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Beginning Data Science in R
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Table of Contents

1. Introduction to R programming. 2. Reproducible analysis. 3. Data manipulation. 4. Visualizing and exploring data. 5. Working with large data sets.6. Supervised learning. 7. Unsupervised learning. 8. More R programming.9. Advanced R programming.10. Object oriented programming.11. Building an R package.12. Testing and checking. 13. Version control. 14. Profiling and optimizing.

About the Author

Thomas Mailund is an associate professor in bioinformatics at Aarhus University, Denmark. His background is in math and computer science but for the last decade his main focus has been on genetics and evolutionary studies, particularly comparative genomics, speciation, and gene flow between emerging species.

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