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Introduction to Data Science

Description

Data Science is a scientific field that aims to extract knowledge and insights from data. In inductive practice one is interested to learn about the state of the world given some event, i.e., the data. Data Science is probability theory turned upside down. In this course we will learn about ``estimation'' procedures, in particular, maximum likelihood and the method of moments, and some of their theoretical properties. Furthermore, we learn about hypothesis testing. Then we apply both estimation and testing to a practical setting: linear regression analysis. Regression analysis is at the basis of many more advanced techniques that you will encounter during your Master. We will describe logistic regression as one possible extension.

 

PREREQUISITES
Introduction to Computational Science

 

REFERENCES

  • Statistical Inference, Casella and Berger, Duxbury, 2th edition.
    Available at https://fsalamri.files.wordpress.com/2015/02/casella_berger_statistical_inference1.pdf.

People

 

Wit E. C.

Course director

Ceoldo G.

Assistant

Additional information

Semester
Fall
Academic year
2019-2020
ECTS
6
Language
English
Education
Master of Science in Computational Science, Core course, Lecture, 1st year

PhD programme of the Faculty of Informatics, Elective course, Lecture, 2nd year (4 ECTS)

PhD programme of the Faculty of Informatics, Elective course, Lecture, 1st year (4 ECTS)