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Predictive Analytics and Machine Learning - Period 2
Business & Economics Program
Amsterdam, Netherlands
Dates: 8/15/25 - 6/27/26
Predictive Analytics and Machine Learning - Period 2
OVERVIEW
CEA CAPA Partner Institution: Vrije Universiteit Amsterdam
Location: Amsterdam, Netherlands
Primary Subject Area: Computer Sciences
Instruction in: English
Course Code: XB_0171
Transcript Source: Partner Institution
Course Details: Level 300
Recommended Semester Credits: 3
Contact Hours: 84
Prerequisites: The course “Statistical methods for data analysis” is a good preparation for this module. Some experience with Python or R is recommended.
DESCRIPTION
This course provides an in-depth introduction to the theory and application of predictive analytics and machine learning techniques. Students will learn about the fundamental methods used for building predictive models, including linear regression, decision trees, support vector machines, neural networks, and ensemble methods. The course will emphasize both the theoretical aspects of these techniques and practical applications using datasets. By the end of the module, students will understand the strengths and weaknesses of various predictive modeling techniques and be able to apply these methods effectively to real-world datasets. The skills gained in this course will serve as a foundation for more advanced topics, such as “Optimization and artificial intelligence”.