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Time Series Analysis in Python

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$12

$6

49% OFF

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Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

Many domains can have time series data, such as stock prices or climate data. Data scientists must learn how to effectively work with these data. This course will show you how to perform time series analysis using Python. You will be able identify and use multiple time series models including cointegration, moving average, autoregressive and moving average. These models can also be forecasted, estimated, and simulated using Python's statistical libraries. These models can be used in many applications with a particular emphasis on finance.

Course Overview

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Virtual Labs

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International Faculty

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Case Based Learning

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Post Course Interactions

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Case Studies,Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

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Manipulating Time Series Data in Python

What You Will Learn

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In this course you'll learn the basics of analyzing time series data

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This course will introduce you to time series analysis in Python

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You'll learn about several time series models ranging from autoregressive and moving average models to cointegration models

Course Instructors

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Rob Reider

Consultant at Quantopian and Adjunct Professor at NYU

Rob is an Adjunct Professor at NYU's Courant Institute where he co-teaches a course on Times Series Analysis and Statistical Arbitrage. He is also currently a Consultant to Quantopian. He has been a ...

Course Reviews

Average Rating Based on 3 reviews

5.0

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Course Cover

$12

$6

49% OFF

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