Update documentation

Author: aaronjnewman

2b-setup/github.html

@@ -626,7 +626,7 @@ <h2> Contents </h2>
                 <article class="bd-article">
 
   <figure class="align-left">
-<a class="reference internal image-reference" href="2b-setup/images/github_octocat.png"><img alt="2b-setup/images/github_octocat.png" src="2b-setup/images/github_octocat.png" style="width: 65px;" /></a>
+<a class="reference internal image-reference" href="../_images/github_octocat.png"><img alt="../_images/github_octocat.png" src="../_images/github_octocat.png" style="width: 65px;" /></a>
 </figure>
 <section class="tex2jax_ignore mathjax_ignore" id="get-on-github">
 <h1>Get on GitHub<a class="headerlink" href="#get-on-github" title="Link to this heading">#</a></h1>

_sources/2b-setup/github.md

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-```{figure} images/github_octocat.png
+```{figure} ../2-nds/images/github_octocat.png
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_sources/intro.md

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 # Neural Data Science in Python
 
-Welcome! This online textbook is aimed primarily at students and researchers in neuroscience and cognitive psychology who want to learn how to work with and make sense of data using Python. It is also accessible for students with a computer science background who want to learn how to apply their skills to neuroscience. The textbook assumes no prior knowledge of Python, or any other programming language. If you do have prior knowledge of Python and want to learn how to apply it to neuroscience, you can skip the first few chapters and start with [Chapter 4](./4-viz/introduction.md).
+Welcome! This online textbook is aimed primarily at students and researchers in neuroscience and cognitive psychology who want to learn how to work with and make sense of data using Python. It is also accessible for students with a computer science background who want to learn how to apply their skills to neuroscience. The textbook assumes no prior knowledge of Python, or any other programming language. If you do have prior knowledge of Python and want to learn how to apply it to neuroscience, you can skip the first few chapters and start with [Chapter 4](./4-viz/introduction).
 
 **This book will teach you the fundamentals of Python, and how to use the GitHub Copilot AI assistant to help you learn to code, and write code for you**. From there, we learn additional Python in the context of using it for data science, including **data visualization**, and **working with different types of neuroscience data, including single unit recordings, EEG, and fMRI**.
 
@@ -10,7 +10,7 @@ Written by Prof. [Aaron J. Newman](https://aaronjnewman.com/), [Department of Ps
 
 ## Downloading the Materials to Work Through the Book
 
-You can learn about neural data science in Python by simply reading the book, but you probably won't become a proficient coder, or practitioner of data science, unless you work through the book's Jupyter notebooks, which let you write and run code. To do this, you will need to download the materials for each chapter from our [GitHub repository](https://github.com/neural-data-science). The third chapter explains [how to set up your computer for this course](./2b-setup/introduction.html), and will walk you through downloading the materials as well as all the software you need to install to work through the book. All of these tools are free and open source, with the possible exception of the GitHub Copilot AI assistant, if you are not a student or otherwise affiliated with an academic institution.
+You can learn about neural data science in Python by simply reading the book, but you probably won't become a proficient coder, or practitioner of data science, unless you work through the book's Jupyter notebooks, which let you write and run code. To do this, you will need to download the materials for each chapter from our [GitHub repository](https://github.com/neural-data-science). The third chapter explains [how to set up your computer for this course](./2b-setup/introduction), and will walk you through downloading the materials as well as all the software you need to install to work through the book. All of these tools are free and open source, with the possible exception of the GitHub Copilot AI assistant, if you are not a student or otherwise affiliated with an academic institution.
 
 ## Video Tutorials
 

intro.html

@@ -630,13 +630,13 @@ <h2> Contents </h2>
 
   <section class="tex2jax_ignore mathjax_ignore" id="neural-data-science-in-python">
 <h1>Neural Data Science in Python<a class="headerlink" href="#neural-data-science-in-python" title="Link to this heading">#</a></h1>
-<p>Welcome! This online textbook is aimed primarily at students and researchers in neuroscience and cognitive psychology who want to learn how to work with and make sense of data using Python. It is also accessible for students with a computer science background who want to learn how to apply their skills to neuroscience. The textbook assumes no prior knowledge of Python, or any other programming language. If you do have prior knowledge of Python and want to learn how to apply it to neuroscience, you can skip the first few chapters and start with <a class="reference internal" href="4-viz/introduction.html"><span class="std std-doc">Chapter 4</span></a>.</p>
+<p>Welcome! This online textbook is aimed primarily at students and researchers in neuroscience and cognitive psychology who want to learn how to work with and make sense of data using Python. It is also accessible for students with a computer science background who want to learn how to apply their skills to neuroscience. The textbook assumes no prior knowledge of Python, or any other programming language. If you do have prior knowledge of Python and want to learn how to apply it to neuroscience, you can skip the first few chapters and start with <a class="reference internal" href="4-viz/introduction.html"><span class="doc std std-doc">Chapter 4</span></a>.</p>
 <p><strong>This book will teach you the fundamentals of Python, and how to use the GitHub Copilot AI assistant to help you learn to code, and write code for you</strong>. From there, we learn additional Python in the context of using it for data science, including <strong>data visualization</strong>, and <strong>working with different types of neuroscience data, including single unit recordings, EEG, and fMRI</strong>.</p>
 <p>This book was written to support the course <a class="reference external" href="https://neural-data-science.github.io/NESC_3505/">NESC 3505 <em>Neural Data Science</em></a>, at <a class="reference external" href="https://dal.ca">Dalhousie University</a>. Development of the textbook is <em>in progress</em>, with irregular but ongoing updates being posted. It is released as an open educational resource, under a <a class="reference external" href="https://creativecommons.org/licenses/by-nc-sa/4.0/">license</a> that allows free re-use and re-mixing, except for commercial purposes.</p>
 <p>Written by Prof. <a class="reference external" href="https://aaronjnewman.com/">Aaron J. Newman</a>, <a class="reference external" href="https://www.dal.ca/faculty/science/psychology_neuroscience">Department of Psychology &amp; Neuroscience</a>, <a class="reference external" href="https://dal.ca">Dalhousie University</a>, with contributions from students in his lab, including <a class="reference external" href="https://github.com/lauraelliott210">Laura Elliott</a>, <a class="reference external" href="https://github.com/Balkazar">Danny Godfrey</a>,, <a class="reference external" href="https://github.com/brynnhs">Brynn Harris-Shanks</a>, <a class="reference external" href="https://github.com/reannpost">Reann Post</a>, and <a class="reference external" href="https://github.com/saisha-r">Saisha Rankaduwa</a> as well as other generous folks from around the world (see the book’s <a class="reference external" href="https://github.com/neural-data-science/NESC_3505_textbook">GitHub page</a> for a complete list). Some of the text and code was generated using the GitHub Copilot AI assistant. We welcome additional contributions from the community; once you are familiar with GitHub (from working through the early part of this book) you can create Issues and Pull Requests to help us correct typos, other errors, and also to suggest things you’d like to see in the book, or requests for clarification of things you don’t understand.</p>
 <section id="downloading-the-materials-to-work-through-the-book">
 <h2>Downloading the Materials to Work Through the Book<a class="headerlink" href="#downloading-the-materials-to-work-through-the-book" title="Link to this heading">#</a></h2>
-<p>You can learn about neural data science in Python by simply reading the book, but you probably won’t become a proficient coder, or practitioner of data science, unless you work through the book’s Jupyter notebooks, which let you write and run code. To do this, you will need to download the materials for each chapter from our <a class="reference external" href="https://github.com/neural-data-science">GitHub repository</a>. The third chapter explains <a class="reference internal" href="#./2b-setup/introduction.html"><span class="xref myst">how to set up your computer for this course</span></a>, and will walk you through downloading the materials as well as all the software you need to install to work through the book. All of these tools are free and open source, with the possible exception of the GitHub Copilot AI assistant, if you are not a student or otherwise affiliated with an academic institution.</p>
+<p>You can learn about neural data science in Python by simply reading the book, but you probably won’t become a proficient coder, or practitioner of data science, unless you work through the book’s Jupyter notebooks, which let you write and run code. To do this, you will need to download the materials for each chapter from our <a class="reference external" href="https://github.com/neural-data-science">GitHub repository</a>. The third chapter explains <a class="reference internal" href="2b-setup/introduction.html"><span class="doc std std-doc">how to set up your computer for this course</span></a>, and will walk you through downloading the materials as well as all the software you need to install to work through the book. All of these tools are free and open source, with the possible exception of the GitHub Copilot AI assistant, if you are not a student or otherwise affiliated with an academic institution.</p>
 </section>
 <section id="video-tutorials">
 <h2>Video Tutorials<a class="headerlink" href="#video-tutorials" title="Link to this heading">#</a></h2>