These courses make up two Professional Certificates and are self-paced: By the third course will be teaching advanced statistical concepts such as hierarchical models and by the fourth advanced software engineering skills, such as parallel computing and reproducible research concepts. You will need to know some basic stats for this course. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses.

If you are a statistician you should consider skipping the first two or three courses, similarly, if you are biologists you should consider skipping some of the introductory biology lectures. You can take the entire series or individual courses that interest you. Given the diversity in educational background of our students we have divided the series into seven parts. Throughout the course we will use the R programming language to perform matrix operations. We perform statistical inference on these differences. In this introductory online course in data analysis, we will use matrix algebra to represent the linear models that commonly used to model differences between experimental units. If you need computing resources for classroom teaching, please contact the Computing in Engineering Education (CEE) team to discuss your needs.Matrix Algebra underlies many of the current tools for experimental design and the analysis of high-dimensional data. Software available on Cannon (FAS RC account required)

Includes Matlab and Mathematica, among others Software from the FAS download site (Harvard Key required) For accounts and other information, visit:įollow the links below for instructions on using these software applications on Cannon: SEAS licensed software ABAQUS, COMSOL, and Lumerical: The best way of accessing the latest version of these software applications is on the FAS RC Cannon cluster.

Harvard mathematica