• Online, Self-Paced
Course Description

Classification models are used to categorize data into a fixed number of discrete classes or categories. The KNIME Analytics Platform allows you to load, explore, pre-process, and use your data to train classification models with little to no code.

In this course, explore classification models and the metrics used to evaluate their performance. Next, construct a KNIME workflow to load and view the data for a classification model. You will clean data, impute missing values, and cap and floor outlier values in a range. Then you will identify and filter correlated variables and you will convert categorical data to numeric values and express numeric variables. Finally, train several different classification models on the training data, evaluate them using the test data, and select the best model using hyperparameter tuning.

Upon completing this course, you will have the skills and knowledge to train, clean, and process your data and to use that data to train classification models and perform hyperparameter tuning.

Learning Objectives

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Framework Connections

The materials within this course focus on the Knowledge Skills and Abilities (KSAs) identified within the Specialty Areas listed below. Click to view Specialty Area details within the interactive National Cybersecurity Workforce Framework.