mirror of
https://github.com/harvard-edge/cs249r_book.git
synced 2026-11-09 10:39:41 -06:00
Vijay Janapa Reddi
0bb05387f1
Simulated instructor walkthroughs (community college, R1 seminar, low- budget TinyML, robotics studio, industry training, department chair) surfaced practical gaps. This change closes the ones the site can answer: - Syllabi gain a short Assessment table with a suggested split (intro, scaling, TinyML, and the ETH Physical AI plan), each summing to 100%. - The introductory and scaling syllabi regain their suggested-papers lists for seminars and graduate sections. - TinyML and Edge AI list hardware options with prices from the Hardware Kits pages; TinyML names the Nano 33 BLE Sense the courseware uses. Hub entries state the starting cost per student or team. - Physical AI links the draft parts list with planning prices, and its hub entry sends "Studio labs" to the robot lab sequence. - The hub's Courses breadcrumb leads to the hub, not the intro syllabus. - The license page names whom to contact about uses outside non-commercial education, such as corporate training. - The course catalog's robot photo drops from 2.1 MB to 97 KB.
131 lines
9.8 KiB
Plaintext
131 lines
9.8 KiB
Plaintext
---
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pagetitle: "MLSysBook Courses"
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description: "Explore reusable ML systems course models, teaching materials, and community offerings."
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page-layout: full
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sidebar: false
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toc: false
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anchor-sections: false
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format:
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html:
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css:
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- _generated/community.css
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- assets/directory.css
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include-after-body:
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- text: '<script src="assets/directory.js"></script>'
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---
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```{=html}
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<div class="crs">
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<header class="crs-head directory-hero">
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<p class="opening-eyebrow">LEARN · BUILD · TEACH</p>
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<h1 id="directory-heading">Learn and teach with MLSysBook.</h1>
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<p id="directory-description">Explore readings, experiments, and teaching plans for machine learning systems. Follow a learning path or adapt the materials for a course.</p>
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<a class="directory-adopt" href="https://mlsysbook.ai/instructors/">Teaching your own course? Visit the Instructor Hub <span aria-hidden="true">↗</span></a>
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</header>
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<section class="hosted-courses" id="hosted-courses" aria-labelledby="hosted-title">
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<div class="directory-section-head"><h2 id="hosted-title">Course models and teaching materials</h2></div>
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<p class="directory-model-intro">These materials show how to organize MLSysBook readings and experiments into a course. Use a model as a starting point, adapt an existing offering, or contribute materials from your own teaching.</p>
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<div class="course-features">
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<article class="course-feature course-feature--core" data-kind="course" data-search="introduction to machine learning systems volume i foundations blueprint semester syllabus">
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<div class="course-feature-meta"><span>MLSysBook · Volume I</span><span class="course-status">Semester plan</span></div>
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<div class="course-feature-body course-feature-body--text"><div><p class="course-feature-kicker">SINGLE-MACHINE SYSTEMS</p><h3><a href="intro/">Introduction to Machine Learning Systems</a></h3><p>Data pipelines, training, optimization, and deployment, with a semester syllabus and implementation work.</p></div></div>
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<nav class="course-feature-footer course-family-links" aria-label="Foundations teaching resources">
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<a href="intro/">Course <span aria-hidden="true">→</span></a>
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<a href="https://mlsysbook.ai/instructors/foundations-syllabus.html">Syllabus <span aria-hidden="true">→</span></a>
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<a href="https://mlsysbook.ai/instructors/">For instructors <span aria-hidden="true">→</span></a>
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</nav>
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</article>
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<article class="course-feature course-feature--core" data-kind="course" data-search="scaling machine learning systems volume ii foundations blueprint semester syllabus">
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<div class="course-feature-meta"><span>MLSysBook · Volume II</span><span class="course-status">Semester plan</span></div>
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<div class="course-feature-body course-feature-body--text"><div><p class="course-feature-kicker">DISTRIBUTED SYSTEMS</p><h3><a href="scaling/">Scaling Machine Learning Systems</a></h3><p>Distributed training, communication, fault recovery, and serving, with systems labs and a capstone.</p></div></div>
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<nav class="course-feature-footer course-family-links" aria-label="Scaling teaching resources">
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<a href="scaling/">Course <span aria-hidden="true">→</span></a>
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<a href="https://mlsysbook.ai/instructors/scale-syllabus.html">Syllabus <span aria-hidden="true">→</span></a>
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<a href="https://mlsysbook.ai/instructors/">For instructors <span aria-hidden="true">→</span></a>
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</nav>
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</article>
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<article class="course-feature course-feature--tiny" data-kind="archive" data-search="tinyml tiny machine learning harvard cs249r cambridge united states 2020 2022 2023 archive embedded">
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<div class="course-feature-meta"><span>Microcontrollers · Volume I</span><span class="course-status">Historical materials</span></div>
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<div class="course-feature-body"><div><p class="course-feature-kicker">EMBEDDED MACHINE LEARNING</p><h3><a href="tinyml/">TinyML</a></h3><p>Model training and deployment on embedded devices, with syllabi, assignments, and example projects.</p></div><div class="tiny-course-mark" aria-hidden="true"><span>EMBEDDED</span><b>TinyML</b><small>Microcontrollers</small></div></div>
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<nav class="course-feature-footer course-family-links" aria-label="TinyML course resources">
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<a href="tinyml/">Course <span aria-hidden="true">→</span></a>
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<a href="tinyml/#syllabus">Syllabus <span aria-hidden="true">→</span></a>
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<a href="tinyml/#offerings">Selected projects <span aria-hidden="true">→</span></a>
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<a href="tinyml/#for-instructors">For instructors <span aria-hidden="true">→</span></a>
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</nav>
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</article>
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<article class="course-feature course-feature--edge" data-kind="course" data-search="edge ai linux raspberry pi deployment accelerator learning path">
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<div class="course-feature-meta"><span>MLSysBook · Volume I</span><span class="course-status">Learning path</span></div>
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<div class="course-feature-body"><div><p class="course-feature-kicker">INFERENCE NEAR THE DATA</p><h3><a href="edge-ai/">Edge AI</a></h3><p>Deployment on Linux edge devices, with hardware guides and companion teaching materials.</p></div><div class="tiny-course-mark" aria-hidden="true"><span>DEPLOYMENT</span><b>Edge AI</b><small>Linux · accelerators</small></div></div>
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<nav class="course-feature-footer course-family-links" aria-label="Edge AI learning resources">
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<a href="edge-ai/">Learning path <span aria-hidden="true">→</span></a>
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<a href="edge-ai/#materials">Materials <span aria-hidden="true">→</span></a>
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<a href="edge-ai/#for-instructors">For instructors <span aria-hidden="true">→</span></a>
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</nav>
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</article>
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<article class="course-feature course-feature--eth" data-kind="course" data-search="physical ai eth zurich zürich switzerland spring 2027 robot studio">
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<div class="course-feature-meta"><span>MLSysBook · Volume IV</span><span class="course-status">Draft course plan</span></div>
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<div class="course-feature-body"><div><p class="course-feature-kicker">ROBOTICS & LEARNED CONTROL</p><h3><a href="physical-ai/">Physical AI</a></h3><p>Robot policies, physical limits, and release decisions supported by measurements.</p></div><img src="assets/images/so101-follower.jpg" alt="SO-101 robot arm" width="155" height="155"></div>
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<nav class="course-feature-footer course-family-links" aria-label="Physical AI course resources">
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<a href="physical-ai/">Course <span aria-hidden="true">→</span></a>
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<a href="physical-ai/#offerings">Offerings <span aria-hidden="true">→</span></a>
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<a href="physical-ai/eth-spring-2027/syllabus.html">Syllabus <span aria-hidden="true">→</span></a>
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<a href="https://mlsysbook.ai/instructors/vol4/">For instructors <span aria-hidden="true">→</span></a>
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</nav>
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</article>
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</div>
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</section>
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<div class="crs-tabs" id="community-courses" role="tablist" aria-label="View">
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<button type="button" role="tab" class="crs-tab" data-view="courses" aria-selected="true">Courses</button>
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<button type="button" role="tab" class="crs-tab" data-view="schools" aria-selected="false">Schools</button>
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</div>
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<div class="crs-tools">
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<label class="crs-search"><span class="visually-hidden">Search courses and schools</span>
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<input id="crs-q" type="search" placeholder="Find your school, a course, or a country" autocomplete="off"></label>
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<div class="crs-chips" id="crs-chips" role="group" aria-label="Filter by type">
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<button type="button" class="crs-chip" data-kind="all" aria-pressed="true">All</button>
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<button type="button" class="crs-chip" data-kind="course" aria-pressed="false">Courses</button>
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<button type="button" class="crs-chip" data-kind="workshop" aria-pressed="false">Workshops</button>
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<button type="button" class="crs-chip" data-kind="archive" aria-pressed="false">Archives</button>
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</div>
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</div>
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<div class="directory-section-head"><h2 id="directory-title">Community courses and workshops</h2><span>Instructor-maintained offerings</span></div>
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<p class="crs-intro" id="crs-intro" hidden></p>
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<div class="crs-list" id="crs-list" aria-live="polite"></div>
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<section class="crs-readers" id="crs-readers" hidden aria-live="polite">
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<h2 id="crs-readers-title"></h2>
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<p id="crs-readers-note"></p>
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<ul id="crs-readers-list"></ul>
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</section>
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<p class="crs-empty" id="crs-empty" hidden></p>
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<section class="crs-early" id="crs-early" hidden>
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<h2>Also teaching with it</h2>
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<p>Instructors named in the Vol. I acknowledgments as early adopters, whose course pages are not public.</p>
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<ul id="crs-early-list"></ul>
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</section>
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<figure class="crs-mapwrap">
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<!-- adopters:courses -->
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<figcaption>Schools in the community directory. Select a pin to filter courses.</figcaption>
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</figure>
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<div class="crs-exits" id="crs-add">
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<a class="crs-exit crs-exit--primary" href="https://github.com/harvard-edge/cs249r_book/issues/new?template=add_course.yml" target="_blank" rel="noopener">
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<strong>Teaching with the book?</strong>
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<span>Share your syllabus or course website with the community.</span>
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</a>
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<a class="crs-exit" href="https://mlsysbook.ai/instructors/">
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<strong>Thinking of teaching it?</strong>
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<span>The Instructor Hub has syllabi, slides, labs, and a course map.</span>
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</a>
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</div>
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<p class="crs-note">Listed courses were added by their instructors, or have a public page, syllabus, or repository that assigns or links the book. Most courses never publish a reading list, so this is a partial list. If yours is listed and you would rather it were not, <a href="https://github.com/harvard-edge/cs249r_book/issues/new?template=add_course.yml" target="_blank" rel="noopener">open an issue</a>.</p>
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</div>
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```
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