Coursera – Practical Time Series Analysis 2021-7 – Full Version

Description

Practical Time Series Analysis is a training course on time series analysis. Many of us are random data analysts. We are trained in science, business or engineering, and now find ourselves in a situation where we have data that we have had no formal training to analyze. This course is intended for people with little technical knowledge who wish to familiarize themselves with this method of analysis.

In practical time series analysis, we will look at data sets that represent sequential information such as crop prices, annual rainfall, sunspot activity, and crop prices. We will also look at mathematical models that can be used to describe the process and generate this type of data. Next, we look at graphical representations that provide insight into our data. Eventually, we will learn how to make relevant predictions for smart cases and likely to occur in the future.

Skills you will learn in hands-on time series analysis:

  • Predict time series
  • Time series
  • Time series models

Course details:

Publisher: Coursera
Instructor: Toural Sadigov and William Thistleton
French language
Average level
Duration: Approximately 26 hours to complete the course

Practical time series analysis:

WEEK 1
WEEK 1: Basic Stats

WEEK 2
Week 2: Visualize time series and start modeling time series

WEEK 3
Week 3: Stationarity process, MA (q) and AR (p)

WEEK 4
Week 4: AR(p) process, Yule-Walker equations, PACF

WEEK 5
Week 5: Akaike Information Criterion (AIC), mixed models, integrated models

WEEK 6
Week 6: Seasonality, SARIMA, Forecasts

Course prerequisites:

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Practical time series analysis

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english subtitle

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