Open Data + Open Science + Data Science
Original motivation of this course: Our era of data - larger than ever and complex like chaos - requires several skills from statisticians and other data scientists.
- We must discover the patterns hidden behind numbers in matrices and arrays.
- We are not afraid of coding, recoding, programming, or modelling.
- We want to visualize, analyze, interpret, understand, and communicate.
After completing this course, the student (that's you!) will be able to
- understand possibilities of open science, open data, and open research tools
state-of-the-art, open and free software tools: RStudio and GitHub
- write dynamic documents (text + R code + results + graphs + tables) in R Markdown
- apply the principle of reproducible research and see its practical advantages
- visualize and analyze data sets with some fairly advanced statistical methods
- learn much more
of all this in the future (continuous learning)
- Organizers: Centre for Social Data Science (CSDS) and Doctoral School in Humanities and Social Sciences (HYMY) at the University of Helsinki (UH); School of Medicine at the University of Eastern Finland (UEF)
- Course page (pre-course info): https://courses.helsinki.fi/en/phd-302/137194141
- Platform: mooc.helsinki.fi (IMPORTANT: always use HAKA login if possible)
- Registration: WebOodi, but you may attend without such formalities (postdocs, lecturers, professors, alumni, guests) : MOOC (O=Open)
- Campus: you may attend anywhere : MOOC (O=Online)
- Teaching: Period #2 of UH: starting 26 Oct 2020, ending 7 Dec 2020.
- Class (mini-lecture + workshop): Weekly on Mon 10-12 in Zoom
- Tools: BYOD (bring your own device), e.g., a laptop (Windows / Mac / Linux)
- Prepare: to download and install R & RStudio & Git (all freely available)
- Schedule: assignments and peer-reviews of reports in a strict weekly schedule