Module Number MDZINF3310 |
Module Title Introduction to Statistical Machine Learning for Bioinformaticians and Medical Informaticians |
Type of Module Elective Compulsory |
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ECTS | 6 | |
Work load - Contact time - Self study |
Workload:
180 h Class time:
60 h / 4 SWS Self study:
120 h |
|
Duration | 1 Semester | |
Frequency | In the summer semester | |
Language of instruction | English | |
Type of Exam | Oral or written exam depending on number of participants; 60% exercise points as pre-requisite; a limited amount of exercise points may count as bonus points in the exam. |
|
Lecture type(s) | Lecture, Tutorial | |
Content | This lecture provides an introduction into statistical machine learning with a |
|
Objectives | The students are capable of explaining the most important terms, problems, |
|
Allocation of credits / grading |
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%) |
|
Prerequisite for participation | There are no specific prerequisites. | |
Lecturer / Other | Eggeling, Pfeifer | |
Literature | Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani: An Introduction to Statistical Learning with Applications in R, Springer Texts in Statistics. Further books will be announced in the first lecture. |
|
Last offered | Sommersemester 2022 | |
Planned for | Sommersemester 2024 | |
Assigned Study Areas | BIOINFM2210, BIOINFM2510, INFM2510, MDZINFM2510, MDZINFM3110, MEINFM3210 |