- Master the basic features and functions of SPSS Statistics.
- Learn the basics of using SPSS in academic research.
- Take a deep dive into using SPSS for ML and AI.
- Use unsupervised learning models for pattern recognition.
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Overview
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Unlock the full potential of SPSS with this comprehensive learning path. Master regression analysis, predictive analytics, classification, decision trees, machine learning, and unsupervised learning. Learn to choose the right algorithms, uncover hidden patterns, and apply advanced techniques through practical examples. Start your journey to becoming a data analysis and machine learning expert today!
Syllabus
Courses under this program:
Course 1: SPSS Statistics Essential Training
-Learn all the essentials of using SPSS, a statistical software suite for data management and advanced analytics.
Course 2: Machine Learning & AI Foundations: Linear Regression
-Expand your data science skills by learning how to leverage the concepts of linear regression to solve real-world problems.
Course 3: Machine Learning and AI Foundations: Classification Modeling
-Classification methods are among the most important in modern data science. Learn classification strategies and algorithms for machining learning and AI.
Course 4: Machine Learning and AI Foundations: Decision Trees with SPSS
-Establish a strong foundation in ML by exploring the IBM SPSS Modeler and learning about CHAID and C&RT. This course is designed to help expand your data science skills.
Course 5: Machine Learning and AI: Advanced Decision Trees with SPSS
-Work toward a mastery of machine learning by exploring advanced decision tree algorithm concepts. Learn about the QUEST and C5.0 algorithms and a few advanced topics.
Course 6: Machine Learning and AI Foundations: Clustering and Association
-Learn how to use cluster analysis, association rules, and anomaly detection algorithms for unsupervised learning.
Course 1: SPSS Statistics Essential Training
-Learn all the essentials of using SPSS, a statistical software suite for data management and advanced analytics.
Course 2: Machine Learning & AI Foundations: Linear Regression
-Expand your data science skills by learning how to leverage the concepts of linear regression to solve real-world problems.
Course 3: Machine Learning and AI Foundations: Classification Modeling
-Classification methods are among the most important in modern data science. Learn classification strategies and algorithms for machining learning and AI.
Course 4: Machine Learning and AI Foundations: Decision Trees with SPSS
-Establish a strong foundation in ML by exploring the IBM SPSS Modeler and learning about CHAID and C&RT. This course is designed to help expand your data science skills.
Course 5: Machine Learning and AI: Advanced Decision Trees with SPSS
-Work toward a mastery of machine learning by exploring advanced decision tree algorithm concepts. Learn about the QUEST and C5.0 algorithms and a few advanced topics.
Course 6: Machine Learning and AI Foundations: Clustering and Association
-Learn how to use cluster analysis, association rules, and anomaly detection algorithms for unsupervised learning.
Courses
-
Classification methods are among the most important in modern data science. Learn classification strategies and algorithms for machining learning and AI.
-
Expand your data science skills by learning how to leverage the concepts of linear regression to solve real-world problems.
-
Work toward a mastery of machine learning by exploring advanced decision tree algorithm concepts. Learn about the QUEST and C5.0 algorithms and a few advanced topics.
-
Establish a strong foundation in ML by exploring the IBM SPSS Modeler and learning about CHAID and C&RT. This course is designed to help expand your data science skills.
-
Get up and running with SPSS Statistics. Learn how to work with the program to make data visualizations, calculate descriptive statistics, and more.
Taught by
Barton Poulson, Yash Patel and Keith McCormick