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In this course, students will understand what the Data Wise Improvement Process is and how it can help you improve teaching and learning.
This course is an introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences.
Through this part of the course, students will learn matrix algebra notation, matrix algebra operations, application of matrix algebra to data analysis and linear models.
This online course gives an introduction to Bioconductor and covers the structure, annotation, normalization, and interpretation of genome scale assays.
This online course bridges the gap between introductory and advanced courses in Python. It includes:Python 3 programming basics (a review)Python tools (e.g., NumPy and SciPy...
In this course students will learn various statistics topics including multiple testing problem, error rates, error rate controlling procedures, false discovery rates, q-values...
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