Introduction to Computational Methods in Biology (Instructor: Arend Hintze – CSE 801 at MSU, offered every fall semester).
Current class information:
Like in every other science advances in computing increase the amount of data scientists are confronted with. It becomes imperative for modern day research to be able to use computational tools, be it storing and analyzing data, doing statistics, or using computational models. This course will introduce students to computational thinking and data literacy in Biology. This is not your typical programming class. Forget sorting lists, or compound interest examples – we are doing biology here. Think of it as the “Swiss army knife course for computational methods in Biology”! This course is intended for graduate students with little or no previous programming experience. There are no prerequisites, but you should bring a laptop to class.
The learning objectives for this course include:
- Students will learn to use the Python programming language and iPython notebook to do open and reproducible science
- Students will learn how to make publication ready data analysis and plots using spreadsheet data as well as data from SQL databases
- Students will learn hot to make computational models to understand ecosystems, game theory, and evolution
While there is no mid-term or final-exam, your grade will be based on weekly homework exercises, spontaneous quizzes, and an individual project that shows your newly learned skills. Expect an intense but very rewarding learning experience that will enable you to become a computational and data savvy scientist.