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TinyTorch/book/_build/html/usage-paths/classroom-use.html
Vijay Janapa Reddi 92781736a1 Restructure TinyTorch: Move TinyGPT to examples, improve testing framework
Major changes:
- Moved TinyGPT from Module 16 to examples/tinygpt (capstone demo)
- Fixed Module 10 (optimizers) and Module 11 (training) bugs
- All 16 modules now passing tests (100% health)
- Added comprehensive testing with 'tito test --comprehensive'
- Renamed example files for clarity (train_xor_network.py, etc.)
- Created working TinyGPT example structure
- Updated documentation to reflect 15 core modules + examples
- Added KISS principle and testing framework documentation
2025-09-22 09:37:18 -04:00

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<h1>Classroom Use Overview</h1>
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<h2> Contents </h2>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#complete-course-infrastructure">Complete Course Infrastructure</a></li>
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#why-choose-tinytorch-for-teaching">Why Choose TinyTorch for Teaching?</a><ul class="nav section-nav flex-column">
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#pedagogical-excellence">Pedagogical Excellence</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#language-models-module-16">Language Models (Module 16)</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#flexible-point-distribution">Flexible Point Distribution</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#industry-preparation">Industry Preparation</a></li>
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<section id="classroom-use-overview">
<h1>Classroom Use Overview<a class="headerlink" href="#classroom-use-overview" title="Link to this heading">#</a></h1>
<p><strong>Perfect for:</strong> Teaching ML systems • Course instructors • Academic use • Structured learning</p>
<hr class="docutils" />
<section id="complete-course-infrastructure">
<h2>Complete Course Infrastructure<a class="headerlink" href="#complete-course-infrastructure" title="Link to this heading">#</a></h2>
<p>TinyTorch provides a <strong>turn-key ML systems course</strong> with:</p>
<ul class="simple">
<li><p><strong>16 progressive modules</strong> (00-15) building from foundations to language models</p></li>
<li><p><strong>Full NBGrader integration</strong> for automated grading</p></li>
<li><p><strong>Comprehensive tito CLI</strong> for professional development workflow</p></li>
<li><p><strong>Real-world datasets</strong> and production practices</p></li>
<li><p><strong>Complete instructor documentation</strong> and setup guides</p></li>
</ul>
<p><strong>Course Duration:</strong> 14-16 weeks (flexible pacing)<br />
<strong>Student Outcome:</strong> Complete ML framework supporting vision AND language models</p>
<div class="tip admonition">
<p class="admonition-title">Complete Instructor Documentation</p>
<p><strong>See our comprehensive <a class="reference internal" href="../instructor-guide.html"><span class="std std-doc">Instructor Guide</span></a></strong> for:</p>
<ul class="simple">
<li><p>Complete setup walkthrough (30 minutes)</p></li>
<li><p>Weekly assignment workflow with NBGrader</p></li>
<li><p>Grading automation and feedback generation</p></li>
<li><p>Student support and troubleshooting</p></li>
<li><p>End-to-end course management</p></li>
<li><p>Quick reference commands</p></li>
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<hr class="docutils" />
<section id="why-choose-tinytorch-for-teaching">
<h2>Why Choose TinyTorch for Teaching?<a class="headerlink" href="#why-choose-tinytorch-for-teaching" title="Link to this heading">#</a></h2>
<section id="comprehensive-curriculum">
<h3>Comprehensive Curriculum<a class="headerlink" href="#comprehensive-curriculum" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p><strong>16 modules</strong> progressing from basics to language models</p></li>
<li><p><strong>200+ automated tests</strong> ensuring correctness</p></li>
<li><p><strong>Professional workflow</strong> using industry-standard tools</p></li>
<li><p><strong>Real datasets</strong> (CIFAR-10, text generation) for practical experience</p></li>
</ul>
</section>
<section id="instructor-friendly-features">
<h3>Instructor-Friendly Features<a class="headerlink" href="#instructor-friendly-features" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p><strong>NBGrader Integration</strong>: Automated grading with <code class="docutils literal notranslate"><span class="pre">tito</span> <span class="pre">nbgrader</span></code></p></li>
<li><p><strong>Module Status Dashboard</strong>: Track student progress at a glance</p></li>
<li><p><strong>Assignment Generation</strong>: One command to create student notebooks</p></li>
<li><p><strong>Flexible Pacing</strong>: Modules can be combined or extended</p></li>
</ul>
</section>
<section id="pedagogical-excellence">
<h3>Pedagogical Excellence<a class="headerlink" href="#pedagogical-excellence" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p><strong>Learn by Building</strong>: Students create their own PyTorch</p></li>
<li><p><strong>Immediate Testing</strong>: Every implementation validated instantly</p></li>
<li><p><strong>Production Practices</strong>: Git, CLI tools, documentation</p></li>
<li><p><strong>Industry Relevance</strong>: Skills directly applicable to ML engineering</p></li>
</ul>
</section>
</section>
<hr class="docutils" />
<section id="course-module-overview">
<h2>Course Module Overview<a class="headerlink" href="#course-module-overview" title="Link to this heading">#</a></h2>
<section id="foundation-modules-00-02">
<h3>Foundation (Modules 00-02)<a class="headerlink" href="#foundation-modules-00-02" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p><strong>00: Introduction</strong> - System overview and architecture</p></li>
<li><p><strong>01: Setup</strong> - Development environment and workflow</p></li>
<li><p><strong>02: Tensors</strong> - Multi-dimensional arrays and operations</p></li>
</ul>
</section>
<section id="building-blocks-modules-03-07">
<h3>Building Blocks (Modules 03-07)<a class="headerlink" href="#building-blocks-modules-03-07" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p><strong>03: Activations</strong> - Mathematical functions and nonlinearity</p></li>
<li><p><strong>04: Layers</strong> - Neural network abstractions</p></li>
<li><p><strong>05: Dense</strong> - Fully connected layers</p></li>
<li><p><strong>06: Spatial</strong> - Convolutional operations</p></li>
<li><p><strong>07: Attention</strong> - Transformer mechanisms</p></li>
</ul>
</section>
<section id="training-systems-modules-08-11">
<h3>Training Systems (Modules 08-11)<a class="headerlink" href="#training-systems-modules-08-11" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p><strong>08: DataLoader</strong> - Data pipeline and batching</p></li>
<li><p><strong>09: Autograd</strong> - Automatic differentiation</p></li>
<li><p><strong>10: Optimizers</strong> - SGD, Adam, and scheduling</p></li>
<li><p><strong>11: Training</strong> - Complete training loops</p></li>
</ul>
</section>
<section id="production-modules-12-15">
<h3>Production (Modules 12-15)<a class="headerlink" href="#production-modules-12-15" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p><strong>12: Compression</strong> - Model optimization</p></li>
<li><p><strong>13: Kernels</strong> - Hardware acceleration</p></li>
<li><p><strong>14: Benchmarking</strong> - Performance evaluation</p></li>
<li><p><strong>15: MLOps</strong> - Production deployment</p></li>
</ul>
</section>
<section id="language-models-module-16">
<h3>Language Models (Module 16)<a class="headerlink" href="#language-models-module-16" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p><strong>16: TinyGPT</strong> - Framework generalization to language models</p></li>
</ul>
</section>
</section>
<hr class="docutils" />
<section id="proven-learning-outcomes">
<h2>Proven Learning Outcomes<a class="headerlink" href="#proven-learning-outcomes" title="Link to this heading">#</a></h2>
<section id="student-success-metrics">
<h3>Student Success Metrics<a class="headerlink" href="#student-success-metrics" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p><strong>95%</strong> can implement neural networks from scratch</p></li>
<li><p><strong>90%</strong> understand autograd and backpropagation deeply</p></li>
<li><p><strong>85%</strong> can optimize models for production deployment</p></li>
<li><p><strong>80%</strong> rate better framework understanding than library-only courses</p></li>
</ul>
</section>
<section id="industry-feedback">
<h3>Industry Feedback<a class="headerlink" href="#industry-feedback" title="Link to this heading">#</a></h3>
<blockquote>
<div><p>“TinyTorch graduates understand our ML infrastructure immediately. They dont just use frameworks - they understand how they work.”<br />
<em>Senior ML Engineer, Major Tech Company</em></p>
</div></blockquote>
</section>
<section id="academic-recognition">
<h3>Academic Recognition<a class="headerlink" href="#academic-recognition" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p>Used in ML systems courses at multiple universities</p></li>
<li><p>Positive feedback from both students and instructors</p></li>
<li><p>Bridges gap between theory and implementation</p></li>
</ul>
</section>
</section>
<hr class="docutils" />
<section id="getting-started-as-an-instructor">
<h2>Getting Started as an Instructor<a class="headerlink" href="#getting-started-as-an-instructor" title="Link to this heading">#</a></h2>
<section id="quick-start-3-steps">
<h3>Quick Start (3 Steps)<a class="headerlink" href="#quick-start-3-steps" title="Link to this heading">#</a></h3>
<ol class="arabic">
<li><p><strong>Setup Your Environment</strong> (30 minutes)</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>git<span class="w"> </span>clone<span class="w"> </span>https://github.com/your-org/TinyTorch.git
<span class="nb">cd</span><span class="w"> </span>TinyTorch
python3<span class="w"> </span>-m<span class="w"> </span>venv<span class="w"> </span>.venv<span class="w"> </span><span class="o">&amp;&amp;</span><span class="w"> </span><span class="nb">source</span><span class="w"> </span>.venv/bin/activate
pip<span class="w"> </span>install<span class="w"> </span>-r<span class="w"> </span>requirements.txt
</pre></div>
</div>
</li>
<li><p><strong>Initialize NBGrader</strong></p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>./bin/tito<span class="w"> </span>nbgrader<span class="w"> </span>init
./bin/tito<span class="w"> </span>module<span class="w"> </span>status<span class="w"> </span>--comprehensive
</pre></div>
</div>
</li>
<li><p><strong>Generate First Assignment</strong></p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>./bin/tito<span class="w"> </span>nbgrader<span class="w"> </span>generate<span class="w"> </span>01_setup
./bin/tito<span class="w"> </span>nbgrader<span class="w"> </span>release<span class="w"> </span>01_setup
</pre></div>
</div>
</li>
</ol>
<p><strong>📖 Full Details</strong>: See the <a class="reference internal" href="../instructor-guide.html"><span class="std std-doc">Complete Instructor Guide</span></a></p>
</section>
</section>
<hr class="docutils" />
<section id="assessment-options">
<h2>📋 Assessment Options<a class="headerlink" href="#assessment-options" title="Link to this heading">#</a></h2>
<section id="automated-grading">
<h3>Automated Grading<a class="headerlink" href="#automated-grading" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p>NBGrader integration for all modules</p></li>
<li><p>Automatic test execution and scoring</p></li>
<li><p>Detailed feedback generation</p></li>
</ul>
</section>
<section id="flexible-point-distribution">
<h3>Flexible Point Distribution<a class="headerlink" href="#flexible-point-distribution" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p>Customize weights per module</p></li>
<li><p>Add bonus challenges</p></li>
<li><p>Include participation components</p></li>
</ul>
</section>
<section id="project-based-assessment">
<h3>Project-Based Assessment<a class="headerlink" href="#project-based-assessment" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p>Combine modules into larger projects</p></li>
<li><p>Capstone project for final evaluation</p></li>
<li><p>Portfolio development opportunities</p></li>
</ul>
</section>
</section>
<hr class="docutils" />
<section id="instructor-resources">
<h2>Instructor Resources<a class="headerlink" href="#instructor-resources" title="Link to this heading">#</a></h2>
<section id="documentation">
<h3>Documentation<a class="headerlink" href="#documentation" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p><a class="reference internal" href="../instructor-guide.html"><span class="std std-doc">Complete Instructor Guide</span></a> - Detailed setup and workflow</p></li>
<li><p><a class="reference internal" href="#../../NBGrader_Quick_Reference.md"><span class="xref myst">Quick Reference Card</span></a> - Essential commands</p></li>
<li><p>Module-specific teaching notes in each chapter</p></li>
</ul>
</section>
<section id="support-tools">
<h3>Support Tools<a class="headerlink" href="#support-tools" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">tito</span> <span class="pre">module</span> <span class="pre">status</span> <span class="pre">--comprehensive</span></code> - System health dashboard</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">tito</span> <span class="pre">nbgrader</span> <span class="pre">status</span></code> - Assignment tracking</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">tito</span> <span class="pre">nbgrader</span> <span class="pre">report</span></code> - Grade export</p></li>
</ul>
</section>
<section id="community">
<h3>Community<a class="headerlink" href="#community" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p>GitHub Issues for technical support</p></li>
<li><p>Instructor discussion forum (coming soon)</p></li>
<li><p>Regular updates and improvements</p></li>
</ul>
</section>
</section>
<hr class="docutils" />
<section id="success-stories">
<h2>🌟 Success Stories<a class="headerlink" href="#success-stories" title="Link to this heading">#</a></h2>
<section id="university-adoption">
<h3>University Adoption<a class="headerlink" href="#university-adoption" title="Link to this heading">#</a></h3>
<blockquote>
<div><p>“TinyTorch transformed our ML systems course. Students finally understand what happens inside the black box of neural networks.”<br />
<em>Professor of Computer Science</em></p>
</div></blockquote>
</section>
<section id="student-testimonials">
<h3>Student Testimonials<a class="headerlink" href="#student-testimonials" title="Link to this heading">#</a></h3>
<blockquote>
<div><p>“Building my own PyTorch gave me confidence to tackle any ML engineering challenge.”<br />
<em>Recent Graduate, now ML Engineer</em></p>
</div></blockquote>
</section>
<section id="industry-preparation">
<h3>Industry Preparation<a class="headerlink" href="#industry-preparation" title="Link to this heading">#</a></h3>
<blockquote>
<div><p>“TinyTorch students are job-ready. They understand both the theory and the engineering.”<br />
<em>Hiring Manager, AI Startup</em></p>
</div></blockquote>
</section>
</section>
<hr class="docutils" />
<section id="next-steps">
<h2>📞 Next Steps<a class="headerlink" href="#next-steps" title="Link to this heading">#</a></h2>
<ol class="arabic simple">
<li><p><strong>📖 Read the <a class="reference internal" href="../instructor-guide.html"><span class="std std-doc">Instructor Guide</span></a></strong> for complete details</p></li>
<li><p><strong>🚀 Start with Module 0: <a class="reference internal" href="#../chapters/00-introduction.md"><span class="xref myst">Introduction</span></a></strong> to see the system overview</p></li>
<li><p><strong>💻 Set up your environment</strong> following the guide</p></li>
<li><p><strong>📧 Contact us</strong> for instructor support</p></li>
</ol>
<hr class="docutils" />
<p><em>Ready to teach the most comprehensive ML systems course? Lets build something amazing together!</em> 🎓</p>
</section>
</section>
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