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Time Series Analysis in Python

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Course Report - Time Series Analysis in Python

Course Report

Find detailed report of this course which helps you make an informed decision on its relevance to your learning needs. Find out the course's popularity among Careervira users and the job roles that would find the course relevant for their upskilling here. You can also find how this course compares against similar courses and much more in the course report.

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.

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Highlights

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Hands on training

Top 10 Percentile

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Pedagogy

Top 10 Percentile

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Rating & Reviews

Top 30 Percentile

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Parameters

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Pedagogy

Acquire all major Python Programming skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in Python Programming, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.

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Hands on training

This course stands out as one of the top 10 percentile options in Python Programming, offering unparalleled hands-on training. Learners gain practical experience and skills through immersive learning, preparing them for real-world challenges. It ensures a well-rounded skill set, catering to a range of learning preferences. With a focus on Hands on training as well as essential Case Based Learning and Virtual Labs, this course is tailored to meet diverse educational needs.

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Rating & Reviews

This highly acclaimed course is among the top-rated in Python Programming, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in Python Programming.

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

Manipulating Time Series Data in Python

What You Will Learn

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

This course will introduce you to time series analysis in Python

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

100%

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