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Given the diversity in educational background of our learners we have divided the series into seven parts. You can take the entire series or individual courses that interest you. If you are a statistician you should consider skipping the first two or three courses, similarly, if you are a biologist, you should consider skipping some of the introductory biology lectures. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. 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.

The courses are self-paced:

Course 1: Statistics and R Course 2: Introduction to Linear Models and Matrix Algebra Course 3: Statistical Inference and Modeling for High-throughput Experiments Course 4: High-Dimensional Data Analysis
Course 5: Introduction to Bioconductor Course 6: Case Studies in Functional Genomics Course 7: Advanced Bioconductor