QTM 350 - Data Science Computing

Welcome to QTM 350! This course introduces key tools in modern data science, focusing on three essential aspects: reliability, reproducibility, and robustness. We will cover command line interfaces and vim, version control with Git and GitHub, and literate programming using Quarto and Jupyter Notebooks. You will also learn about data storage and manipulation with SQL and Pandas, and parallel computing with Dask. We will explore artificial intelligence-assisted programming with GitHub Copilot and finish with Docker and containerisation.

We will meet every Monday and Wednesday from 14:30 to 15:45 in the Maths and Science Centre - E208.

Contact Information

Learning Outcomes

By the end of this course, students will be able to:

  • Use the command line interface to manage files and directories.
  • Work with version control systems to track changes in code and collaborate with others.
  • Create reproducible reports and presentations.
  • Use AI tools to assist with programming tasks.
  • Apply advanced techniques for data storage, manipulation, and querying.
  • Understand the basics of containerisation and parallel computing.

Website Structure

This website contains the course syllabus, lecture materials, tutorials, and assignments for the course. The course repository at https://github.com/danilofreire/qtm350 is similarly structured. Feel free to explore the materials and use them as needed.

Getting Help

If you encounter any issues with the course materials or have questions about the content, please:

  1. Check the course syllabus and this README for relevant information
  2. Review the lecture materials and tutorials in the repository
  3. Consult with your classmates or post in the course discussion forum
  4. Attend office hours or schedule an appointment with the instructor

Contributing to the Repository

While this repository is primarily maintained by the course instructor, everyone is welcome to contribute. Please feel free to suggest improvements or report issues by opening a GitHub issue, submitting a pull request, creating a discussion post, or contacting the instructor directly.

License

This repository is licensed under the MIT License. You are free to use, modify, and distribute the materials as needed, with appropriate attribution to the original source.

We look forward to an engaging and productive semester! Happy coding!

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