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<h1 class="title">Parallel Python</h1>
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<p>This course is aimed at researchers, students, and industry professionals who want to learn intermediate python skills applied to scientific computing and data science.</p>
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<h2 class="anchored" data-anchor-id="trainers">Trainers</h2>
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<li>Kristian Maras (Kris) (MSc Mathematics / Ba Commerce)</li>
<li>Thomas Mauch (Tom) (PhD in astronomy)</li>
<li>Nathaniel (Nate) Butterworth (PhD Computational Geophysics)</li>
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<p>Introductory Python experience recommended.</p>
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<p>We expect all attendees of our training to follow our code of conduct, including bullying, harassment and discrimination prevention policies.</p>
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<li>Use welcoming and inclusive language</li>
<li>Be respectful of different viewpoints and experiences</li>
<li>Gracefully accept constructive criticism</li>
<li>Focus on what is best for the community</li>
<li>Show courtesy and respect towards other community members</li>
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<p>Our full CoC, with incident reporting guidelines, is available <a href="https://sydney-informatics-hub.github.io/codeofconduct/">here</a>.</p>
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<h2 class="anchored" data-anchor-id="general-session-timings">General session timings</h2>
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<li>A. Intoduction and Revise Python Data Manipulation and Pandas Data Structure</li>
<li>B. Why Polars is a better option for dataframes</li>
<li>C. Why Dask provides an ecosystem of tools that can run on clusters of machines.</li>
</ul>
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<h2 class="anchored" data-anchor-id="setup-instructions">Setup Instructions</h2>
<p><strong>For local installation</strong>:</p>
<p><code>git clone https://github.com/Sydney-Informatics-Hub/ParallelPython.git</code></p>
<p><code>cd ParallelPython</code></p>
<p><code>conda env create -f environment.yml</code></p>
<p><code>conda activate parallel</code></p>
<p><strong>Google Colab</strong>:</p>
<p>Alternatively, you can use Google co-lab, which requires you to sign into your google account. Go to <a href="https://colab.research.google.com/">Google Colab</a>, and click “new notebook”. Colab is very similar to jupyter notebook except the compute is run on google cloud infrastructure.</p>
<p>Most packages are by defualt installed. If a package is needed you can run the pip install with the “!” prefix. ie. <code>! pip install ucimlrepo</code>. This access the underlying terminal.</p>
</section>
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