Webinar: Introduction to Time Series Modeling – A Must-Know Concept for Data Scientists

We will review simple techniques and concepts used in time series modeling and what lies beyond those.

1. Stationarity Processes and Non-Stationary Processes, Dickey Fuller Test
2. Auto Regressive, Integrated, Moving Average Models
3. Multivariate Methods
4. What Lies Beyond

Why You Should Participate?

If you are new to data science and want to understand the basics of how time series modeling works, please join us in the Webinar.

Speaker

Dr. Vikas Agrawal

Vikas Agrawal works as a Senior Principal Data Scientist in Cognitive Computing for Oracle Analytics Cloud. His current interests are in automated discovery, adaptive anomaly detection in streaming data, intelligent context-aware systems, and explaining black-box model predictions. Vikas credits his continued learning to smart creative colleagues and mentors at Intel Corporation, Infosys Limited, and Oracle Corporation, where they researched and developed novel IP, products, and solutions to amplify humans.

Vikas received a B.Tech. in Electrical Engineering from the Indian Institute of Technology, New Delhi (1997), an MS in Computer Science and a PhD in Computational Modeling from University of Delaware, with post-doctoral research at California Institute of Technology (CalTech, Pasadena, CA) with colleagues from NASA’s Jet Propulsion Labs (JPL) for NSF’s FIBR.