Other Helpful Resources for Implementation: Difference between revisions
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Back to [[Beginner's Guide to Computation in Statistical Research]] | |||
== Productivity Tools == | |||
{| class="wikitable" | |||
|+ | |||
!Title | |||
!Description | |||
!Technical Level | |||
!Relevance | |||
|- | |||
|[[ChatGPT and other LLMs]] | |||
|Overview of how to use LLMs for computing tasks | |||
|⭐⚫⚫⚫⚫ | |||
| style="background-color: #44ee88;" |'''All computing workflows''' | |||
|- | |||
|[[GitHub Copilot]] | |||
| Instructions for installing Copilot for your IDE. Copilot is an AI-powered code generation and editing tool. | |||
|⭐⚫⚫⚫⚫ | |||
| style="background-color: #44ee88;" | '''All computing workflows''' | |||
|- | |||
|[[Amphetamine]] | |||
|Tool for preventing your device from entering sleep mode while you are away | |||
|⭐⚫⚫⚫⚫ | |||
|Personal device workflows | |||
|} | |||
== | ==CMU Courses== | ||
The CMU Department of Statistics and Data Science provides a number of courses that will walk through many of the basic steps of building research workflows using code | |||
== | *[https://36-750.github.io/ 36-750], 36-708, and 36-707 are required PhD courses that cover implementations of common statistical algorithms in code. | ||
*[https://www.cs.cmu.edu/~nihars/teaching/10715Fa25.html 10-715] in the Machine Learning Department introduces students to common ML algorithms and their implementation in code. | |||
*Other courses pertaining to algorithms and software development can be taken depending on your specific research requirements and interest. | |||
==StatBytes Seminars== | |||
Starting in Fall 2024, the department has been hosting the StatBytes seminar series aimed at showcasing computing tools and methods that are useful for statistical research. Seminars occur a few times per semester and are advertised over email. If you are heavily involved in computational work, we highly encourage you to attend these seminar. You may also view | |||
[https://drive.google.com/drive/folders/1W1fkOW73dUCMVX-U-6gjMRrSMLXf4OYd?usp=drive_link past presentations] at any time. | |||
Latest revision as of 07:54, 10 April 2026
Back to Beginner's Guide to Computation in Statistical Research
Productivity Tools
| Title | Description | Technical Level | Relevance |
|---|---|---|---|
| ChatGPT and other LLMs | Overview of how to use LLMs for computing tasks | ⭐⚫⚫⚫⚫ | All computing workflows |
| GitHub Copilot | Instructions for installing Copilot for your IDE. Copilot is an AI-powered code generation and editing tool. | ⭐⚫⚫⚫⚫ | All computing workflows |
| Amphetamine | Tool for preventing your device from entering sleep mode while you are away | ⭐⚫⚫⚫⚫ | Personal device workflows |
CMU Courses
The CMU Department of Statistics and Data Science provides a number of courses that will walk through many of the basic steps of building research workflows using code
- 36-750, 36-708, and 36-707 are required PhD courses that cover implementations of common statistical algorithms in code.
- 10-715 in the Machine Learning Department introduces students to common ML algorithms and their implementation in code.
- Other courses pertaining to algorithms and software development can be taken depending on your specific research requirements and interest.
StatBytes Seminars
Starting in Fall 2024, the department has been hosting the StatBytes seminar series aimed at showcasing computing tools and methods that are useful for statistical research. Seminars occur a few times per semester and are advertised over email. If you are heavily involved in computational work, we highly encourage you to attend these seminar. You may also view past presentations at any time.
