PROBABILITY AND STATISTICS FOR DATA SCIENCE
- Course
- DASC545 - PROBABILITY AND STATISTICS FOR DATA SCIENCE
- Department
- Data Science - English - Master
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 8
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- -
- Prerequisite
- -
Course Description
The objective of this course is to provide the necessary knowledge of probability and statistics theory to solve a variety of data science problems. Fundamental concepts such as random variables, independence, expected values, standard errors and central limit theorem are covered. The tools that are frequently used in data science, like Bayesian inference and maximum likelihood estimation, are highlighted. Upon completion of this course, students will be capable of employing probabilistic and statistical models for data manipulation and using the statistical programming language R to perform statistical data analysis. Students will be able to suggest statistical techniques to estimate the parameters of probabilistic models that represent randomness in life. Students will also be prepared to use the new techniques in later machine learning courses.
PROBABILITY AND STATISTICS FOR DATA SCIENCE
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