target audience of this program?
I would say any and everybody who wants to make a career in the field of big data and analytics can participate. This field is expanding so rapidly that there will be openings across all levels of experienced candidates in a few years’ from now. This program is best suited for candidates having these three qualities:
First: Background in a quantitative field such as mathematics, economics, statistics, engineering, physics or chemistry. While an undergraduate level is preferable, even students who have studied mathematics till 10+2 level and who still remember their concepts are suitable for the course.
Second: Exposure to principles of programming. This need not be professional exposure. Even if the student has done some programming at school or college level, they are ready for the course. And even if they have not done any programming in school or college, a beginner’s course on programming in languages such as C++, Java or Python, offered on any of the online learning platforms such as coursera, edx or codecademy will lay the suitable programming background for them.
Third: A serious desire to learn big data and analytics. Our course is aimed at making students readily employable in the field of big data and analytics. We intend to equip them with a set of diverse skills. Learning them will require a serious commitment and investment of time and effort from the students. Our course is not for the casual learner. We do not provide an overview or just theoretical knowledge. We are offering an extremely intensive course with extensive coverage.
AV: What is the structure of the program – total classroom time, expectation from the candidate and the areas covered as part of the course?
The program is being offered in two formats – a full-time program, that runs for six months and a part-time program that runs for a year. The total number of contact hours for each format is the same – 400 hours. We designed the full-time format for those who have not yet embarked on their professional life yet such as students who have completed or are in the final year of their bachelor’s , masters or doctoral degree. Working professionals who want to take a break from their career to re-equip themselves with new skills are also welcome to join the full-time program. The classes of the full-time program will be held on weekdays i.e. Monday to Friday. For industry professionals who cannot afford to take a break, we have designed the part-time format. The classes of the part-time program will be held on weekends. There is no distinction between the two formats except the number of contact hours a week and hence the time-span of the program. None of the programs is superior or inferior to the other, they are just variations tailored to different needs of the students. 90% of the modules will have the same instructors on both the part-time and the full-time mode.
The program seeks to equip students with all the essential tools to turn them into data science professionals. Hence the syllabus is expansive and the coverage is deep. The modules can be broadly divided into 5 categories:
Basics: Statistics, Python, R, Relational DB & SQL, Excel, Tableau, Ubuntu
Tools & Technologies: Hadoop, Data warehousing, NoSQL, Cloud computing
Analytics: Machine Learning, Data Visualization,
Specialization: Natural Language Processing, Recommender System
General topics: Business metrics, Data science in start-ups, Design patterns in Statistical Computing, Basics of Problem solving, Stream processing, Dashboard, Data Security, Business applications in Data science, Future of Data Science
In addition to these technical modules, students will also undertake the professional readiness program, which is also undertaken by our MBA students. The professional readiness program trains students on the necessary interviewing and personal skills and imparts leadership, decision-making and other real-world business skills.
AV: What is the teaching methodology adopted for this Program – Online / Offline / Hybrid?
We believe that the best learning takes place in classrooms. For this reason, all modules will be covered in their entirety in classrooms and labs with actual face-to-face contact with professors. The professors will also be readily available outside class-room hours for the students during the duration of the module, and can be connected via email and phone after the completion of the module. Each lecture hall is equipped with state of the art recording equipment. Each lecture will be recorded and uploaded online for students for later reference.
AV: How much of the program is devoted to Industry Interaction and Live Project? Again are these professionals across the globe or just in India?
Roughly 20% of the program is hands-on and projects. In these modules, professionals working in big data will guide students on working in real-world problems incorporating live data.
AV: Is there a capstone project / industry project at the end of the course? If yes, how much time are people expected to spend on it?
Yes, we do have a live-project component of about 10% at the end of the program. That means about 40 hours will be devoted to an industry project at the end of the curriculum.
AV: Tell us about the Profile of the Faculty. Considering the fact that this program is supported by SP Jain Global, do we get to see faculties coming from abroad to commence classes?
The faculty is a mix of analytics industry professionals and renowned academicians. We have also invited faculty members from overseas universities to teach some of the modules. Some of our key faculty members are:
Dr Mahendra Mehta
Dr Mahendra Mehta is the director of the program and was formerly the Head of Analytics at Citibank, India. Dr Mehta has been a visiting faculty with S P Jain for over 10 years now. Dr Mehta has published several papers on machine learning, neural networks and was a radar scientist with HUL for 15 years. Dr Mehta has a PhD in electrical engineering from IIT Bombay.
Prof Sunil Lakdawala
Dr. Sunil D. Lakdawala, a Ph.D. from Yale University-USA and post graduate from I.I.T.-Mumbai is a visiting faculty with S P Jain Global Institute of management. He has over 20 years of experience in IT with various IT consultancy companies including CMC Ltd. and Tech Span India Ltd. He has specialized in the area of Business Intelligence System (Data Warehousing and Data Analysis Techniques like OLAP, Data Mining) and has a rich experience in consultancy, project execution and training in that area.
Mr. Tobias Setz
Mr. Setz has a Master and Bachelor of Science degree from ETH Zurich and is currently a Research Assistant at ETH Zurich, Institute for Theoretical Physics. He is one of the key members of the Rmetrics Association and maintainer of its broad open source software libraries. Mr Setz has conducted several R/Rmetrics Workshops in Europe which include “Computational Finance and Financial Engineering”, Basic R, Advanced R Programming and webinars on advanced statistics and visualization (Zurich & Mumbai)
Dr Satish Patil
Dr Satish Patil holds a PhD from the University of Minnesota, USA, and has 8+ years of experience in the field of Pharma & Healthcare domain. He is an inventor of 4 US patents over the last 4 years, has helped several companies & startups with Big Data & Analytics solutions using Big Data technologies, advanced machine-learning algorithms and statistical models. His core competency lies in Big Data, applied math and statistical analysis, machine learning, artificial intelligence and data visualisation.
AV: Is there a lab / virtual lab environment which S.P.Jain has created to support this course? If not, how is the student expected to learn in Big Data environment?
Yes, the course will be conducted at the dedicated labs and simulation centers at the new Lower Parel campus of S P Jain School of Global Management. The labs will enable students to work in a windows as well as Linux based environment and are equipped with high-end systems with all essential data science tools and technologies like Python, SQL, and Hadoop etc.
AV: How about placements? Would placement support be available for this program? Can we expect international placements as part of this program?
S P Jain extends placement support to all candidates who enroll in the BDAP program. We also offer a professional readiness program that equips them with the right skills to negotiate their way through the selection process. Like I said, before the curriculum has received an enthusiastic response from several companies working on big data and analytics. These include start-ups, established companies planning to start their own Big data business as well as specialist analytics consulting and outsourcing firms.
Note: The enrollments for current batch are closed. You can apply for the February batch 2016. Apply Here
End Notes
We would like to thank Dr. Mahendra Mehta and his team for sparing time for this interview. S.P.Jain School of Global Management has surely upped the ante by coming up with this unique offering. 6 month full time program is an interesting format and something being tried for the first time in industry. We thank S.P.Jain Institute of Global Management for joining the party and wish them all the best for running these courses.
If you have any query, concern, feedback regarding this course, please feel free to leave your response in the comments section below.
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Kunal is a post graduate from IIT Bombay in Aerospace Engineering. He has spent more than 10 years in field of Data Science. His work experience ranges from mature markets like UK to a developing market like India. During this period he has lead teams of various sizes and has worked on various tools like SAS, SPSS, Qlikview, R, Python and Matlab.
