learning-path.qmd

---
title: "R Learning Path"
format: html
title-block: false
---

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<div class="page-shell">
  <p class="page-lead">Return to R by learning the work you need to do, not every corner of the language.</p>

  <section class="journey">
    <div class="journey-nav">
      <p class="section-title">Recommended path</p>
      <p class="section-copy">Start at the top and move stage by stage. You can revisit any stage whenever your work exposes a gap.</p>

      <div class="stage-list">
        <button class="stage-btn active" id="btn-orientation" onclick="showStage('orientation')">
          <span class="stage-index">1</span>
          <span class="stage-copy">
            <span class="stage-title">Introduction</span>
            <span class="stage-sub">Mindset, role, and how this path works.</span>
          </span>
        </button>

        <button class="stage-btn" id="btn-syntax" onclick="showStage('syntax')">
          <span class="stage-index">2</span>
          <span class="stage-copy">
            <span class="stage-title">Learn Enough Syntax</span>
            <span class="stage-sub">Recognise data frames, dplyr, ggplot2, pipes, and packages.</span>
          </span>
        </button>

        <button class="stage-btn" id="btn-ai" onclick="showStage('ai')">
          <span class="stage-index">3</span>
          <span class="stage-copy">
            <span class="stage-title">Learn Through Relevant Work</span>
            <span class="stage-sub">Pick a project that matters to you and use AI to learn by doing it.</span>
          </span>
        </button>

        <button class="stage-btn" id="btn-code" onclick="showStage('code')">
          <span class="stage-index">4</span>
          <span class="stage-copy">
            <span class="stage-title">Learn from Real Scripts</span>
            <span class="stage-sub">Read team code and notice which analyses, outputs, or tools matter to you.</span>
          </span>
        </button>

        <button class="stage-btn" id="btn-workflow" onclick="showStage('workflow')">
          <span class="stage-index">5</span>
          <span class="stage-copy">
            <span class="stage-title">Use AI as a Translator</span>
            <span class="stage-sub">Turn familiar SAS, or analysis ideas into R code.</span>
          </span>
        </button>
      </div>
    </div>

    <div class="journey-panel-wrap">
      <div class="panel active" id="panel-orientation">
        <div class="panel-head">
          <div class="panel-head-main">
            <span class="pill pill-green">Stage 1</span>
            <h2>1. Introduction</h2>
          </div>
          <button class="close-btn" onclick="showStage('orientation')">Reset stage</button>
        </div>
        <p class="panel-intro">
          Mindset, role, and how this path works.
        </p>
        <div class="panel-rule"></div>
        <div class="panel-grid panel-grid-3">
          <div class="content-card">
            <div class="icon-badge">B</div>
            <h3>Goal</h3>
            <p>Replace the feeling of "I have to relearn everything" with "I already know the analysis, I just need to learn how R expresses it."</p>
          </div>
          <div class="content-card">
            <div class="icon-badge">AI</div>
            <h3>AI Role</h3>
            <p>Use AI as a translator, explainer, code reviewer, and debugging partner while you learn in context.</p>
          </div>
          <div class="content-card">
            <div class="icon-badge">U</div>
            <h3>Audience</h3>
            <p>Designed for people either returning to R or coming to R as a newcomer.</p>
          </div>
        </div>
        <div class="callout-row">
          <div class="panel-foot">If you last touched R years ago at university, the fastest route back is not a long course taken in order. It is a guided, applied path: learn enough syntax to recognise what R is doing, use AI to translate what you already know from SAS, or other analysis workflows, then learn from real scripts and real tasks.</div>
        </div>
      </div>

      <div class="panel" id="panel-syntax">
        <div class="panel-head">
          <div>
            <span class="pill pill-blue">Stage 2</span>
            <h2>Learn enough syntax to recognise what R is doing</h2>
          </div>
          <button class="close-btn" onclick="showStage('orientation')">Back to start</button>
        </div>
        <p class="panel-intro">
          Spend a short burst of time on the core shapes of modern R code. The aim is recognition and confidence, not deep mastery.
        </p>
        <div class="panel-rule"></div>
        <div class="panel-grid">
          <div class="content-card">
            <h3>Goal</h3>
            <p>Become comfortable seeing data frames, verbs like <code>filter()</code> and <code>mutate()</code>, pipes, and basic <code>ggplot2</code> code.</p>
          </div>
          <div class="content-card">
            <h3>What to do</h3>
            <ul>
              <li>Spend one or two days on introductory material only.</li>
              <li>Focus on data frames, <code>dplyr</code>, <code>ggplot2</code>, pipes, and packages.</li>
              <li>Do not worry if you cannot write everything from memory.</li>
            </ul>
          </div>
          <div class="content-card">
            <h3>Ask AI this</h3>
            <div class="prompt-list">
              <div class="prompt">"Explain data frames, dplyr, ggplot2, and pipes as if I am a clinical-trial analyst returning to R."</div>
              <div class="prompt">"Show me a tiny example that reads a dataset, filters rows, creates a new variable, and makes a simple plot in R."</div>
            </div>
          </div>
          <div class="content-card">
            <h3>Recommended resources</h3>
            <div class="resource-list">
              <a class="resource-card" href="https://gsk-biostatistics.github.io/intro_to_r_and_the_tidyverse_training/" target="_blank" rel="noopener">
                <strong>GSK: Intro to R and the tidyverse</strong>
                <span>Practical, structured material for getting comfortable with modern R syntax.</span>
                <em>gsk-biostatistics.github.io</em>
              </a>
              <a class="resource-card" href="https://r4ds.hadley.nz/" target="_blank" rel="noopener">
                <strong>R for Data Science</strong>
                <span>Use selected sections, not necessarily front-to-back, to recognise common tidyverse patterns.</span>
                <em>r4ds.hadley.nz</em>
              </a>
              <a class="resource-card" href="https://www.youtube.com/watch?v=yZ0bV2Afkjc" target="_blank" rel="noopener">
                <strong>Introductory video walkthrough</strong>
                <span>A lightweight way to re-familiarise yourself with what R code looks like in practice.</span>
                <em>youtube.com</em>
              </a>
            </div>
          </div>
        </div>
        <div class="panel-foot">If someone can look at a short tidyverse script and roughly follow its shape, this stage has done its job.</div>
      </div>

      <div class="panel" id="panel-ai">
        <div class="panel-head">
          <div>
            <span class="pill pill-coral">Stage 3</span>
            <h2>Learn through work that actually matters to you</h2>
          </div>
          <button class="close-btn" onclick="showStage('orientation')">Back to start</button>
        </div>
        <p class="panel-intro">
          The best way to keep progressing is to choose an analysis, output, or area you are genuinely likely to work on, then use AI to turn that into a learning loop.
        </p>
        <div class="panel-rule"></div>
        <div class="panel-grid">
          <div class="content-card">
            <h3>Goal</h3>
            <p>Create a workflow that turns a relevant project into one connected cycle of planning, coding, debugging, and explanation.</p>
          </div>
          <div class="content-card">
            <h3>What to do</h3>
            <ul>
              <li>Choose something you genuinely care about learning, such as meta-analysis, dashboards, survival analysis, repeated measures work, plotting, reporting, or reproducible pipelines.</li>
              <li>Write the project or analysis plan in plain English first.</li>
              <li>Ask AI to generate a first draft of the R code.</li>
              <li>Run it, inspect the output, then debug with AI when needed.</li>
              <li>Ask AI to explain the final script and tell you what R concepts you learned through the project.</li>
            </ul>
          </div>
          <div class="content-card">
            <h3>Ask AI this</h3>
            <div class="prompt-list">
              <div class="prompt">"I am likely to need to do meta-analysis in my role. Help me learn how to approach that in R step by step."</div>
              <div class="prompt">"I am interested in dashboards rather than modelling right now. What is a good beginner-friendly R project path for that?"</div>
              <div class="prompt">"Here is the analysis I need to do. Turn this English plan into tidyverse R code."</div>
              <div class="prompt">"Here is my current script and output. What should I check next?"</div>
              <div class="prompt">"Now that this works, explain the final code and point out the R ideas I should remember from this project."</div>
            </div>
          </div>
          <div class="content-card">
            <h3>Why this works</h3>
            <p>People learn faster when the work feels relevant. If meta-analysis is something you are likely to do, learn that in R. If dashboards, plots, reporting, or survival work matter more, start there instead.</p>
          </div>
        </div>
        <div class="panel-foot">The long-term aim is not dependence on AI. It is faster understanding, cleaner iteration, and better transfer from one real project to the next.</div>
      </div>

      <div class="panel" id="panel-code">
        <div class="panel-head">
          <div>
            <span class="pill pill-green">Stage 4</span>
            <h2>Learn from the real code your team already uses</h2>
          </div>
          <button class="close-btn" onclick="showStage('orientation')">Back to start</button>
        </div>
        <p class="panel-intro">
          The most relevant R education often comes from the scripts, packages, and conventions already present in your team, especially when they point toward the kinds of analyses or outputs you are likely to work on yourself.
        </p>
        <div class="panel-rule"></div>
        <div class="panel-grid">
          <div class="content-card">
            <h3>Goal</h3>
            <p>Understand the actual style of R code used around you, and notice which analyses, reports, or tools feel most relevant to your own work.</p>
          </div>
          <div class="content-card">
            <h3>What to do</h3>
            <ul>
              <li>Take short sections of shared scripts and study them with AI.</li>
              <li>Notice the packages, naming patterns, and data-flow style your team prefers.</li>
              <li>Pay attention to the types of work the code supports, such as meta-analysis, visualisation, dashboards, reporting workflows, or survival analysis.</li>
              <li>Ask for beginner-friendly rewrites when a script feels too dense.</li>
            </ul>
          </div>
          <div class="content-card">
            <h3>Ask AI this</h3>
            <div class="prompt-list">
              <div class="prompt">"Explain what this code is doing and tell me which R concepts I need to understand first."</div>
              <div class="prompt">"What packages are being used here and why would a clinical-trial team choose them?"</div>
              <div class="prompt">"Looking at this script, what kind of analysis or project is this closest to, and would it be a good learning project for me?"</div>
              <div class="prompt">"Rewrite this in a more beginner-friendly way but keep the same analytical result."</div>
            </div>
          </div>
          <div class="content-card">
            <h3>Recommended resources</h3>
            <div class="resource-list">
              <a class="resource-card" href="https://posit.cloud/learn/recipes" target="_blank" rel="noopener">
                <strong>Posit Recipes</strong>
                <span>Bite-sized worked examples that pair well with reading and adapting real scripts.</span>
                <em>posit.cloud/learn/recipes</em>
              </a>
              <a class="resource-card" href="https://posit.co/resources/cheatsheets/" target="_blank" rel="noopener">
                <strong>Posit cheat sheets</strong>
                <span>Useful when you are reading team code and need a quick reminder of syntax or function patterns.</span>
                <em>posit.co/resources/cheatsheets</em>
              </a>
            </div>
          </div>
        </div>
        <div class="panel-foot">This is often where R starts to feel real: the learner can connect tutorial ideas to the scripts, analyses, and outputs their team actually cares about, then choose one of those areas as the next place to learn more deeply.</div>
      </div>

      <div class="panel" id="panel-workflow">
        <div class="panel-head">
          <div>
            <span class="pill pill-amber">Stage 5</span>
            <h2>Use AI as a translator, not just a search engine</h2>
          </div>
          <button class="close-btn" onclick="showStage('orientation')">Back to start</button>
        </div>
        <p class="panel-intro">
          AI is most useful when you ask it to bridge from what you already know into R code, explanation, and debugging help.
        </p>
        <div class="panel-rule"></div>
        <div class="panel-grid">
          <div class="content-card">
            <h3>Goal</h3>
            <p>Learn in context by translating familiar analytical tasks into R instead of trying to memorise syntax in isolation.</p>
          </div>
          <div class="content-card">
            <h3>What to do</h3>
            <ul>
              <li>Describe the task the way you would describe it in SAS, or plain English.</li>
              <li>Ask AI to explain code line by line, not only to generate code.</li>
              <li>When you hit an error, paste the code and error together and ask for diagnosis.</li>
            </ul>
          </div>
          <div class="content-card">
            <h3>Ask AI this</h3>
            <div class="prompt-list">
              <div class="prompt">"I would do this in SAS. How do I do it in R using tidyverse code?"</div>
              <div class="prompt">"Explain this R code line by line as if I am an analyst new to R."</div>
              <div class="prompt">"I ran this code and got this error. Tell me what the error means, what probably caused it, and how to fix it."</div>
              <div class="prompt">"Rewrite this R code in a more beginner-friendly way and explain the packages being used."</div>
            </div>
          </div>
          <div class="content-card">
            <h3>Recommended resources</h3>
            <ul>
              <li>Save good prompts that worked well for translation, explanation, and debugging.</li>
              <li>Keep asking AI to rewrite dense code in a simpler style until the structure feels familiar.</li>
              <li>Use this stage alongside real datasets and real scripts, not only toy examples.</li>
            </ul>
          </div>
        </div>
        <div class="panel-foot">This stage is where learning speed usually jumps. AI lets people learn from real work instead of waiting until they feel fully trained.</div>
      </div>
    </div>
  </section>
</div>

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