This is a monorepo of course projects I enjoyed working on during my time at UT Austin.
The objectives of this repo are:
- To demonstrate my own ability to work in a R, C++, Go and Rust hybrid environment and produce statistically meaningful results.
- For future students to reference on what the courses are about.
It currently includes the following courses, I may post more in the future:
- SDS 322E: Element of Data Science
- Analysis of Occurrence Frequency and Patterns of Reported Drug Events in the US: A study of the FDA Adverse Event Reporting System (FAERS) using R and Rcpp. code base
- A Glimpse Into the State Of R Packages: A static analysis of CRAN and Bioconductor packages using a Go-R two stage pipeline.
- SDS 335: Scientific & Technical Computing
- SDS 375: Data Visualization in R
- JPN 330: Practical Readings in Advanced Japanese
Works intended to be printed (.Rmd, .pdf, .md, etc) are licensed under CC BY-NC 4.0
Other supplementary code is licensed under MIT
Course Syllabi are public access at UT Austin.
I chose to publish these projects/homeworks because one of these is true:
- I have your explicit permission to reproduce this.
- I believe I hold copyright to this work and I will not infringe your copyright (to your course materials) by reproducing it.
This boils down to the following points:
- Solely my own work: I did not receive direct input from you or other students when working on the published portion of this project other than to fit my idea into your grading requirements.
- Transformative: The project does not resemble any copyrighted course material more than headings, formats or trivial instructions.
- Highly Unique: Any future student should not be able to use only what I have published to reproduce my solution without more knowledge and effort than the original project/homework had asked for by itself.
However, if you are the instructor and you have a legitimate concern on one of my published projects, please send me an E-mail at yume [at] yumechi.jp and I will take it down.