{"id":22328368,"url":"https://github.com/sijuswamy/computational-mathematics-for-data-science","last_synced_at":"2025-03-26T06:25:30.070Z","repository":{"id":260312246,"uuid":"869118407","full_name":"sijuswamy/Computational-Mathematics-for-Data-Science","owner":"sijuswamy","description":"Course Website for Computational Mathematics for Data Science","archived":false,"fork":false,"pushed_at":"2024-10-30T16:30:10.000Z","size":10665,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-31T08:15:02.304Z","etag":null,"topics":["computing","data-science","linear-algebra"],"latest_commit_sha":null,"homepage":"https://sijuswamy.github.io/Computational-Mathematics-for-Data-Science/","language":"JavaScript","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sijuswamy.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-10-07T18:43:57.000Z","updated_at":"2024-10-30T16:22:38.000Z","dependencies_parsed_at":"2024-10-30T17:38:21.675Z","dependency_job_id":null,"html_url":"https://github.com/sijuswamy/Computational-Mathematics-for-Data-Science","commit_stats":null,"previous_names":["sijuswamy/computational-mathematics-for-data-science"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sijuswamy%2FComputational-Mathematics-for-Data-Science","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sijuswamy%2FComputational-Mathematics-for-Data-Science/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sijuswamy%2FComputational-Mathematics-for-Data-Science/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sijuswamy%2FComputational-Mathematics-for-Data-Science/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sijuswamy","download_url":"https://codeload.github.com/sijuswamy/Computational-Mathematics-for-Data-Science/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245600330,"owners_count":20642282,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["computing","data-science","linear-algebra"],"created_at":"2024-12-04T03:12:25.808Z","updated_at":"2025-03-26T06:25:30.037Z","avatar_url":"https://github.com/sijuswamy.png","language":"JavaScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Quarto template for university courses\n\n\u003cfigure\u003e\n    \u003cimg src=\"./figures/icons/course_favicon.png\" alt=\"Image Created with DALL·E. Prompt: 'octopus-like alien futuristic teacher, abstract award-winning material design favicon blue flat colours'\"  role=\"presentation\" style=\"object-fit: cover;width:5em;height:5em;border-radius: 50%;\"\u003e\n    \u003cfigcaption\u003e\n        \u003cspan style=\"display:inline-block;font-size:0.3em;width:30%;\"\u003e\n        Image created with DALL·E. Prompt: 'octopus-like alien futuristic teacher, abstract award-winning material design favicon blue flat colours'\n        \u003c/span\u003e\n    \u003c/figcaption\u003e\n\n\u003c/figure\u003e\n\n\nA template for developing university courses using Quarto.\n\n**Real Examples:**\n\n- \u003cimg src=\"https://lse-dsi.github.io/DS101/figures/DS101_favicon.png\" style=\"object-fit: cover;width:1em;height:1em;border-radius: 50%;\" /\u003e [LSE DS101](https://lse-dsi.github.io/DS101/) - Fundamentals of Data Science\n- \u003cimg src=\"https://lse-dsi.github.io/DS105/figures/icons/DS105L_favicon.png\" style=\"object-fit: cover;width:1em;height:1em;border-radius: 50%;\" /\u003e [LSE DS105](https://lse-dsi.github.io/DS105/) - Data for Data Science\n- \u003cimg src=\"https://lse-dsi.github.io/DS202/figures/icons/favicon_DS202_200px.png\" style=\"object-fit: cover;width:1em;height:1em;border-radius: 50%;\" /\u003e [LSE DS202](https://lse-dsi.github.io/DS202/) - Data Science for Social Scientists\n- \u003cimg src=\"https://lse-dsi.github.io/ME204/figures/icons/favicon_ME204_200px.png\" style=\"object-fit: cover;width:1em;height:1em;border-radius: 50%;\" /\u003e [LSE ME204](https://lse-dsi.github.io/ME204/) - Data Engineering for the Social World\n\n**New to \u003cimg src=\"https://quarto.org/favicon.png\" style=\"object-fit: cover;width:1em;height:1em;\" /\u003e Quarto?**\n\nYou will need to understand the basics of the following features of Quarto to make the most of this template. It's worth it!\n\n- Check [their initial tutorial](https://quarto.org/docs/get-started/)\n- Then read about [Quarto websites](https://quarto.org/docs/websites/)\n- Check out also [Revealjs tutorial](https://quarto.org/docs/presentations/revealjs/) to learn how to create modern slides\n- Then move on to learn about [Quarto projects](https://quarto.org/docs/projects/quarto-projects.html)\n\nThere you go. You might be wondering how to put all of this to work. That is precisely why this template exists!\n\n# 💡 How to use this template\n\n\u003cdetails\u003e\u003csummary\u003e\u003cstrong\u003eOn GitHub:\u003c/strong\u003e\u003c/summary\u003e\n\n1. Click on the green button **Use this template** then **Create a new repository**.\n\n2. Wait for GitHub to copy the files and run the initial setup (you will see this on the **Actions** tab).\n\u003c/details\u003e\n\n\u003cdetails\u003e\u003csummary\u003e\u003cstrong\u003eLocally in your computer:\u003c/strong\u003e\u003c/summary\u003e\n\n3. Clone your newly created repository to your computer.\n\n4. Follow the instructions written below in the 🧰 [Dev Setup](#dev-setup) section.\n\n5. Skip the R or Python setup if you do not plan on working in one of these languages.\n\n\u003c/details\u003e\n\n\u003cdetails\u003e\u003csummary\u003e\u003cstrong\u003eStart editing the files:\u003c/strong\u003e\u003c/summary\u003e\n\nHere is a guide of the initial files you might want to modify to remove the sections that refer to the template, leaving only what is relevant to developing/updating the material of your course.\n\n6. Start by editing the `README.md` file carefully. \n    - Change the title\n    - Remove some of the sections\n    - Edit the Dev Setup instructions to cater to your needs.\n7. Add your **course code** and **course name** to the web pages\n\n    - If you are using VSCode, you can Ctrl + Shift + F (or ⌘ + Shift + F if you are on Mac) and replace all occurrences of `MY_COURSE_CODE` and `MY_COURSE_NAME` to the code and name of your course, respectively.\n    - Or, you can manually edit those in the following files:\n        - `_quarto.yml`\n        - `2023/index.qmd`\n        - `helpers/remove-nav.html`\n\n8. Then move on to `_quarto.yml`. Scan through this file to spot what you want to change. What pages do you want to keep or remove from your website?\n\n9. Next, modify the content of `index.qmd` and start working properly on your content pages under `2023/*`\n\n10. Visualise your changes by running the Quarto website locally:\n\n    ```bash\n    quarto preview . --render all --no-browser\n    ```\n\u003c/details\u003e\n\n# 🧰 Dev Setup\n\nOn top of the setup below, I also recommend you use [VSCode](https://code.visualstudio.com/Download) as your primary IDE.\n\n\u003cdetails\u003e\u003csummary\u003e🐍 The Python setup\u003c/summary\u003e\n\n## 🐍 The Python setup\n\n1. Install [Python 3.8](python.org) or higher on your computer.\n2. Install [anaconda](https://www.anaconda.com/products/individual) or [miniconda](https://docs.conda.io/en/latest/miniconda.html) on your computer.\n3. Create a new `conda` environment:\n\n    ```bash\n    conda create -y -n=venv-my-course python=3.10.8\n    ```\n\n    Never worked with conda environments before? Take some time to read [their documentation](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html). \n\n    💡 **Pro-tip**: replace `my-course` with your course code. Say, for example, `venv-ds105`.\n\n4. Activate the environment and make sure you have `pip` installed inside that environment:\n\n    ```bash\n    # the exact `activate` command will vary depending on your OS\n    conda activate venv-my-course \n    ```\n\n💡 Remember to activate this particular `conda` environment whenever you reopen VSCode/the terminal.\n\n10. Install required libraries\n\n  ```bash\n  pip install -r requirements.txt\n  ```\n\nNow, whenever you open a Jupyter Notebook, you should see the `venv-my-course` kernel available.\n\u003c/details\u003e\n\n\u003cdetails\u003e\u003csummary\u003e📊 The R setup\u003c/summary\u003e\n\n## 📊 The R setup\n\n1. Open a terminal and navigate to the root of this repository.\n2. Ensure you have **R version 4.2.2** or higher\n3. Open the R console in this same directory and install `renv` package:\n    ```r\n    install.packages(\"renv\")\n    ```\n4. Run `renv::restore()` to install all the packages needed for this project\n5. Whenever you install a new R package, run `renv::snapshot()` to save it on your renv.\n\n\u003c/details\u003e\n\n\u003cdetails\u003e\u003csummary\u003e\u003cimg src=\"https://quarto.org/favicon.png\" style=\"object-fit: cover;width:1em;height:1em;\" /\u003e The Quarto setup\u003c/summary\u003e\n\n## \u003cimg src=\"https://quarto.org/favicon.png\" style=\"object-fit: cover;width:1em;height:1em;\" /\u003e The Quarto setup\n\n1. Install [Quarto](https://quarto.org/docs/getting-started/installation.html) on your computer.\n2. Run the following command to start the website locally:\n\n    ```bash\n    quarto preview . --render all --no-browser\n    ```\n    This will read the instructions from `_quarto.yml` and render the website locally.\n5. Open your browser and navigate to `http://localhost:\u003cport\u003e/`. That's it!\n\n\u003c/details\u003e\n\n\u003cdetails\u003e\u003csummary\u003e🕸️ Publishing the website\u003c/summary\u003e\n\n## 🕸️ Publishing the website\n\nI recommend you set up a **GitHub Action** for this. Just follow the instructions in the official [Quarto instructions](https://quarto.org/docs/publishing/github-pages.html#publish-action).\n\n💡 This template already comes with a GitHub workflow setup. You can find it in the [.github/workflows/publish.yml_](.github/workflows/publish.yml_) file. You just need to rename it to `.github/workflows/publish.yml` (remove the underscore at the end)\n\n\u003c/details\u003e\n\n# 📟 Contact\n\n**✋ Questions? Suggestions?** If you are not sure how to do something with the template or have a suggestion for a new feature, start a [discussion](https://github.com/jonjoncardoso/quarto-template-for-university-courses/discussions).\n\n**🐞 Spotted any bugs?** Create a new [Issue](https://github.com/jonjoncardoso/quarto-template-for-university-courses/issues).\n\n**🖼️ Want to show us your courses?** Share a link to your public page on the [discussions page](https://github.com/jonjoncardoso/quarto-template-for-university-courses/discussions) or write me an e-mail.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsijuswamy%2Fcomputational-mathematics-for-data-science","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsijuswamy%2Fcomputational-mathematics-for-data-science","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsijuswamy%2Fcomputational-mathematics-for-data-science/lists"}