Learning Codeless Machine Learning with KNIME
Offered By: LinkedIn Learning
Course Description
Overview
Machine learning is not only for software developers and engineers. With no-code and low-code solutions, this learning path introduces you to visual programming for machine learning and focuses on the KNIME suite. Walk through the process of analyzing, blending, and visualizing data, without any coding.
- Explore no-code solutions to modeling with KNIME.
- Understand the principles of predictive analytics and decision trees.
- Learn how to work with data for predictive modeling.
Syllabus
Courses under this program:
Course 1: Introduction to Machine Learning with KNIME
-Learn KNIME, a popular open-source platform for predictive analytics and machine learning. Discover how to use KNIME for merging and aggregation, modeling, data scoring, and more.
Course 2: Machine Learning and AI Foundations: Decision Trees with KNIME
-Expand your data science skills and establish a strong foundation in codeless machine learning.
Course 3: Data Science Foundations: Data Assessment for Predictive Modeling
-Explore the data understanding phase of the CRISP-DM methodology for predictive modeling. Find out how to collect, describe, explore, and verify data.
Course 4: Machine Learning and AI Foundations: Producing Explainable AI (XAI) and Interpretable Machine Learning Solutions
-Learn best practices for how to produce explainable AI and interpretable machine learning solutions.
Course 5: Machine Learning and AI Foundations: Advanced Decision Trees with KNIME
-Learn to go beyond the basic decision tree algorithms in KNIME by accessing WEKA, R, and Python-based decision tree and rule induction algorithms from within the KNIME platform.
Course 1: Introduction to Machine Learning with KNIME
-Learn KNIME, a popular open-source platform for predictive analytics and machine learning. Discover how to use KNIME for merging and aggregation, modeling, data scoring, and more.
Course 2: Machine Learning and AI Foundations: Decision Trees with KNIME
-Expand your data science skills and establish a strong foundation in codeless machine learning.
Course 3: Data Science Foundations: Data Assessment for Predictive Modeling
-Explore the data understanding phase of the CRISP-DM methodology for predictive modeling. Find out how to collect, describe, explore, and verify data.
Course 4: Machine Learning and AI Foundations: Producing Explainable AI (XAI) and Interpretable Machine Learning Solutions
-Learn best practices for how to produce explainable AI and interpretable machine learning solutions.
Course 5: Machine Learning and AI Foundations: Advanced Decision Trees with KNIME
-Learn to go beyond the basic decision tree algorithms in KNIME by accessing WEKA, R, and Python-based decision tree and rule induction algorithms from within the KNIME platform.
Courses
-
Learn KNIME, a popular open-source platform for predictive analytics and machine learning. Discover how to use KNIME for merging and aggregation, modeling, data scoring, and more.
-
Explore the data understanding phase of the CRISP-DM methodology for predictive modeling. Find out how to collect, describe, explore, and verify data.
-
Expand your data science skills and establish a strong foundation in codeless machine learning.
-
Learn to go beyond the basic decision tree algorithms in KNIME by accessing WEKA, R, and Python-based decision tree and rule induction algorithms from within the KNIME platform.
Taught by
Keith McCormick
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