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Introduction to Data Science - Period 1+2 Course Overview
OVERVIEW
CEA CAPA Partner Institution: Vrije Universiteit Amsterdam
Location: Amsterdam, Netherlands
Primary Subject Area: Mathematics
Instruction in: English
Course Code: E_EOR1_IDS
Transcript Source: Partner Institution
Course Details: Level 100
Recommended Semester Credits: 3
Contact Hours: 84
DESCRIPTION
This course covers the topics of introductory and elementary probability theory for data scientists and it promises a comprehensive understanding of theoretical and practical applications of probability theory by bridging the theory and practice.
In particular upon a brief discussion of combinatorial analysis, the students will be introduced to axioms of probability and the concepts of conditional probability and independence. Then, the concept of random variables including will be discussed. This part will mainly cover discrete and continuous random variables and jointly distributed random variables. Next, the concept of expectation in probability theory will be discussed. This part will include expectations of sums of random variables, moments, moments generating functions. Finally, students will be briefly introduced to limit theorems such as central limit theorems and laws of large numbers.
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.
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