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‎_sass/color_schemes/wider.scss‎

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$content-width: 75rem;
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// wider.scss is already setting the content width
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$content-width: 75rem;
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// Global styles
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body {
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margin: 0 auto;
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font-family: 'Inter', 'Helvetica Neue', Arial, sans-serif;
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font-size: 1.1rem;
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background: #fafdff;
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color: black;
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}
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// Links
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a,
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a:visited {
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color: #397DFF !important; // force blue for all links
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text-decoration: underline;
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font-weight: 500;
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transition: color 0.15s;
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}
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a:hover,
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a:focus {
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color: #245dcc !important; // force dark blue for hover/focus
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text-decoration: underline;
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}
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// Headings
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h1, h2, h3, h4, h5, h6 {
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color: #397DFF;
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font-weight: 700;
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margin-top: 2.2rem;
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margin-bottom: 1.2rem;
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line-height: 1.2;
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letter-spacing: -0.5px;
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}
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h2 {
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font-size: 1.75rem;
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border-bottom: 1px solid #e0ebfa;
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padding-bottom: 0.2rem;
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}
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h3 {
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font-size: 1.3rem;
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}
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h4, h5, h6 {
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font-size: 1.05rem;
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font-weight: 600;
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}
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// Bold text
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strong, b {
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color: #397DFF;
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font-weight: 700;
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}
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// Table styles
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table {
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width: 100%;
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border-collapse: collapse;
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margin: 2rem 0;
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background: #fff;
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font-size: 1rem;
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}
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thead th {
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background: #e4ecfa;
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color: #397DFF;
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font-weight: 700;
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border-bottom: 2px solid #c6d5f9;
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padding: 0.7rem;
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}
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tbody td {
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border-bottom: 1px solid #e4ecfa;
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padding: 0.7rem;
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vertical-align: top;
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}
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tbody tr:nth-child(even) {
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background: #f3f8fe;
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}
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.label {
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background: #397DFF;
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color: #fff !important; // ensures text stays white
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border-radius: 1.3em;
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padding: 0.22em 1.1em;
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font-size: 1em;
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font-family: 'Geist', Arial, sans-serif;
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font-weight: 800;
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display: inline-block;
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letter-spacing: 0.5px;
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}
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.label, .label * {
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color: #fff !important;
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}
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// Miscellaneous
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img {
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max-width: 100%;
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height: auto;
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border-radius: 4px;
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}
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blockquote {
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border-left: 4px solid #397DFF;
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background: #f0f6fe;
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padding: 0.6em 1em;
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margin: 1.5em 0;
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color: #397DFF;
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font-style: italic;
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}
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hr {
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border: none;
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border-top: 2px solid #e4ecfa;
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margin: 3rem 0;
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}
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.assignment-buttons {
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display: flex;
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align-items: center;
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gap: 0.5rem;
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}
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.assignment-buttons .label {
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font-size: 0.85rem;
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padding: 0.2em 0.9em;
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border-radius: 1em;
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}
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.colab-link {
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display: inline-flex;
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align-items: center;
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gap: 0.35rem;
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font-size: 0.9rem;
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font-weight: 600;
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color: #ff9933; // lighter orange tone
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text-decoration: none;
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transition: color 0.2s ease;
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}
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.colab-link:hover {
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color: #e6861f; // darker hover orange
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}
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.colab-link img {
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height: 1rem; // keeps logo small & neat
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width: auto;
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}
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‎docs/resources.md‎

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layout: home
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---
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# Additional Resources
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# <span style="color: #397DFF; font-weight: 350">Additional Resources</span>
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This page contains additional resources for each lecture to help you dive deeper into the topics covered.
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## Week 1: Welcome! and Introduction to Programming in Python
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*Coming soon...*
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## <span style="color: #397DFF">Week 1: Welcome! and Introduction to Programming in Python</span>
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- [Composing Programs Online Textbook] (https://www.composingprograms.com/)
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- [CS 61A Lecture Videos] (https://www.youtube.com/@JohnDeNero/playlists)
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- [Python Tutor] (https://pythontutor.com/)
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## Week 2: Data Structures
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## <span style="color: #397DFF">Week 2: Data Structures</span>
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*Coming soon...*
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## Week 3: Introduction to SWE I
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## <span style="color: #397DFF">Week 3: Introduction to SWE I</span>
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*Coming soon...*
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## Week 4: Introduction to SWE II
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## <span style="color: #397DFF">Week 4: Introduction to SWE II</span>
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*Coming soon...*
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## Week 5: Databases
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## <span style="color: #397DFF">Week 5: Databases</span>
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*Coming soon...*
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## Week 6: Linear Algebra for ML
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## <span style="color: #397DFF">Week 6: Linear Algebra for ML</span>
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*Coming soon...*
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## Week 7: Calculus for ML
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- [EECS 127 sp24 Reader](https://drive.google.com/file/d/1X-f6JTgsp8WHvOc4k2NcJgKm74hH2ZFD/view) - Vector Calculus
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- [EECS 127 sp24 - Vector Calculus I Recording](https://www.youtube.com/watch?v=QvnXLI4HwLM&list=PLnocShPlK-FsQ-Sflqs4tbX-dKhYZSD3g&index=8) - Watch until end
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- [EECS 127 sp24 - Vector Calculus II Recording](https://www.youtube.com/watch?v=0CJbfW4_Y3g&list=PLnocShPlK-FsQ-Sflqs4tbX-dKhYZSD3g&index=9) - Watch until 34:45
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- [MATH 53 fa22 notes - Directional Derivatives and the Gradient Vector](https://drive.google.com/file/d/1IUx13k688MkK0y7IPXn6jkONex-5vDtl/view)
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- [MATH 53 fa22 notes - Partial Derivatives, Tangent Planes, and Linear Approximations](https://drive.google.com/file/d/1MFwlXkN9N0RGNCZTtC9_wfPL42TnhieN/view)
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- [MATH 53 fa22 notes - The Chain Rule](https://drive.google.com/file/d/1kP-jRggb76k36Yibyawh9WBWVRyBSRhl/view)
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## <span style="color: #397DFF">Week 7: Calculus for ML</span>
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- [EECS 127 sp24 Reader](https://drive.google.com/file/d/1X-f6JTgsp8WHvOc4k2NcJgKm74hH2ZFD/view) - Vector Calculus
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- [EECS 127 sp24 - Vector Calculus I Recording](https://www.youtube.com/watch?v=QvnXLI4HwLM&list=PLnocShPlK-FsQ-Sflqs4tbX-dKhYZSD3g&index=8) - Watch until end
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- [EECS 127 sp24 - Vector Calculus II Recording](https://www.youtube.com/watch?v=0CJbfW4_Y3g&list=PLnocShPlK-FsQ-Sflqs4tbX-dKhYZSD3g&index=9) - Watch until 34:45
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- [MATH 53 fa22 notes - Directional Derivatives and the Gradient Vector](https://drive.google.com/file/d/1IUx13k688MkK0y7IPXn6jkONex-5vDtl/view)
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- [MATH 53 fa22 notes - Partial Derivatives, Tangent Planes, and Linear Approximations](https://drive.google.com/file/d/1MFwlXkN9N0RGNCZTtC9_wfPL42TnhieN/view)
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- [MATH 53 fa22 notes - The Chain Rule](https://drive.google.com/file/d/1kP-jRggb76k36Yibyawh9WBWVRyBSRhl/view)
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## Week 8: Probability for ML
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## <span style="color: #397DFF">Week 8: Probability for ML</span>
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*Coming soon...*
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## Week 9: Classical ML
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## <span style="color: #397DFF">Week 9: Classical ML</span>
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*Coming soon...*
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## Week 10: Deep Learning I
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## <span style="color: #397DFF">Week 10: Deep Learning I</span>
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*Coming soon...*
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## Week 11: Deep Learning II
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## <span style="color: #397DFF">Week 11: Deep Learning II</span>
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*Coming soon...*
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## Week 12: Introduction to MLE
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## <span style="color: #397DFF">Week 12: Introduction to MLE</span>
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*Coming soon...*

‎docs/syllabus.md‎

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layout: home
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---
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# Syllabus
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# <span style="color: #397DFF; font-weight: 350">Syllabus</span>
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## Course Format
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## <span style="color: #397DFF">Course Format</span>
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- **Length**: 3 hours, once a week, in person (or hybrid, depending on availability).
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- **Time & Date**: Saturday or Sunday from 10am–1pm.
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## Contact Information
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## <span style="color: #397DFF">Contact Information</span>
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- **EdVPs**: [[email protected]](mailto:[email protected])
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- **Mentored PMs**: [[email protected]](mailto:[email protected])
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## Course Description
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## <span style="color: #397DFF">Course Description</span>
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This 12-week course offers a foundational introduction to SWE and ML/AI, designed in response to the emerging industry shift toward AI-integrated systems. New members will gain hands-on experience with Python programming, explore modern frameworks, and develop machine learning models including neural networks.
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## Prerequisites
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## <span style="color: #397DFF">Prerequisites</span>
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- Taken or concurrently enrolled in **CS 61A / Data 8** OR have previous coding experience
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- No prior industry experience
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- Little to no prior web dev experience
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- Completed **1 or fewer upper-division CS/Data Science technical courses** at UC Berkeley
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## Desired Course Outcomes
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## <span style="color: #397DFF">Desired Course Outcomes</span>
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By the end of the 12 weeks, we hope you:
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- Are comfortable programming in **Python** and **Java**.
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- Know common data structures (Arrays, LinkedLists, Trees, HashTables)
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- Understand fundamental ML/AI concepts (optimization, neural networks)
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- Feel comfortable working in a **team environment**, similar to that found in industry
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## Course Content
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## <span style="color: #397DFF">Course Content</span>
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The course will roughly follow this outline (subject to change based on member needs, popularity, and resources):
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1. Programming in Python
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2. Data Structures
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7. Deep Learning
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8. Introduction to MLE
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## Course Outline
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## <span style="color: #397DFF">Course Outline</span>
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- **Weeks 1–4**: Welcome! and Introduction to Programming in Python, Data Structures, and Introduction to SWE
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- **Weeks 5–8**: Databases and Math for ML
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- **Weeks 9–12**: Classical ML, Deep Learning, and Introduction to MLE
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## Homeworks
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## <span style="color: #397DFF">Homeworks</span>
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Throughout the course, we’ll be releasing homeworks that accompany lectures.
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- **Deadline policy**: Homework must be submitted **on the day of the next lecture** (no rolling extensions).
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- **Homework parties**: Weekly, right after lecture — a space to ask questions and work together with your fellow members.
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⚠️ Failure to adhere to the above policies may impact your eligibility to become a **client developer** the following semester and attend **Codebase social events**.
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## Midterm
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## <span style="color: #397DFF">Midterm</span>
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Before switching gears to the ML portion of the curriculum, you’ll take a **60-minute midterm**.
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- Mirrors lecture examples & homework problems
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- Not designed to trick you — just to help us see how to best support the class
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- Scores will not be scrutinized heavily
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- 🎉 Expect some festivities after the exam!
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## Final Project
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## <span style="color: #397DFF">Final Project</span>
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You’ll complete a **final course project** in teams of **3–4 people** (with 1–2 client devs and 1–2 mentored devs).
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- **Showcase**: At Codebase’s banquet, where you’ll present everything you’ve learned ⭐⭐⭐
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- **Requirements**: Must incorporate full stack, databases, SWE practices, or machine learning

‎index.md‎

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# CRUP Fall 2025
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# <span style="color: #397DFF; font-weight: 490;">CRUP Fall 2025</span>
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Welcome to **Codebase's Ramp Up Program (CRUP)**! We will dive into **Software Engineering, Machine Learning, and AI** through hands-on work in **Python, Java,** and **SQL**, and frameworks like **PyTorch, scikit-learn, and more!**.
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---
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## Schedule
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## <span style="color: #397DFF;">Schedule</span>
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<table>
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<thead>
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<td>Sep 13</td>
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<td>Welcome! and Intro to Programming in Python (<a href="https://docs.google.com/presentation/d/1qIpgvEjE79MUhFeDaQFaAQRr6w-uNUwvFq7xgK_CEgM/edit?usp=sharing">slides</a>)</td>
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<td>
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<span class="label"><strong>Homework</strong></span>
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<a target="_blank"
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href="https://colab.research.google.com/github/codebase-berkeley/crup-code/blob/main/week-1/intro_to_python.ipynb">
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<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"/>
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</a>
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<div class="assignment-buttons">
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<span class="label"><strong>Homework</strong></span>
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<a class="colab-link" target="_blank" href="https://colab.research.google.com/github/codebase-berkeley/crup-code/blob/main/week-1/intro_to_python.ipynb">
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<img src="https://colab.research.google.com/img/colab_favicon_256px.png" alt="Colab"/> Open in Colab
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</a>
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</div>
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</td>
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<td>Anika</td>
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</tr>

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