LEARNING OUTCOMES
After the course students will have a basic understanding of statistical data analysis methods that are used in various genetics, biomedicine, personalized medicine and digital health problems. Students will learn to apply various statistical methods in biomedical problems as well as presentation and team work skills.
Credits: 5
Schedule: 01.03.2024 - 31.05.2024
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Harri Lähdesmäki
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
The course introduces statistical methods for analyzing high-throughput biological data in various genetics and personalized medicine problems, including e.g. genetic association analysis, survival analysis, longitudinal modeling, biomarker identification and drug response modeling.
Assessment Methods and Criteria
valid for whole curriculum period:
Exercise work/Project assignments.
Workload
valid for whole curriculum period:
24 + 12 (4 + 2)
DETAILS
Study Material
valid for whole curriculum period:
To be specified in MyCourses at the start of the course.
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
SDG: Sustainable Development Goals
3 Good Health and Well-being
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language : English
Teaching Period : 2022-2023 No teaching
2023-2024 Spring IV - VEnrollment :
Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.