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Machine Learning for Econometrics and Data Science - Period 4
STEM in Amsterdam Program
Amsterdam, Netherlands
Dates: 2/1/23 - 7/1/23
Machine Learning for Econometrics and Data Science - Period 4
OVERVIEW
CEA CAPA Partner Institution: Vrije Universiteit Amsterdam
Location: Amsterdam, Netherlands
Primary Subject Area: Computer Sciences
Instruction in: English
Course Code: E_EOR3_MLEDS
Transcript Source: Partner Institution
Course Details: Level 300
Recommended Semester Credits: 3
Contact Hours: 84
Prerequisites: Intermediate level of Linear Algebra, Probability, Statistics and Econometrics
DESCRIPTION
The aim is to explore, study, and develop quantitative learning systems, methods, and algorithms with the purpose to improve the performance with learning from large data sets using powerful computers.
Vrije Universiteit Amsterdam (VU Amsterdam) awards credits based on the ECTS system. Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.
Course includes lab component.
Vrije Universiteit Amsterdam (VU Amsterdam) awards credits based on the ECTS system. Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.
Course includes lab component.