• Online, Self-Paced
Course Description

Explore the various machine learning techniques and implementations using Java libraries, and learn to identify certain scenarios where you can implement algorithms.

Learning Objectives

Developing AI and ML Solutions with Java: Machine Learning Implementation

  • identify the critical relation between machine learning and artificial intelligence
  • specify the various classifications of machine learning algorithms
  • describe the differences between supervised and unsupervised learning
  • state how to implement K-Means clusters
  • describe how to implement KNN algorithms
  • implement decision tree and random forest
  • recall how to use and work with linear regression analysis
  • implement gradient boosting algorithms using Java
  • illustrate the implementation of logistic regression using Java
  • recognize the usage and objective of probabilistic classifiers for statistical classification
  • implement Naive Bayes classifier using Java
  • demonstrate how to use the K-Mean algorithm in ML applications


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.