'R' and Python Programming for Data Science, Analytics & AI

Program Fees: 44,000

Early Bird: 39,600 (after 10% discount)

Program Dates: August 14 - 18, 2018 (Full-time: 9 am - 6:00 pm daily )

Program Venue: India (further details to be communicated after registering interest)

Why 'R' and Python

  1. A good conceptual & application knowledge of the two most popular & widely used languages in the domains of Data Science & Analytics, Machine Learning and AI helps launch an individual for an exciting & rewarding career in these domains.
  2. Good first languages for learning the basics of easily readable, elegant code which looks like rudimentary English or simple, abstract Mathematics. 
  3. Both ‘R’ and Python allow the programmer to code quickly. Owing to their agile design and flexibility, these languages are used by several enterprises for a variety of other applications including web development.
  4. Data Science, Analytics, Machine Learning & AI are among the fastest growing and most rewarding domains for professionals and a grounding in both ‘R’ & Python is the ideal launchpad for a rewarding career in these domains.

Key takeaways for participants:

  • Equipping oneself for a rewarding career in Data Science and AI.
  • Getting a theoretical and application grounding of the two most popular languages used in Analytics, Machine Learning & AI.
  • Picking up two of the hottest and most sought-after skills currently for software development professionals.

Faculty - Dr. S. Das


Dr. Das graduated in Electrical Engineering and has subsequently done his Ph.D. in the same discipline, after doing his post-graduation in Control Systems.

He has several years of industry experience and is currently an Asst. Professor in the Department of Data Science for a private University, where, among various subjects, he has also been involved in teaching ‘R’.

He has a number of published papers in the domains mentioned to his credit and is a visiting scientist at the Indian Statistical Institute (ISI), involved in the areas of Statistical Quality Control & Operations Research. His research interests include Data Analytics, Stochastic Systems and Real-time Systems