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DSCI 521: Computing Platforms for Data Science

How to install, maintain, and use the data scientific software "stack". The Unix operating system, integrated development environments, and problem solving strategies.

Course Learning Outcomes

By the end of the course, students are expected to:

  1. Use the Unix command line to navigate their computer's filesystem.
  2. Define and distinguish between absolute file paths and relative file paths.
  3. Effectively use local and remote version control software (e.g., Git and GitHub) to organize projects and manage file versions.
  4. Create, edit and run reproducible literate Python and R code documents (e.g., reports and presentations) using Jupyter and RMarkdown.
  5. Write and edit Markdown and in-line LaTeX syntax within literate code documents.
  6. Define and correctly use a project working directory.
  7. Diagnose and troubleshoot programming and development environment problems, and explain how such problems can be avoided.

Assessments

This is an assignment-based course. You'll be evaluated as follows:

Assessment Weight Due Date Location
iClicker 2% iClicker and Canvas
Policies 1% 2024-09-04 23:59 PT Canvas
Setup 1% 2024-09-04 23:59 PT Canvas
Lab 0a 1% 2024-09-05 18:00 PT Gradescope
Lab 0b 1% 2024-09-05 18:00 PT Gradescope
Lab 1 11% 2024-09-07 18:00 PT Github & Gradescope
Lab 2 11% 2024-09-14 18:00 PT Github & Gradescope
Quiz 1 25% Week of 2024-09-17 ICICS Testing Center
Lab 3 11% 2024-09-21 18:00 PT Github & Gradescope
Lab 4 11% 2024-09-28 18:00 PT Github & Gradescope
Quiz 2 25% Week of 2024-10-01 ICICS Testing Center

Tip: Use the lecture learning objectives as beacons when studying for your quizzes!

Course preparation

Follow the installation guide for the UBC Master of Data Science Software Stack here: https://ubc-mds.github.io/resources_pages/installation_instructions/

Lectures

See the course lecture book.

Attributions

Materials were inspired, re-used and re-mixed from the following sources:

License

The UBC Master of Data Science DSCI 521: Computing Platforms for Data Science course materials here are licensed under the Creative Commons Attribution 2.5 Canada License (CC BY 2.5 CA). If re-using/re-mixing please provide attribution and link to this webpage.

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