Flowers

DataHour: Practical Time Series Analysis

Online 22-09-2022 07:00 PM to 22-09-2022 08:00 PM
  • 11243

    Registered

  • Knowledge and Learning

    Prizes

DataHour Recording

Find the resources used in the DataHour HERE.

About the DataHour:

Time series prediction is one of the most powerful methods used for predicting any variable which is time dependent. It helps in forecasting the future using the past time dependent data and is therefore applied in every domain. 

In this DataHour, Rahul Kumar will cover from the very basics of time series predictions and demonstrate the idea behind all algorithms like AR, MA, ARMA, ARIMA, SARIMA, ARCH and GARCH and how can these algorithms executed using in Python

Prerequisites:  Basic understanding of Python programming, pandas library and basic ML understanding.


Who is this DataHour for?

  • Students & Freshers who want to build a career in the Data-tech domain.
  • Working professionals who want to transition to the Data-tech domain.
  • Data science professionals who want to accelerate their career growth


Speaker:

Rahul Kumar

Data Scientist at Oracle

Rahul is currently working as a Data Scientist with Oracle. He has completed his post graduation in Data Science from IIT, Bangalore.

He is a Result-oriented and a certified Data Science professional with 7 years of experience in Data Science, Analytics and application development with  expertise in Machine Learning, Core Data Science and NLP. He 

Connect with Rahul at: https://www.linkedin.com/in/rahul-kumar-81b99397/

ALT

Please register/login to participate in the contest

Please register to participate in the contest

Please register to participate in the contest

Closed

Support

We use cookies essential for this site to function well. Please click to help us improve its usefulness with additional cookies. Learn about our use of cookies in our Privacy Policy.

Feedback

We believe in making Analytics Vidhya the best experience possible for Data Science enthusiasts. Help us by providing valuable Feedback.