Curricula

Objective

Time series analysis and forecasting are central in e.g. economic forecasting, weather modeling and energy measurements. You learn about different forecasting methods suitable for time series and you also learn how to visualize time series.

EUR-ACE Knowledge and Understanding
You know different forecasting methods suitable for time series.

EUR-ACE Engineering practice
You know how to apply time series analysis methods. You know how to visualize time series and identify anomalies. You know how to optimize hyperparameters.

Content

In this course, you will learn the key methods of time series analysis and forecasting, which are essential in fields such as economic forecasting, weather modeling, and energy measurement. You will explore various forecasting methods suitable for time series and learn to visualize time series data and identify anomalies. By the end of the course, you will be able to apply time series analysis methods and optimize hyperparameters in practical applications. This course equips you with the skills to utilize time series analysis across various domains.

Basics of time series analysis
Forecasting methods: ARIMA, RNN, LSTM
Visualization and interpretation of time series
Plotting time series
Modeling periodic data
Identification of anomalies
Hyperparameter optimization

Qualifications

Basics of Programming

Assessment criteria, satisfactory (1)

Sufficient (1)
You know forecasting methods suitable for time series. You know some time series analysis methods. You know how to visualize a time series. You recognize hyperparameters.

Satisfactory (2)
You know how to use some forecasting methods suitable for time series. You know analysis methods of time series . You can visualize time series and recognize some anomalies. You can edit hyperparameters.

Assessment criteria, good (3)

Good (3)
You know how to use some forecasting methods suitable for time series. You know how to use some analysis methods of time series. You know how to visualize time series and identify anomalies. You know how to use hyperparameters.

Very good (4)
You know how to use and compare forecasting methods suitable for time series. You know how to use analysis methods of time series. You can visualize time series and interpret anomalies. You know how to use hyperparameters and analyze the results.

Assessment criteria, excellent (5)

Excellent (5)
You know how to use forecasting methods suitable for time series and apply them to a business problem. You can recommend analysis methods of time series for specific business problems. You can visualize time series and recognize anomalies and trends. You know how to use hyperparameters and interpret the results.