Coursera – Practical Time Series Analysis 2021-7 – Download

explanation

Time Series Analysis Practice is a time series analysis curriculum. Many of us are random data analysts. We have a background in science, business or engineering, but now we find ourselves in a situation where we have data that we have no formal training to analyze. This course is suitable for people who have little technical knowledge but would like to become more familiar with this method of analysis.

In real-world analysis of time series, we will look at data sets that represent sequential information, such as crop prices, annual rainfall, sunspot activity, and crop prices. We’ll also describe the process and look at mathematical models that can be used to generate this type of data. We’ll then look at a graphical representation that shows insights into the data. In the end, we learn how to make predictions that relate to smart cases and what might happen in the future.

Skills you can learn from real-world time series analysis:

  • Time Series Forecasting
  • time series
  • time series model

Course details:

Publisher: Coursera
teacher: Tural Sadigov and William Thiselton
Language:English
Level: Average
Duration: The course takes approximately 26 hours to complete.

Practical time series analysis:

Week 1
Week 1: Basic Statistics

Week 2
Week 2: Start time series visualization and time series modeling

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

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

Week 5
Week 5: Akaike Information Criteria (AIC), mixed models, integrated models.

Week 6
Week 6: Seasonality, SARIMA, Forecasting

Course Prerequisites:

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Practical time series analysis

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