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    <title>SWC/GCNU Software Skills</title>

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        <a href="https://www.sainsburywellcome.org/"><img src="https://rawcdn.githack.com/adamltyson/public-data/609927f999257b129c15d99116fadb11710a5e98/PyStarters_2019/SWC.png" alt="SWC logo" style="width:400px"></a>
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        <h2>Links</h2>
        <a href="https://github.com/SainsburyWellcomeCentre/software-skills">GitHub repository</a>

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        <section>
        <h1>SWC/GCNU Software Skills</h1><br>

          <h2>Upcoming dates</h2>
          <b><a href="events/timeseries_march_2023.html">Introduction to Timeseries Analysis in Python</a></b>
          <ul style="list-style-type:circle">
            <li>March 20<sup>th</sup> 2023. 1pm-5.30pm. SWC Lecture Theatre, UCL.</li>
          </ul>

          <b><a href="events/linux_hpc_april_2023.html">Introduction to high-performance computing with Linux</a></b>
          <ul style="list-style-type:circle">
            <li>May 15<sup>th</sup> 2023. 9am-5.30pm. SWC Lecture Theatre, UCL.</li>
          </ul>

          <b><a href="events/image_march_2023.html">Image analysis in Python</a></b>
          <ul style="list-style-type:circle">
            <li>Date and time TBC.</li>
          </ul>




        <h2>Previous dates</h2>

          <b><a href="events/type_annotation_nov_2022.html">Type annotation in Python</a></b>
          <ul style="list-style-type:circle">
            <li>November 25<sup>th</sup> 2022. 11am-12pm. GCNU 3rd floor seminar room.</li>
          </ul>

          <b><a href="events/release_dec_2022.html">Turning your Python scripts into reusable, general-purpose software</a></b>
          <ul style="list-style-type:circle">
            <li>December 1st 2022. 10am-5pm. SWC brasserie seminar room.</li>
          </ul>

          <b><a href="events/intro_sept_2022.html">Two-day introductory software skills course</a></b>
          <ul style="list-style-type:circle">
            <li>Sept 26<sup>th</sup>  and 27<sup>th</sup> 2022. 10am-5pm</li>
          </ul>

          <b><a href="events/intro_may_2021.html">Two-day Python introductory course</a></b>
          <ul style="list-style-type:circle">
            <li>May 6<sup>th</sup>  and 13<sup>th</sup> 2021 10am-4pm</li>
          </ul>

          <b><a href="events/plotting_with_matplotlib_april_2020.html">Plotting with Matplotlib</a></b>
          <ul style="list-style-type:circle">
            <li>April 2<sup>nd</sup> 10am-11.30am & April 6<sup>th</sup> 2020 1pm-2.30pm</li>
          </ul>

          <b><a href="events/git_intermediate_feb_2020.html">Intermediate Git</a></b>
          <ul style="list-style-type:circle">
            <li>February 25<sup>th</sup> 2020</li>
          </ul>

          <b><a href="events/intro_nov_2019.html">Two-day Python introductory course</a></b>
          <ul style="list-style-type:circle">
            <li>November 25<sup>th</sup>  - 26<sup>th</sup> 2019</li>
          </ul>

        <h2>Summary</h2>
          <p>The course will be split into two sections:
          <ul style="list-style-type:circle">
            <li>An introduction to python, and general scientific programming, split over two days (eventually expanded to a one week course). <b>No experience required</b>.</li>
            <li>A series of standalone, more specialist short courses covering specific software skills.</li>
          </ul></p>

          <p>You will be able to come to the entire course without any previous programming experience, but the later specialist courses will hopefully be useful to those with experience. </p>
          <p>The focus will be on using Python to develop efficient, reproducible workflows for neuroscience research, while teaching efficient programming and good coding practice.</p>

          <h2>Two-day introduction</h2>
          <h3>Aims</h3>
            <ul style="list-style-type:circle">
              <li>Introduce those new to Python (and programming in general) to the language and the vocabulary and show how to install Python and the entire ecosystem (virtual environment, package manager, text editor/IDE). </li>
              <li>Allow new users to feel comfortable carrying out basic data analysis independently. </li>
            <li>To provide a common base level of knowledge for the more advanced, specialist courses that will follow.</li>
            </ul>


        <h3>Contents</h3>
          General software carpentry
          <ul style="list-style-type:circle">
          <li>Bash command line</li>
          <li>Version control using git</li>
          <li>Github (making an account, raising issues, using other peoples software)</li>
          <li>IDEs (what software you use to write your software)</li><li>Working with virtual environments</li>
          </ul>

            Software development in Python
          <ul style="list-style-type:circle">
            <li>Introduction to Python</li>
            <li>Installing Python</li>
            <li>Variables</li>
            <li>Data types</li>
            <li>Loops</li>
            <li>Conditional statements</li>
            <li>Loading and saving data</li>
            <li>Writing your first Python script</li>
            <li>Installing packages with pip</li>
            <li>Using third party libraries from pip and conda</li>
            <li>List comprehensions</li>
            <li>Functions</li>
            <li>Object oriented programming</li>
            <li>Errors and exceptions</li>
            <li>Organising your Python project and importing functions</li>
            <li>Documenting your code</li>
          </ul>

          <h2>Standalone specialist courses</h2>
          <p>Future courses to be confirmed, but possible topics include:
          <ul style="list-style-type:circle">
            <li>Image analysis (e.g. 2p imaging)</li>
            <li>Timeseries analysis (e.g. neuropixels) </li>
          <li>Plotting </li>
          <li>General data analysis in <a href="https://pandas.pydata.org/">Pandas</a></li>
          <li>Data acqusition </li>
          <li>Testing </li>
          <li>Object oriented programming </li>
          <li>Distributing and packaging code </li>
          <li>Profiling, optimisation and packages for efficient computation (e.g. <a href="https://numba.pydata.org/">Numba</a> & <a href="https://dask.org/">Dask</a></li>
          <li>Behavioural analysis using <a href="http://www.mousemotorlab.org/deeplabcut">DeepLabCut</a> </li>
          <li>Machine learning</li>


        </ul></p>
          <p>The courses run will depend on enthusiasm and availability of instructors and students. If there's something you want to learn, or tell everyone about, <a href="mailto:adam.tyson@ucl.ac.uk?subject=Software%Teachiing">get in touch</a>. </p>



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