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@@ -5522,13 +5522,46 @@ <h2 class="anchored" data-anchor-id="day-4">Day 4</h2>
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</section>
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<section id="resources" class="level2">
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<h2 class="anchored" data-anchor-id="resources">Resources</h2>
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<section id="popular-package-resources" class="level3">
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<h3 class="anchored" data-anchor-id="popular-package-resources">Popular package resources</h3>
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<p>For a brief overview, or cheat sheet, of the most commonly used Python packages in data analysis, check out the following resources:</p>
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<ul>
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<li><a href="https://ccb-hms.github.io/workbench-python-workshop/index.html">Introduction to data analysis in Python</a></li>
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<li><a href="https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf">Pandas cheat sheet</a></li>
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<li><a href="https://www.datacamp.com/cheat-sheet/numpy-cheat-sheet-data-analysis-in-python">NumPy cheat sheet</a></li>
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<li><a href="https://matplotlib.org/cheatsheets/cheatsheets.pdf">Matplotlib cheat sheet</a></li>
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<li><a href="https://www.datacamp.com/cheat-sheet/scikit-learn-cheat-sheet-python-machine-learning">Scikit-learn cheat sheet</a></li>
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<li><a href="https://seaborn.pydata.org/examples/index.html">Seaborn examples with code</a></li>
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</ul>
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</section>
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<section id="other-python-courses" class="level3">
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<h3 class="anchored" data-anchor-id="other-python-courses">Other Python courses</h3>
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<p>We acknowledge that there are many other groups that have created excellent Python courses:</p>
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<ul>
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<li><a href="https://ccb-hms.github.io/workbench-python-workshop/index.html">Harvard CCB - Introduction to Data Analysis in Python</a></li>
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<li><a href="https://developers.google.com/edu/python">Google - Python Class</a></li>
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<li><a href="https://www.coursera.org/specializations/python">Coursera - Python for Everybody</a></li>
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</ul>
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</section>
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<section id="learning-more-ai-and-ml" class="level3">
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<h3 class="anchored" data-anchor-id="learning-more-ai-and-ml">Learning more AI and ML</h3>
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<p>Python is one of the most popular languages for machine learning and artificial intelligence. If you are interested in learning more about these topics, we recommend the following resources as good starting points:</p>
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<ul>
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<li><a href="https://www.coursera.org/learn/machine-learning">Coursera - Machine Learning by Andrew Ng</a></li>
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<li><a href="https://course.fast.ai/">fast.ai - Practical Deep Learning for Coders</a></li>
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</ul>
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</section>
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<section id="datasets-for-more-practice" class="level3">
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<h3 class="anchored" data-anchor-id="datasets-for-more-practice">Datasets for more practice</h3>
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<p>There are many websites that aggregate interesting datasets that you can use to practice your Python skills. Here are a few popular ones:</p>
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<ul>
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<li><a href="https://www.kaggle.com/datasets">kaggle</a></li>
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<li><a href="https://huggingface.co/datasets">Hugging Face</a></li>
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</ul>
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@@ -6147,7 +6180,40 @@ <h2 class="anchored" data-anchor-id="resources">Resources</h2>
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<span id="cb1-162"><a href="#cb1-162" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-163"><a href="#cb1-163" aria-hidden="true" tabindex="-1"></a><span class="fu">## Resources</span></span>
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<span id="cb1-164"><a href="#cb1-164" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-165"><a href="#cb1-165" aria-hidden="true" tabindex="-1"></a><span class="ss">- </span><span class="co">[</span><span class="ot">Introduction to data analysis in Python</span><span class="co">](https://ccb-hms.github.io/workbench-python-workshop/index.html)</span></span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button" data-in-quarto-modal><i class="bi"></i></button></div>
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<span id="cb1-165"><a href="#cb1-165" aria-hidden="true" tabindex="-1"></a><span class="fu">### Popular package resources</span></span>
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<span id="cb1-166"><a href="#cb1-166" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-167"><a href="#cb1-167" aria-hidden="true" tabindex="-1"></a>For a brief overview, or cheat sheet, of the most commonly used Python packages in data analysis, check out the following resources:</span>
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<span id="cb1-168"><a href="#cb1-168" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-169"><a href="#cb1-169" aria-hidden="true" tabindex="-1"></a><span class="ss">- </span><span class="co">[</span><span class="ot">Pandas cheat sheet</span><span class="co">](https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf)</span></span>
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<span id="cb1-170"><a href="#cb1-170" aria-hidden="true" tabindex="-1"></a><span class="ss">- </span><span class="co">[</span><span class="ot">NumPy cheat sheet</span><span class="co">](https://www.datacamp.com/cheat-sheet/numpy-cheat-sheet-data-analysis-in-python)</span></span>
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<span id="cb1-171"><a href="#cb1-171" aria-hidden="true" tabindex="-1"></a><span class="ss">- </span><span class="co">[</span><span class="ot">Matplotlib cheat sheet</span><span class="co">](https://matplotlib.org/cheatsheets/cheatsheets.pdf)</span></span>
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<span id="cb1-172"><a href="#cb1-172" aria-hidden="true" tabindex="-1"></a><span class="ss">- </span><span class="co">[</span><span class="ot">Scikit-learn cheat sheet</span><span class="co">](https://www.datacamp.com/cheat-sheet/scikit-learn-cheat-sheet-python-machine-learning)</span></span>
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<span id="cb1-173"><a href="#cb1-173" aria-hidden="true" tabindex="-1"></a><span class="ss">- </span><span class="co">[</span><span class="ot">Seaborn examples with code</span><span class="co">](https://seaborn.pydata.org/examples/index.html)</span></span>
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<span id="cb1-174"><a href="#cb1-174" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-175"><a href="#cb1-175" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-176"><a href="#cb1-176" aria-hidden="true" tabindex="-1"></a><span class="fu">### Other Python courses</span></span>
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<span id="cb1-177"><a href="#cb1-177" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-178"><a href="#cb1-178" aria-hidden="true" tabindex="-1"></a>We acknowledge that there are many other groups that have created excellent Python courses:</span>
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<span id="cb1-179"><a href="#cb1-179" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-180"><a href="#cb1-180" aria-hidden="true" tabindex="-1"></a><span class="ss">- </span><span class="co">[</span><span class="ot">Harvard CCB - Introduction to Data Analysis in Python</span><span class="co">](https://ccb-hms.github.io/workbench-python-workshop/index.html)</span></span>
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<span id="cb1-181"><a href="#cb1-181" aria-hidden="true" tabindex="-1"></a><span class="ss">- </span><span class="co">[</span><span class="ot">Google - Python Class</span><span class="co">](https://developers.google.com/edu/python)</span></span>
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<span id="cb1-182"><a href="#cb1-182" aria-hidden="true" tabindex="-1"></a><span class="ss">- </span><span class="co">[</span><span class="ot">Coursera - Python for Everybody</span><span class="co">](https://www.coursera.org/specializations/python)</span></span>
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<span id="cb1-183"><a href="#cb1-183" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-184"><a href="#cb1-184" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-185"><a href="#cb1-185" aria-hidden="true" tabindex="-1"></a><span class="fu">### Learning more AI and ML</span></span>
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<span id="cb1-186"><a href="#cb1-186" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-187"><a href="#cb1-187" aria-hidden="true" tabindex="-1"></a>Python is one of the most popular languages for machine learning and artificial intelligence. If you are interested in learning more about these topics, we recommend the following resources as good starting points:</span>
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<span id="cb1-188"><a href="#cb1-188" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-189"><a href="#cb1-189" aria-hidden="true" tabindex="-1"></a><span class="ss">- </span><span class="co">[</span><span class="ot">Coursera - Machine Learning by Andrew Ng</span><span class="co">](https://www.coursera.org/learn/machine-learning)</span></span>
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<span id="cb1-190"><a href="#cb1-190" aria-hidden="true" tabindex="-1"></a><span class="ss">- </span><span class="co">[</span><span class="ot">fast.ai - Practical Deep Learning for Coders</span><span class="co">](https://course.fast.ai/)</span></span>
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<span id="cb1-191"><a href="#cb1-191" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-192"><a href="#cb1-192" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-193"><a href="#cb1-193" aria-hidden="true" tabindex="-1"></a><span class="fu">### Datasets for more practice</span></span>
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<span id="cb1-194"><a href="#cb1-194" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-195"><a href="#cb1-195" aria-hidden="true" tabindex="-1"></a>There are many websites that aggregate interesting datasets that you can use to practice your Python skills. Here are a few popular ones:</span>
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<span id="cb1-196"><a href="#cb1-196" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-197"><a href="#cb1-197" aria-hidden="true" tabindex="-1"></a><span class="ss">- </span><span class="co">[</span><span class="ot">kaggle</span><span class="co">](https://www.kaggle.com/datasets)</span></span>
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<span id="cb1-198"><a href="#cb1-198" aria-hidden="true" tabindex="-1"></a><span class="ss">- </span><span class="co">[</span><span class="ot">Hugging Face</span><span class="co">](https://huggingface.co/datasets)</span></span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button" data-in-quarto-modal><i class="bi"></i></button></div>
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