Time Series Analysis in Python: Theory, Modeling: AR to SARIMAX, Vector Models, GARCH, Auto ARIMA, Forecasting
Sub Category
- Data Science
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Objectives
- Encounter special types of time series like White Noise and Random Walks.
- Learn about accounting for "unexpected shocks" via moving averages.
- Start coding in Python and learn how to use it for statistical analysis.
- Comprehend the need to normalize data when comparing different time series.
Pre Requisites
- Beginner data scientists looking to gain experience with time series
- People interested in quantitative finance.
- Aspiring data scientists.
- Programmers who want to specialize in finance.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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