Introduction to data analysis for life scientists

About this programme

The course covers general rules and methodologies associated with data analysis in life sciences with a user perspective. This includes conventional statistical tools, handling and visualization of large and/or complex data sets (e.g., omics), image analysis, as well as an introduction to machine learning. Pitfalls and good practice associated with data analysis (e.g., bias) are also actively discussed during the course. - Identify and discuss potential pitfalls, like data bias, associated with analysis of complex data sets (module 1, 3) - Account for and use common statistical tools for data analysis (module 1, 2, 3) - Perform basic coding tasks and image processing using open source platforms (module 1, 2, 3) - Load and shape a data set to run existing computational tools and interpret their results (1, 2, 3) - identify and formulate a research question that should be addressed (module 3) Teaching in the course consist of lectures, seminars, project work and laboratory sessions. Examination of module 2 takes place through written lab reports and oral presentations. Examination of module 3 takes place through written reports and oral presentations. Course responsible Juliette Griffe, email: juliette.griffie@dbb.su.se Chemistry Section & Student Affairs Office: chemistry@su.se To follow your passion. To be close to international career opportunities. To explore city and countryside. In Stockholm you can really get the best of both worlds. Here we explain all the different steps you need to go through when applying to a course or programme.