Data Analytics Using KNIME
Training Provider: Temasek Polytechnic
Course Reference: TGS-2025060668
S$150
Original: S$500
Save S$350
About This Course
The course is designed with a top-down approach to data science projects, following the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology. It covers theoretical concepts of machine learning algorithms and evaluation metrics, which are then applied using KNIME for hands-on implementation.
What You'll Learn
Theory & Hands-on
- Introduction to CRISP-DM methodology
- Introduction to different types of commonly used machine learning algorithms and evaluation metrics:
.Classification Algorithms: Decision Trees, Logistic Regression or K-Nearest Neighbor (KNN)
.Clustering: K-Means
.Regression / Prediction algorithms: Linear Regression
.Model evaluation metrics
- KNIME Installation: brief walk through for installation of add-ons & extensions
- Implementation of machine learning algorithms using KNIME
- Introduction to CRISP-DM methodology
- Introduction to different types of commonly used machine learning algorithms and evaluation metrics:
.Classification Algorithms: Decision Trees, Logistic Regression or K-Nearest Neighbor (KNN)
.Clustering: K-Means
.Regression / Prediction algorithms: Linear Regression
.Model evaluation metrics
- KNIME Installation: brief walk through for installation of add-ons & extensions
- Implementation of machine learning algorithms using KNIME
Entry Requirements
Basic familiarity with data and analytics concepts
Course Details
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