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- Delete outdated site/ directory - Rename docs/ → site/ to match original architecture intent - Update all GitHub workflows to reference site/: - publish-live.yml: Update paths and build directory - publish-dev.yml: Update paths and build directory - build-pdf.yml: Update paths and artifact locations - Update README.md: - Consolidate site/ documentation (website + PDF) - Update all docs/ links to site/ - Test successful: Local build works with all 40 pages The site/ directory now clearly represents the course website and documentation, making the repository structure more intuitive. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
227 lines
11 KiB
Markdown
227 lines
11 KiB
Markdown
# TinyTorch for Instructors: Complete ML Systems Course
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<div style="background: #d4edda; border: 1px solid #28a745; padding: 1.5rem; border-radius: 0.5rem; margin: 2rem 0;">
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<h3 style="margin: 0 0 0.5rem 0; color: #155724;">✅ Classroom Integration Available</h3>
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<p style="margin: 0; color: #155724;">TinyTorch includes complete <a href="https://nbgrader.readthedocs.io/" style="color: #155724; text-decoration: underline; font-weight: bold;">NBGrader</a> integration with automated grading workflows. See the <a href="../instructor-guide.html" style="color: #155724; font-weight: bold;">Complete Instructor Guide</a> for setup, grading rubrics, and sample solutions.</p>
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</div>
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<div style="background: #e3f2fd; border: 1px solid #2196f3; padding: 1rem; border-radius: 0.5rem; margin: 1rem 0;">
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<strong>📖 Course Vision:</strong> This page describes the planned TinyTorch classroom experience.<br>
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<strong>📖 For Current Usage:</strong> Students should follow the <a href="../student-workflow.html">Student Workflow</a> guide.
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</div>
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<div style="background: #f8f9fa; border: 1px solid #dee2e6; padding: 2rem; border-radius: 0.5rem; text-align: center; margin: 2rem 0;">
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<h2 style="margin: 0 0 1rem 0; color: #495057;">🏫 Planned: Turn-Key ML Systems Education</h2>
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<p style="font-size: 1.1rem; margin: 0; color: #6c757d;">Transform students from framework users to systems engineers</p>
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</div>
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**Vision:** Replace black-box API courses with deep systems understanding. Students will build neural networks from scratch, understand every operation, and graduate job-ready for ML engineering roles.
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---
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## 🎯 Planned Course Infrastructure
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<div style="background: #f8f9fa; border-left: 4px solid #007bff; padding: 1.5rem; margin: 1.5rem 0;">
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<h4 style="margin: 0 0 1rem 0; color: #0056b3;">Planned Features: Production-Ready Course Materials</h4>
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<div style="display: grid; grid-template-columns: 1fr 1fr; gap: 1rem;">
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<div>
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<ul style="margin: 0; padding-left: 1rem;">
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<li><strong>Three-tier progression</strong> (20 modules) with [NBGrader](https://nbgrader.readthedocs.io/) integration</li>
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<li><strong>Automated grading</strong> for immediate feedback</li>
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<li><strong>Professional CLI tools</strong> for development workflow</li>
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<li><strong>Real datasets</strong> (CIFAR-10, text generation)</li>
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</ul>
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</div>
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<div>
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<ul style="margin: 0; padding-left: 1rem;">
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<li><strong>Complete instructor guide</strong> with setup & grading ([available now](../instructor-guide.md))</li>
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<li><strong>Flexible pacing</strong> (14-18 weeks depending on depth)</li>
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<li><strong>Industry practices</strong> (Git, testing, documentation)</li>
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<li><strong>Academic foundation</strong> from university research</li>
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</ul>
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</div>
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</div>
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</div>
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**Planned Course Duration:** 14-16 weeks (flexible pacing)
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**Student Outcome:** Complete ML framework supporting vision AND language models
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**Current Status:** Complete NBGrader integration available! See the [Instructor Guide](../instructor-guide.md) for setup, grading workflows, and sample solutions.
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---
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## 🌟 Why TinyTorch for Your Classroom
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<div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(300px, 1fr)); gap: 1.5rem; margin: 2rem 0;">
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<div style="background: #e8f5e8; padding: 1.5rem; border-radius: 0.5rem; border-left: 4px solid #4caf50;">
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<h4 style="margin: 0 0 1rem 0; color: #2e7d32;">🎯 Deep Learning Outcomes</h4>
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<p style="margin: 0 0 0.5rem 0; font-weight: 600;">Students build neural networks from scratch</p>
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<ul style="margin: 0; font-size: 0.9rem; color: #64748b;">
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<li>Graduates understand deep systems architecture</li>
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<li>Can debug ML issues from first principles</li>
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<li>Prepared for ML engineering roles</li>
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<li>Confident implementing novel architectures</li>
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</ul>
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</div>
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<div style="background: #fff3e0; padding: 1.5rem; border-radius: 0.5rem; border-left: 4px solid #ff9800;">
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<h4 style="margin: 0 0 1rem 0; color: #f57c00;">⚡ Zero-Setup Teaching</h4>
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<p style="margin: 0 0 0.5rem 0; font-weight: 600;">30-minute instructor setup, then focus on teaching</p>
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<ul style="margin: 0; font-size: 0.9rem; color: #64748b;">
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<li><strong>NBGrader integration</strong>: Automated grading & feedback</li>
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<li><strong>One-command workflows</strong>: Generate, release, collect assignments</li>
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<li><strong>Progress dashboards</strong>: Track all students at a glance</li>
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<li><strong>Flexible pacing</strong>: Adapt to your semester schedule</li>
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</ul>
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</div>
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<div style="background: #f3e5f5; padding: 1.5rem; border-radius: 0.5rem; border-left: 4px solid #9c27b0;">
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<h4 style="margin: 0 0 1rem 0; color: #7b1fa2;">🏆 Industry-Standard Workflow</h4>
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<p style="margin: 0 0 0.5rem 0; font-weight: 600;">Students learn professional ML engineering practices</p>
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<ul style="margin: 0; font-size: 0.9rem; color: #64748b;">
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<li><strong>Git workflow</strong>: Feature branches, commits, merges</li>
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<li><strong>CLI tools</strong>: Professional development environment</li>
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<li><strong>Testing culture</strong>: Every implementation immediately validated</li>
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<li><strong>Documentation</strong>: Clear code, explanations, insights</li>
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</ul>
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</div>
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<div style="background: #e1f5fe; padding: 1.5rem; border-radius: 0.5rem; border-left: 4px solid #03a9f4;">
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<h4 style="margin: 0 0 1rem 0; color: #0277bd;">🔬 Deep Systems Understanding</h4>
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<p style="margin: 0 0 0.5rem 0; font-weight: 600;">Beyond APIs: Students understand how ML really works</p>
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<ul style="margin: 0; font-size: 0.9rem; color: #64748b;">
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<li><strong>Memory analysis</strong>: Profile and optimize resource usage</li>
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<li><strong>Performance insights</strong>: Understand computational complexity</li>
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<li><strong>Production context</strong>: How PyTorch/TensorFlow actually work</li>
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<li><strong>Systems thinking</strong>: Architecture, scaling, optimization</li>
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</ul>
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</div>
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</div>
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---
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## Course Module Overview
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The TinyTorch course consists of 20 progressive modules organized into learning stages.
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**📖 See [Complete Course Structure](../chapters/00-introduction.md)** for detailed module descriptions, learning objectives, and prerequisites for each module.
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---
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## Academic Learning Goals
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**What Students Will Achieve:**
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- Build deep systems understanding through implementation
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- Bridge gap between ML theory and engineering practice
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- Prepare for real-world ML systems challenges
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- Enable research into novel architectures and optimizations
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**Core Capabilities Developed:**
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- Implement neural networks from scratch
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- Understand autograd and backpropagation deeply
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- Optimize models for production deployment
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- Build complete frameworks supporting vision and language
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---
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## 🚀 Quick Start for Instructors
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<div style="background: #f8f9fa; border: 1px solid #dee2e6; border-radius: 0.5rem; padding: 2rem; margin: 2rem 0;">
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<h3 style="margin: 0 0 1rem 0; text-align: center; color: #495057;">⏱️ 30 Minutes to Teaching-Ready Course</h3>
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<p style="text-align: center; margin: 0 0 1.5rem 0; color: #6c757d;">Three simple steps to transform your ML teaching</p>
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<div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(250px, 1fr)); gap: 1.5rem;">
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<div style="background: white; padding: 1.5rem; border-radius: 0.5rem; border: 1px solid #dee2e6;">
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<h4 style="color: #495057; margin: 0 0 0.5rem 0;">1️⃣ Clone & Setup (10 min)</h4>
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<div style="background: #f8f9fa; padding: 1rem; border-radius: 0.25rem; font-family: monospace; font-size: 0.85rem; margin: 0.5rem 0;">
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git clone TinyTorch<br>
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cd TinyTorch<br>
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source .venv/bin/activate<br>
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pip install -r requirements.txt
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</div>
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<p style="font-size: 0.9rem; margin: 0; color: #6c757d;">One-time environment setup</p>
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</div>
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<div style="background: white; padding: 1.5rem; border-radius: 0.5rem; border: 1px solid #dee2e6;">
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<h4 style="color: #495057; margin: 0 0 0.5rem 0;">2️⃣ Initialize Course (10 min)</h4>
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<div style="background: #f8f9fa; padding: 1rem; border-radius: 0.25rem; font-family: monospace; font-size: 0.85rem; margin: 0.5rem 0;">
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tito nbgrader init<br>
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tito module status --comprehensive
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</div>
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<p style="font-size: 0.9rem; margin: 0; color: #6c757d;">NBGrader integration & health check</p>
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</div>
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<div style="background: white; padding: 1.5rem; border-radius: 0.5rem; border: 1px solid #dee2e6;">
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<h4 style="color: #495057; margin: 0 0 0.5rem 0;">3️⃣ First Assignment (10 min)</h4>
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<div style="background: #f8f9fa; padding: 1rem; border-radius: 0.25rem; font-family: monospace; font-size: 0.85rem; margin: 0.5rem 0;">
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tito nbgrader generate 01_tensor<br>
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tito nbgrader release 01_tensor
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</div>
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<p style="font-size: 0.9rem; margin: 0; color: #6c757d;">Ready to distribute to students!</p>
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</div>
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</div>
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<div style="text-align: center; margin-top: 1.5rem;">
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<a href="../instructor-guide.html" style="display: inline-block; background: #007bff; color: white; padding: 0.5rem 1rem; border-radius: 0.25rem; text-decoration: none; font-weight: 500; margin-right: 1rem;">📖 Complete Instructor Guide</a>
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<a href="ta-guide.html" style="display: inline-block; background: #28a745; color: white; padding: 0.5rem 1rem; border-radius: 0.25rem; text-decoration: none; font-weight: 500;">👥 TA Guide</a>
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<a href="../testing-framework.html" style="display: inline-block; background: #28a745; color: white; padding: 0.5rem 1rem; border-radius: 0.25rem; text-decoration: none; font-weight: 500;">🧪 Testing Framework Guide</a>
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</div>
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</div>
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---
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## 📋 Assessment Options
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### Automated Grading
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- NBGrader integration for all modules
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- Automatic test execution and scoring
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- Detailed feedback generation
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### Flexible Point Distribution
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- Customize weights per module
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- Add bonus challenges
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- Include participation components
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### Project-Based Assessment
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- Combine modules into larger projects
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- Capstone project for final evaluation
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- Portfolio development opportunities
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---
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## Instructor Resources
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### Essential Documentation
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- **[Complete Instructor Guide](../instructor-guide.md)** - 30-minute setup, grading rubrics, sample solutions, common errors
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- **[TA Guide](ta-guide.md)** - Common student errors, debugging strategies, office hour patterns
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- Module-specific teaching notes in each ABOUT.md file
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- [Course Structure](../chapters/00-introduction.md) - Full curriculum overview
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- [Student Workflow](../student-workflow.md) - Essential development cycle
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### Support Tools
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- `tito module status --comprehensive` - System health dashboard
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- `tito nbgrader status` - Assignment tracking
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- `tito nbgrader report` - Grade export
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### Community
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- GitHub Issues for technical support
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- Instructor discussion forum (coming soon)
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- Regular updates and improvements
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---
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## 📞 Next Steps
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1. **📖 Review [Course Structure](../chapters/00-introduction.md)** for complete curriculum overview
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2. **🚀 Explore [Student Workflow](../student-workflow.md)** to understand the development cycle
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3. **💻 Set up your environment** using the [Quick Start Guide](../quickstart-guide.md)
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4. **📧 Contact us** via GitHub Issues for instructor support
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---
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*Ready to teach the most comprehensive ML systems course? Let's build something amazing together!* 🎓 |