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<!DOCTYPE html>
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<title>Getting Ready for the SCIPE LLM Workshop | Tutorials and Courses</title>
<meta name="description" content="Curated videos, courses, and tutorials to prepare for the SCIPE Workshop on Large Language Models.">
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<h1><a class="scipe-link" href="https://oh-scipe.github.io/" target="_blank" rel="noopener noreferrer">SCIPE</a> Workshop on LLMs</h1>
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<li><a href="index.html">Home</a></li>
<li><a href="index.html#about">About</a></li>
<li><a href="index.html#schedule">Schedule</a></li>
<li><a href="getting-ready.html" class="active">Getting Ready</a></li>
<li><a href="recordings.html">Recordings</a></li>
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<!-- Hero Section -->
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<h2>Getting Ready for the Workshop</h2>
<p class="hero-subtitle">Curated materials to help you prepare and get the most out of your workshop experience</p>
</div>
</div>
</section>
<!-- Introduction Section -->
<section class="section about">
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<p>Welcome! We've carefully selected a collection of high-quality learning materials to help you prepare for the <a class="scipe-link" href="https://oh-scipe.github.io/" target="_blank" rel="noopener noreferrer">SCIPE</a> Workshop on LLMs. Whether you're new to the field or looking to deepen your understanding, these resources will provide a solid foundation for the workshop.</p>
<p>Take your time exploring these materials at your own pace. You don't need to complete everything before the workshop, but familiarizing yourself with the basics will help you get more value from the hands-on sessions.</p>
</div>
</div>
</section>
<!-- Filter Section -->
<section class="section resources">
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<h3 class="filter-title">Filter by Difficulty Level</h3>
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<button class="filter-btn active" data-filter="all">All</button>
<button class="filter-btn" data-filter="beginner">Beginner</button>
<button class="filter-btn" data-filter="intermediate">Intermediate</button>
<button class="filter-btn" data-filter="advanced">Advanced</button>
</div>
</div>
</div>
</section>
<!-- Introduction to LLMs & Tutorials Section -->
<section class="section resources">
<div class="container">
<h2 class="section-title">Introduction to LLMs & Tutorials</h2>
<p class="section-intro">Start here to build a strong foundation in LLMs</p>
<div class="resource-list">
<div class="resource-item featured" data-level="beginner">
<div class="resource-badge">Recommended First</div>
<div class="resource-badge-level">Beginner</div>
<h4>Intro to Large Language Models</h4>
<p class="resource-author">Andrej Karpathy</p>
<p>An excellent starting point that covers the fundamentals of LLM architecture, training, and applications. Andrej Karpathy's clear explanations make complex concepts accessible to newcomers while providing valuable insights for experienced practitioners.</p>
<a href="https://youtu.be/zjkBMFhNj_g?si=WEaJjnjJdnbwgKx0" target="_blank" rel="noopener noreferrer">Watch Video</a>
</div>
<div class="resource-item" data-level="beginner">
<div class="resource-badge-level">Beginner</div>
<h4>How I Use LLMs</h4>
<p class="resource-author">Andrej Karpathy</p>
<p>Practical insights on leveraging LLMs in real-world workflows. Learn how an expert integrates these tools into daily work and discovers what's possible with current technology.</p>
<a href="https://youtu.be/EWvNQjAaOHw?si=6sB2JJMOx4QxsE4Q" target="_blank" rel="noopener noreferrer">Watch Video</a>
</div>
<div class="resource-item" data-level="beginner">
<div class="resource-badge-level">Beginner</div>
<h4>Large Language Models and Chatbots</h4>
<p class="resource-author">IBM Technology</p>
<p>A comprehensive playlist that covers LLM fundamentals and chatbot development. These videos break down complex topics into digestible segments, perfect for building understanding step by step.</p>
<a href="https://www.youtube.com/playlist?list=PLOspHqNVtKAAsiohuZj1Bt4XpA3_bkS3c" target="_blank" rel="noopener noreferrer">View Playlist</a>
</div>
<div class="resource-item" data-level="intermediate">
<div class="resource-badge-level">Intermediate</div>
<h4>Let's Reproduce GPT-2 (124M)</h4>
<p class="resource-author">Andrej Karpathy</p>
<p>An in-depth walkthrough of implementing GPT-2 from scratch. This is for those who want to understand the intricate details of transformer architecture and training. Highly rewarding for research-oriented participants.</p>
<a href="https://youtu.be/l8pRSuU81PU?si=PWySE_LphU9OcpQC" target="_blank" rel="noopener noreferrer">Watch Video</a>
</div>
<div class="resource-item" data-level="beginner">
<div class="resource-badge-level">Beginner</div>
<h4>Learn RAG From Scratch</h4>
<p class="resource-author">LangChain</p>
<p>Python AI tutorial on building retrieval-augmented generation systems. This practical guide shows you how to enhance LLMs with external knowledge, a technique we'll explore in the workshop.</p>
<a href="https://www.youtube.com/watch?v=sVcwVQRHIc8&t=228s" target="_blank" rel="noopener noreferrer">Watch Tutorial</a>
</div>
<div class="resource-item" data-level="beginner">
<div class="resource-badge-level">Beginner</div>
<h4>Neural Networks</h4>
<p class="resource-author">3Blue1Brown</p>
<p>Beautiful visual explanations of neural network concepts. If you're looking to understand the mathematical foundations with intuitive animations, this series is unmatched. Essential for grasping how neural networks actually work.</p>
<a href="https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi" target="_blank" rel="noopener noreferrer">View Playlist</a>
</div>
</div>
</div>
</section>
<!-- Generative AI & Language Models Courses Section -->
<section class="section resources-alt">
<div class="container">
<h2 class="section-title">Generative AI & Language Models Courses</h2>
<p class="section-intro">Comprehensive university courses on LLMs and transformers</p>
<div class="resource-list">
<div class="resource-item" data-level="beginner">
<div class="resource-badge-level">Beginner</div>
<h4>Transformers & Large Language Models (CME 295)</h4>
<p class="resource-author">Stanford University, 2025</p>
<p>A comprehensive course dedicated to transformer architectures and large language models. Covers both theoretical foundations and practical implementations, ideal for understanding the complete picture of modern LLMs.</p>
<a href="https://www.youtube.com/playlist?list=PLoROMvodv4rOCXd21gf0CF4xr35yINeOy" target="_blank" rel="noopener noreferrer">View Playlist</a> |
<a href="https://cme295.stanford.edu/" target="_blank" rel="noopener noreferrer">Course Page</a>
</div>
<div class="resource-item" data-level="intermediate">
<div class="resource-badge-level">Intermediate</div>
<h4>Language Modeling from Scratch (CS336)</h4>
<p class="resource-author">Stanford University, 2025</p>
<p>Build language models from the ground up. This course provides deep understanding of how transformers and language models work at a fundamental level.</p>
<a href="https://www.youtube.com/playlist?list=PLoROMvodv4rOY23Y0BoGoBGgQ1zmU_MT_" target="_blank" rel="noopener noreferrer">View Playlist</a> |
<a href="https://stanford-cs336.github.io/spring2025/" target="_blank" rel="noopener noreferrer">Course Page</a>
</div>
<div class="resource-item" data-level="intermediate">
<div class="resource-badge-level">Intermediate</div>
<h4>Deep Reinforcement Learning (CS224R)</h4>
<p class="resource-author">Stanford University, 2025</p>
<p>Explore deep reinforcement learning techniques that are increasingly important for training and fine-tuning LLMs with human feedback.</p>
<a href="https://www.youtube.com/watch?v=EvHRQhMX7_w" target="_blank" rel="noopener noreferrer">First Lecture</a> |
<a href="https://cs224r.stanford.edu/" target="_blank" rel="noopener noreferrer">Course Page</a>
</div>
<div class="resource-item" data-level="advanced">
<div class="resource-badge-level">Advanced</div>
<h4>Advanced Natural Language Processing (CS11-747)</h4>
<p class="resource-author">Carnegie Mellon University, Fall 2025</p>
<p>Dive deeper into NLP with this advanced course. Features video lectures covering cutting-edge topics in natural language processing. Great for those who want to explore beyond the basics.</p>
<a href="https://www.youtube.com/playlist?list=PLqC25OT8ZpD2-RuhyacIsODl5iJVgMjI3" target="_blank" rel="noopener noreferrer">View Playlist</a> |
<a href="https://cmu-l3.github.io/anlp-fall2025/" target="_blank" rel="noopener noreferrer">Course Page</a>
</div>
<div class="resource-item" data-level="advanced">
<div class="resource-badge-level">Advanced</div>
<h4>Inference Algorithms for Language Modeling (11-664/763)</h4>
<p class="resource-author">Carnegie Mellon University, Fall 2025</p>
<p>Focused course on inference optimization techniques and test-time scaling. Perfect for understanding how to make LLMs faster and more efficient, a topic we'll cover extensively in the workshop.</p>
<a href="https://www.youtube.com/watch?v=F-mduXzNcRQ" target="_blank" rel="noopener noreferrer">First Lecture</a> |
<a href="https://phontron.com/class/lminference-fall2025/" target="_blank" rel="noopener noreferrer">Course Page</a>
</div>
<div class="resource-item" data-level="intermediate">
<div class="resource-badge-level">Intermediate</div>
<h4>Deep Learning (CS230)</h4>
<p class="resource-author">Stanford University, Fall 2025</p>
<p>Build a strong foundation in deep learning concepts and applications. This course covers the fundamentals that underpin all modern LLMs. Recommended if you're new to deep learning.</p>
<a href="https://www.youtube.com/watch?v=_NLHFoVNlbg&t=12s" target="_blank" rel="noopener noreferrer">First Lecture</a> |
<a href="https://cs230.stanford.edu/" target="_blank" rel="noopener noreferrer">Course Page</a>
</div>
<div class="resource-item" data-level="advanced">
<div class="resource-badge-level">Advanced</div>
<h4>A Practical Introduction to Diffusion Models (6.S183)</h4>
<p class="resource-author">MIT, IAP 2025</p>
<p>Explore diffusion models, another important class of generative AI models. Understanding these techniques provides broader context for generative AI beyond language models.</p>
<a href="https://www.youtube.com/playlist?list=PL_1TbuIu65A_G908tHHvTnyQsueR17rMh" target="_blank" rel="noopener noreferrer">View Playlist</a> |
<a href="https://www.practical-diffusion.org/" target="_blank" rel="noopener noreferrer">Course Page</a>
</div>
<div class="resource-item" data-level="advanced">
<div class="resource-badge-level">Advanced</div>
<h4>An Introduction to Flow and Diffusion Models (6.S184)</h4>
<p class="resource-author">MIT, IAP 2025</p>
<p>Deep dive into flow and diffusion models with mathematical foundations. Advanced course for those interested in the theoretical aspects of generative models.</p>
<a href="https://www.youtube.com/playlist?list=PL_1TbuIu65A9rac2dMLkvXvPS5YHtADRF" target="_blank" rel="noopener noreferrer">View Playlist</a> |
<a href="https://diffusion.csail.mit.edu/2026/index.html" target="_blank" rel="noopener noreferrer">Course Page</a>
</div>
</div>
</div>
</section>
<!-- Background Courses Section -->
<section class="section resources">
<div class="container">
<h2 class="section-title">Background & Foundations</h2>
<p class="section-intro">Mathematical foundations for understanding LLMs</p>
<div class="courses-section">
<h3 class="subsection-title">Linear Algebra</h3>
<div class="resource-list">
<div class="resource-item" data-level="beginner">
<div class="resource-badge-level">Beginner</div>
<h4>Essence of Linear Algebra</h4>
<p class="resource-author">3Blue1Brown</p>
<p>Intuitive visual explanations of linear algebra concepts. Perfect for understanding the mathematical foundations behind neural networks and transformers.</p>
<a href="https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab" target="_blank" rel="noopener noreferrer">View Playlist</a>
</div>
<div class="resource-item" data-level="beginner">
<div class="resource-badge-level">Beginner</div>
<h4>Linear Algebra (18.06)</h4>
<p class="resource-author">MIT OpenCourseWare</p>
<p>Comprehensive introduction to linear algebra from MIT. Covers vectors, matrices, eigenvalues, and more - all essential for understanding deep learning.</p>
<a href="https://www.youtube.com/playlist?list=PL221E2BBF13BECF6C" target="_blank" rel="noopener noreferrer">View Playlist</a> |
<a href="https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/" target="_blank" rel="noopener noreferrer">Course Page</a>
</div>
<div class="resource-item" data-level="intermediate">
<div class="resource-badge-level">Intermediate</div>
<h4>Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (18.065)</h4>
<p class="resource-author">MIT</p>
<p>Advanced matrix methods with direct applications to machine learning. Covers singular value decomposition, principal component analysis, and optimization techniques.</p>
<a href="https://www.youtube.com/playlist?list=PLUl4u3cNGP63oMNUHXqIUcrkS2PivhN3k" target="_blank" rel="noopener noreferrer">View Playlist</a> |
<a href="https://ocw.mit.edu/courses/18-065-matrix-methods-in-data-analysis-signal-processing-and-machine-learning-spring-2018/" target="_blank" rel="noopener noreferrer">Course Page</a>
</div>
</div>
<h3 class="subsection-title">Calculus</h3>
<div class="resource-list">
<div class="resource-item" data-level="beginner">
<div class="resource-badge-level">Beginner</div>
<h4>Essence of Calculus</h4>
<p class="resource-author">3Blue1Brown</p>
<p>Visual intuition for calculus concepts. Essential for understanding gradients, derivatives, and the optimization algorithms used in training neural networks.</p>
<a href="https://www.youtube.com/playlist?list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr" target="_blank" rel="noopener noreferrer">View Playlist</a>
</div>
<div class="resource-item" data-level="intermediate">
<div class="resource-badge-level">Intermediate</div>
<h4>Matrix Calculus for Machine Learning and Beyond</h4>
<p class="resource-author">MIT, IAP 2023</p>
<p>Specialized course on matrix calculus with focus on machine learning applications. Covers gradients, Jacobians, and automatic differentiation.</p>
<a href="https://www.youtube.com/playlist?list=PLUl4u3cNGP62EaLLH92E_VCN4izBKK6OE" target="_blank" rel="noopener noreferrer">View Playlist</a> |
<a href="https://ocw.mit.edu/courses/18-s096-matrix-calculus-for-machine-learning-and-beyond-january-iap-2023/" target="_blank" rel="noopener noreferrer">Course Page</a>
</div>
</div>
<h3 class="subsection-title">Probability & Statistics</h3>
<div class="resource-list">
<div class="resource-item" data-level="beginner">
<div class="resource-badge-level">Beginner</div>
<h4>Probability for Computer Scientists (CS109)</h4>
<p class="resource-author">Stanford University</p>
<p>Essential probability concepts for computer science and machine learning. Covers distributions, random variables, and statistical inference.</p>
<a href="https://www.youtube.com/playlist?list=PLoROMvodv4rOpr_A7B9SriE_iZmkanvUg" target="_blank" rel="noopener noreferrer">View Playlist</a> |
<a href="https://web.stanford.edu/class/archive/cs/cs109/cs109.1254/" target="_blank" rel="noopener noreferrer">Course Page</a>
</div>
<div class="resource-item" data-level="beginner">
<div class="resource-badge-level">Beginner</div>
<h4>Statistics 110: Probability</h4>
<p class="resource-author">Harvard University</p>
<p>Comprehensive introduction to probability theory. In-depth coverage of probability concepts with clear explanations and examples.</p>
<a href="https://www.youtube.com/playlist?list=PL2SOU6wwxB0uwwH80KTQ6ht66KWxbzTIo" target="_blank" rel="noopener noreferrer">View Playlist</a> |
<a href="https://projects.iq.harvard.edu/stat110/home" target="_blank" rel="noopener noreferrer">Course Page</a>
</div>
</div>
</div>
</div>
</section>
<!-- Study Tips Section -->
<section class="section about">
<div class="container">
<h2 class="section-title">How to Prepare</h2>
<div class="goals-grid">
<div class="goal-card">
<h3>For Beginners</h3>
<p><strong>Priority:</strong> Start with Andrej Karpathy's 1-hour introduction, then watch the 3Blue1Brown neural networks series. These two resources will give you a solid conceptual foundation.</p>
<p><strong>Optional:</strong> Browse the IBM Technology playlist for specific topics that interest you.</p>
</div>
<div class="goal-card">
<h3>For Practitioners</h3>
<p><strong>Priority:</strong> Review "How I Use LLMs" and the RAG tutorial to see practical applications. Look at the Stanford CME 295 syllabus to identify areas where you want to deepen your knowledge.</p>
<p><strong>Optional:</strong> Explore the inference optimization course if you're interested in deployment efficiency.</p>
</div>
<div class="goal-card">
<h3>For Researchers</h3>
<p><strong>Priority:</strong> Review the advanced NLP course and inference algorithms course. Consider watching the GPT-2 reproduction video to understand implementation details.</p>
<p><strong>Optional:</strong> Dive into the CS 230 materials if you want to refresh your deep learning fundamentals.</p>
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<h3 style="color: var(--primary-color); margin-bottom: 1rem; font-size: 1.5rem;">Timeline Suggestion</h3>
<p><strong>6+ weeks before:</strong> Start with the foundational videos and courses that interest you most.</p>
<p><strong>2-4 weeks before:</strong> Focus on areas relevant to your goals (practitioner tools or research topics).</p>
<p><strong>1 week before:</strong> Review key concepts and make sure you have your development environment set up.</p>
<p style="margin-top: 1.5rem;"><em>Remember: These are suggestions to enhance your workshop experience, not requirements. Come with curiosity and a willingness to learn!</em></p>
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