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‎docs/past/fa25.md‎

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---
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title: NMEP Fall 2025
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nav_order: 1
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parent: past
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layout: home
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---
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## NMEP Fall 2025
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Welcome everyone!
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In the New Member Education Program (NMEP), we'll be paving a sturdy ML foundation for you—from classical ML to diffusion models. Come hungry to learn and get to know the rest of your class!
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Your instructors this semester are [Aaditya Agnihotri](mailto:aaditya_agni@berkeley.edu), [Aditya Ghai](mailto:aditya_ghai@berkeley.edu) and [Tanmayi Dasari](mailto:tanmayi_dasari@berkeley.edu)!
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### Schedule
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<table style="table-layout: fixed;">
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<colgroup>
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<col span="1" style="width: 30px;">
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<col span="1" style="width: 60px;">
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<col span="1" style="width: calc(40% - 120px)">
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<col span="1" style="width: calc(60% - 120px)">
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<col span="1" style="width: 150px;">
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</colgroup>
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<tbody>
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<tr> <th style="max-width: 30px;">Week</th> <th>Date</th> <th>Lecture</th> <th>Assignments</th> <th>Lecturer(s)</th> </tr>
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<tr>
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<td style="max-width: 30px;">1</td>
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<td>Sep 15</td>
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<td>Intro + Background Review
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(<a href="https://docs.google.com/presentation/d/1bjh2TxylNo9ICEUp-4cGwDpdBBQUuvf6BmNdUQEF6AY">slides</a>)
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</td>
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<td>
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<span class="label"><strong>Lecture Exercise</strong></span>
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<a href="https://drive.google.com/file/d/1p_QsJX3d3T3mSeePed0_CDieP39g83Pc/view?usp=drive_link">Rockfall</a>
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-
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<a href="https://drive.google.com/file/d/1r1_Kj7nzAd10DLk9D87AZet81uEnhBIa/view?usp=drive_link">Sol.</a>
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<br>
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<span class="label label-yellow"><strong>Homework 1</strong> (due 9/26)</span>
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<a href="/nmep/assets/hw1/hw1-numpy.ipynb">Numpy</a>
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<a href="/nmep/assets/hw1/hw1-intro-pytorch.ipynb">Pytorch</a>
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</td>
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<td>
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Aaditya, Tejas
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</td>
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</tr>
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<tr>
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<td style="max-width: 30px;">2</td>
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<td>Sep 22</td>
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<td>Classical ML
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(<a href="https://docs.google.com/presentation/d/1K2fFV9_dYichrDxjXkIZ04aJ_cgfNfeIc6JI5hesdQY">slides</a>)
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</td>
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<td>
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<span class="label label-yellow"><strong>Homework 1</strong> (due 9/26)</span>
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<a href="/nmep/assets/hw1/hw1-math.pdf">Math</a>
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</td>
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<td>Aaditya, Aditya, Tanmayi</td>
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</tr>
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<tr>
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<td style="max-width: 30px;">3</td>
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<td>Sep 29</td>
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<td>Deep Learning (<a href="https://docs.google.com/presentation/d/14RE7f7HXmqpzRjGxOvJunsJ-vnWSvi7ENvag4pGrW1c/">slides</a>)</td>
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<td>
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<span class="label label-red"><strong>Reading</strong></span>
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<a href="https://web.stanford.edu/class/ee384m/Handouts/HowtoReadPaper.pdf">How to read a paper</a>
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<!-- <span class="label"><strong>Worksheet</strong></span>
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<a href="/nmep/assets/hw2/wk2-nns-worksheet.pdf">NNs</a> -->
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<br>
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<span class="label label-yellow"><strong>Homework 2</strong> (due 10/6)</span>
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<a href="https://drive.google.com/drive/folders/1fSEXCMcF8t8U4UCQDlkncTFR5b72KhPs">Word Embeddings</a>
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</td>
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<td>Aaditya, Aditya, Tanmayi</td>
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</tr>
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<tr>
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<td style="max-width: 30px;">4</td>
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<td>Oct 6</td>
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<td>Computer Vision (<a href="https://docs.google.com/presentation/d/15xuS2jh0KqBKpTMyNwb-DhgsvEER2-A8IFNwBd6RzZE/edit?usp=sharing">slides</a>)</td>
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<td>
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<span class="label"><strong>Lecture Exercise</strong></span>
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<a href="https://colab.research.google.com/drive/1aBFBPwhhulkr8n2eRkGygPJsrTekXNk6?usp=sharing">YOLO</a>
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<br />
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<span class="label label-yellow"><strong>Homework 3</strong> (due 10/20)</span>
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<a href="docs/homeworks/hw3.html">Model Zhu</a>
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</td>
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<td>Tim & Andrew</td>
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</tr>
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<tr>
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<td style="max-width: 30px;">5</td>
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<td>Oct 13</td>
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<td>NLP + Transformers I (<a href="https://docs.google.com/presentation/d/1QAqkpaoEulM478d3REZHvZYb_uNEQe8XptfVyPF_I4c/edit?usp=sharing">slides</a>)</td>
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<td></td>
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<td>Bharat, Tejas</td>
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</tr>
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<tr>
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<td style="max-width: 30px;">6</td>
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<td>Oct 20</td>
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<td>Transformers II + LLMs (<a href="https://docs.google.com/presentation/d/11Cg3YT4JDLdou8v18p7sruhxOvNXnLt8swQL5sEkf2E/edit?usp=sharing">slides</a>) </td>
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<td>
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<span class="label"><strong>Worksheet</strong></span>
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<a href="/assets/hw4/transformers_pseudo_fa25.pdf">Transformer Basics</a>
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<br>
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<span class="label label-purple"><strong>Solutions</strong></span>
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<a href="/assets/hw4/transformers_pseudo_fa25_sol.pdf">Transformer Basics Solutions</a>
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<br>
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<span class="label label-yellow"><strong>Homework 4</strong> (due 3/28)</span>
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<a href="docs/homeworks/hw4.html">Transformers!</a>
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</td>
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<td>Aaditya</td>
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</tr>
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<tr>
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<td style="max-width: 30px;">7</td>
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<td>TBD</td>
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<td><strong>Midterm</strong></td>
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<td>
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<span class="label label-red"><strong>NMEP Midterm</strong></span>
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</td>
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<td></td>
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</tr>
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<tr>
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<td style="max-width: 30px;">10</td>
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<td>Nov 3</td>
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<td>State Space Models and Self-Supervised Learning(<a href="https://docs.google.com/presentation/d/1_whj4gntfZ35t_3uzTJLfMXKF7DJouAzeMIdG_iQPGM/edit?usp=sharing">slides</a>)</td>
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<td>
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<span class="label"><strong>Lecture Exercise</strong></span>
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<!-- <a href="https://github.com/tejasprabhune/lec10-diffusion">U-Net</a> -->
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</td>
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<td>Tejas, Julia</td>
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</tr>
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<tr>
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<td style="max-width: 30px;">8</td>
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<td>Nov 10</td>
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<td>GANs and Diffusion(<a href="https://docs.google.com/presentation/d/1EK1BM6dbD8GslEg218Qfz579cg_KcQC6T91pF4lhjx4/edit?usp=sharing">slides</a>)</td>
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<td>
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<span class="label label-yellow"><strong>Homework 5 Part 1</strong> (due Nov 17)</span>
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<a href="https://colab.research.google.com/drive/1FPC6aq6oye9VMVNYb837pCwj3Bv9zsBy?usp=sharing">U-Nets and Diffusion!</a>
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</td>
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<td>Aditya, Aaditya</td>
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</tr>
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<tr>
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<td style="max-width: 30px;">9</td>
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<td>Nov 17</td>
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<td>RL(<a href="https://docs.google.com/presentation/d/1NU4cYmHmOZGF3L_j78qVQ1LKqcu7dk7dtSzio1kn0iA/edit?usp=sharing">slides</a>)</td>
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<td>
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<!--<span class="label">
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<strong>Lecture Exercise</strong>
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</span>
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<a href="https://colab.research.google.com/drive/1A8OUfUPW4DOSbQ8Ieb1soa_AsPR7IQOy?usp=sharing">Ant PPO</a> -->
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</td>
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<td>Tanmayi</td>
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</tr>
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<tr>
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<td style="max-width: 30px;">11</td>
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<td>Nov 24</td>
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<td>AI Safety</td>
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<td><span class="label label-green"><strong>Final Project Checkpoint</strong></span></td>
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<td>Andrew</td>
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</tr>
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<tr>
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<td style="max-width: 30px;">12</td>
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<td>TBD</td>
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<td><strong>Final project showcase</strong></td>
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<td><span class="label label-green"><strong>Final Project Due</strong></span></td>
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<td></td>
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</tr>
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</tbody>
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</table>
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[Just the Docs]: https://just-the-docs.github.io/just-the-docs/
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[GitHub Pages]: https://github.com/just-the-docs/just-the-docs-template/blob/main/README.md
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[README]: https://github.com/just-the-docs/just-the-docs-template/blob/main/README.md
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[Jekyll]: https://jekyllrb.com
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[GitHub Pages / Actions workflow]: https://github.blog/changelog/2022-07-27-github-pages-custom-github-actions-workflows-beta/
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[use this template]: https://github.com/just-the-docs/just-the-docs-template/generate

‎docs/past/past.md‎

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## Past Offerings
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<br>
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<a href="/nmep/docs/past/fa25.html">Fall 2025</a>
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<a href="/nmep/docs/past/fa24.html">Fall 2024</a>
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<a href="https://machine-learning-berkeley.gitbook.io/nmep-website-1">Spring 2024</a>

‎index.md‎

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---
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title: NMEP Fall 2025
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title: NMEP Spring 2026
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nav_order: 1
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layout: home
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---
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## NMEP Fall 2025
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## NMEP Spring 2026
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Welcome everyone!
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In the New Member Education Program (NMEP), we'll be paving a sturdy ML foundation for you—from classical ML to diffusion models. Come hungry to learn and get to know the rest of your class!
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Your instructors this semester are [Aaditya Agnihotri](mailto:aaditya_agni@berkeley.edu), [Aditya Ghai](mailto:aditya_ghai@berkeley.edu) and [Tanmayi Dasari](mailto:tanmayi_dasari@berkeley.edu)!
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Your instructors this semester are TBD!
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### Schedule

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