斯坦福正式开课了！ 课号CS146S —— 一门正经3学分的AI编程课， 免费公开自学！ 课程名字叫《The Modern Software Developer》，核心观点狠准： 软件开发已经不是从0手写代码的时代了， 而是规划 → AI生成 → 修改迭代的新循环，能把生产力直接拉到10倍。 10周内容全是实战干货： Week 1-2：LLM原理、Prompt工程、Agent、Tool Use Week 3-4：AI IDE上下文、PRD驱动、Agent协作 Week 5：AI增强终端自动化 Week 6：AI代码安全（Prompt注入、漏洞检测） Week 7：AI Code Review 自动文档 Week 8：一个Prompt搞定完整应用 Week 9-10：部署监控 未来十年软件开发趋势 讲师阵容炸裂：Claude Code作者、Devin核心研究员、Warp CEO、Semgrep CEO、Vercel AI负责人、a16z合伙人…… 有CS111基础就能跟上， 非斯坦福学生也能白嫖全套课件 作业（GitHub开源） 想成为下一代AI时代程序员的，这门课必须冲！ themodernsoftware.dev

斯坦福开了一门课，免费教你怎么用AI写代码——不是选修水课，是正经3学分，课号CS146S 「The Modern Software Developer」，核心论点：软件开发已经从0到1写代码，进化成"规划 → AI生成 → 修改 → 循环"的迭代流程。课程目标是教下一代工程师怎么用AI工具把生产力拉到10倍 10周课程，每周的内容拆开看都很实在： → Week 1-2：LLM原理、Prompt工程、Agent架构、Tool Use、MCP协议 → Week 3-4：AI IDE的上下文管理、PRD驱动开发、Agent自治层级和人机协作模式 → Week 5：AI增强的终端和命令行自动化 → Week 6：AI代码的安全问题——漏洞检测、Prompt注入攻击、SAST/DAST → Week 7：AI辅助Code Review和文档生成 → Week 8：一个Prompt搞定端到端应用构建 → Week 9：部署后的监控、可观测性和自动化事件响应 → Week 10：未来十年软件开发会变成什么样 嘉宾阵容是真的强：Claude Code创作者Boris Cherney、Cognition（Devin）研究负责人Silas Alberti、Warp CEO Zach Lloyd、Semgrep CEO Isaac Evans、Vercel AI研究负责人Gaspar Garcia、a16z合伙人Martin Casado 前置要求CS111编程基础，推荐有CS221/229（AI/ML）背景。作业全在GitHub上开源，非斯坦福学生也能跟着自学 课件、Slides、阅读材料全部公开，相当于一套免费的AI编程系统课 🔗 themodernsoftware.dev

今年はcs111回出場の12回優勝🥇でした。 みんな関わってくれてありがとうございます🙇 来年もたくさん遊びたいです! 2026年もよろしくお願いします！！

I decided to take CS111 a second time, as I didn't feel particularly confident in my coding skills after try one. As such, I may or may have gone into the first lab with an inflated perception of the difficulty of the assignment, and written a check for every madlib input rather than just the first one, which was all the assignment was asking for. I knew we weren't supposed to know try/except commands until later in the semester...

・N172、NN→NNN207 ・横119、横前116 ・CS111、3.68秒 ・前→NNN209これが使い勝手良さそう ・サブは相変わらず慣性なし、打ち切りリロード5秒 総じて格闘が弱体化してる気がします 急いでやってきたから違うよ！ってところがあればどんどん教えてくださいm(._.)m

บน ผ่านcs111 ชั้นแจก100นึง รอเกรดออกก่อน เม้นไว้เลอ!

If you just took these classes, you'd get almost all of the basics relevant for industry. 3 other classes that are worth a mention: 1. Algorithms (CS180) - taught me how to do Leetcode hards 2. Operating systems (CS111) - taught me how computers work

Stanford courses in Computer Science with Artificial Intelligence: CS103 - Mathematical Foundations of Computing CS109 - Introduction to Probability for Computer Scientists MATH19 - Calculus MATH20 - Calculus MATH21 - Calculus MATH51 - Linear Algebra, Multivariable Calculus, and Modern Applications MATH52 - Integral Calculus of Several Variables MATH53 - Differential Equations with Linear Algebra, Fourier Methods, and Modern Applications MATH104 - Applied Matrix Theory MATH107 - Graph Theory MATH108 - Introduction to Combinatorics and Its Applications MATH109 - Groups and Symmetry MATH110 - Number Theory for Cryptography MATH113 - Linear Algebra and Matrix Theory CS157 - Computational Logic CS205L - Continuous Mathematical Methods with an Emphasis on Machine Learning CME100 - Vector Calculus for Engineers CME102 - Ordinary Differential Equations for Engineers CME104 - Linear Algebra and Partial Differential Equations for Engineers ENGR108 - Introduction to Matrix Methods PHIL151 - Metalogic PHYSICS41 - Mechanics OR PHYSICS21 - Mechanics and Fluids OR PHYSICS61 - Mechanics and Special Relativity PHYSICS43 - Electricity and Magnetism PHYSICS23 - Electricity, Magnetism, and Optics PHYSICS81 - Electricity and Magnetism Using Special Relativity and Vector Calculus CS106B - Programming Abstractions ENGR40M - An Intro to Making: What is EE ENGR76 - Information Science and Engineering CS107 - Computer Organization and Systems CS107E - Computer Systems from the Ground Up CS111 - Operating Systems Principles CS161 - Design and Analysis of Algorithms CS108 - Object-Oriented Systems Design CS112 - Operating systems kernel implementation project CS123 - A Hands-On Introduction to Building AI-Enabled Robots CS124 - From Languages to Information CS131 - Computer Vision: Foundations and Applications CS140E - Operating systems design and implementation CS142 - Web Applications CS143 - Compilers CS144 - Introduction to Computer Networking CS145 - Data Management and Data Systems CS147 - Introduction to Human-Computer Interaction Design CS147L - Cross-platform Mobile App Development CS148 - Introduction to Computer Graphics and Imaging CS149 - Parallel Computing CS151 - Logic Programming CS154 - Introduction to the Theory of Computation CS155 - Computer and Network Security CS163 - The Practice of Theory Research CS166 - Data Structures CS168 - The Modern Algorithmic Toolbox CS173A - Foundations of Computational Human Genomics CS177 - Human Centered Product Management CS190 - Software Design Studio CS195 - Supervised Undergraduate Research CS197 - Computer Science Research CS197C - Computer Science Research: CURIS Internship Onramp CS206 - Exploring Computational Journalism CS210A - Software Project Experience with Corporate Partners CS217 - Hardware Accelerators for Machine Learning CS221 - Artificial Intelligence: Principles and Techniques CS223A - Introduction to Robotics CS224N - Natural Language Processing with Deep Learning CS224S - Spoken Language Processing CS224U - Natural Language Understanding CS224V - Conversational Virtual Assistants with Deep Learning CS224W - Machine Learning with Graphs CS225A - Experimental Robotics CS227B - General Game Playing CS229 - Machine Learning CS229M - Machine Learning Theory CS230 - Deep Learning CS231A - Computer Vision: From 3D Perception to 3D Reconstruction and Beyond CS231N - Deep Learning for Computer Vision CS232 - Digital Image Processing CS233 - Geometric and Topological Data Analysis CS234 - Reinforcement Learning CS235 - Computational Methods for Biomedical Image Analysis and Interpretation CS237A - Principles of Robot Autonomy I CS237B - Principles of Robot Autonomy II CS238 - Decision Making under Uncertainty CS240 - Advanced Topics in Operating Systems CS240LX - Advanced Systems Laboratory, Accelerated CS242 - Programming Languages CS243 - Program Analysis and Optimizations CS244 - Advanced Topics in Networking CS244B - Distributed Systems CS245 - Principles of Data-Intensive Systems CS246 - Mining Massive Data Sets CS247 - Human-Computer Interaction Design Studio CS247A - Design for Artificial Intelligence CS247B - Design for Behavior Change CS247G - Design for Play CS247I - Design for Understanding CS247L - Human Computer Interaction Technology Laboratory CS247S - Service Design CS248A - Computer Graphics: Rendering, Geometry, and Image Manipulation CS248B - Fundamentals of Computer Graphics: Animation and Simulation CS249I - The Modern Internet CS250 - Algebraic Error Correcting Codes CS251 - Cryptocurrencies and blockchain technologies CS252 - Analysis of Boolean Functions CS253 - Web Security CS254 - Computational Complexity CS254B - Computational Complexity II CS255 - Introduction to Cryptography CS256 - Algorithmic Fairness CS257 - Introduction to Automated Reasoning CS259Q - Quantum Computing CS261 - Optimization and Algorithmic Paradigms CS263 - Counting and Sampling CS265 - Randomized Algorithms and Probabilistic Analysis CS269I - Incentives in Computer Science CS269O - Introduction to Optimization Theory CS269Q - Elements of Quantum Computer Programming CS270 - Modeling Biomedical Systems CS271 - Artificial Intelligence in Healthcare CS272 - Introduction to Biomedical Data Science Research Methodology CS273B - Deep Learning in Genomics and Biomedicine CS273C - Cloud Computing for Biology and Healthcare CS274 - Representations and Algorithms for Computational Molecular Biology CS275 - Translational Bioinformatics CS276 - Information Retrieval and Web Search CS278 - Social Computing CS279 - Computational Biology: Structure and Organization of Biomolecules and Cells CS281 - Ethics of Artificial Intelligence CS330 - Deep Multi-task and Meta Learning CS333 - Algorithms for Interactive Robotics CS336 - Robot Perception and Decision-Making: Optimal and Learning-based Approaches CS342 - Building for Digital Health CS348A - Computer Graphics: Geometric Modeling & Processing CS348B - Computer Graphics: Image Synthesis Techniques CS348C - Computer Graphics: Animation and Simulation CS348E - Character Animation: Modeling, Simulation, and Control of Human Motion CS348I - Computer Graphics in the Era of AI CS348K - Visual Computing Systems CS348N - Neural Models for 3D Geometry CS351 - Open Problems in Coding Theory CS368 - Algorithmic Techniques for Big Data CS398 - Computational Education CS448 - Topics in Computer Graphics CME108 - Introduction to Scientific Computing EE180 - Digital Systems Architecture EE282 - Computer Systems Architecture EE267 - Virtual Reality EE374 - Blockchain Foundations MS&E234 - Data Privacy and Ethics CS224R - Deep Reinforcement Learning CS228 - Probabilistic Graphical Models: Principles and Techniques CS229T - Machine Learning Theory: A Modern Perspective CS236 - Deep Generative Models STATS315A - Modern Applied Statistics: Learning STATS315B - Modern Applied Statistics: Learning II CS371 - Computational Biology in Four Dimensions CS327A - Advanced Robotic Manipulation CS329 - Topics in Artificial Intelligence ENGR205 - Introduction to Control Design Techniques MS&E251 - Introduction to Stochastic Control with Applications MS&E351 - Dynamic Programming and Stochastic Control CS325B - Data for Sustainable Development CS326 - Topics in Advanced Robotic Manipulation CS329D - Machine Learning Under Distributional Shifts CS338 - Physical Human Robot Interaction CS428 - Computation and Cognition: The Probabilistic Approach EE263 - Introduction to Linear Dynamical Systems EE278 - Probability and Statistical Inference EE364A - Convex Optimization I EE364B - Convex Optimization II MS&E252 - Foundations of Decision Analysis MS&E352 - Decision Analysis II: Professional Decision Analysis MS&E355 - Influence Diagrams and Probabilistics Networks PHIL152 - Computability and Logic PSYCH204A - Human Neuroimaging Methods PSYCH204B - Computational Neuroimaging: Data Analyses and Experimental Designs PSYCH209 - Neural Network Models of Cognition STATS200 - Introduction to Statistical Inference STATS202 - Data Mining and Analysis STATS203 - Introduction to Regression Models and Analysis of Variance STATS205 - Introduction to Nonparametric Statistics STATS271 - Applied Bayesian Statistics CME106 - Introduction to Probability and Statistics for Engineers EE178 - Probabilistic Systems Analysis MS&E220 - Probabilistic Analysis STATS116 - Theory of Probability CS140 - Operating Systems and Systems Programming CS210B - Software Project Experience with Corporate Partners CS212 - Operating Systems and Systems Programming CS239 - Advanced Topics in Sequential Decision Making CS341 - Project in Mining Massive Data Sets CS229B - Machine Learning for Sequence Modeling CS329X - Human Centered NLP CS332 - Advanced Survey of Reinforcement Learning CS373 - Statistical and Machine Learning Methods for Genomics CS224C - NLP for Computational Social Science CS229S - Systems for Machine Learning CS231C - Computer Vision and Image Analysis of Art CS293 - Empowering Educators via Language Technology CS322 - Triangulating Intelligence: Melding Neuroscience, Psychology, and AI CS324 - Advances in Foundation Models CS324H - History of Natural Language Processing CS328 - Foundations of Causal Machine Learning CS329E - Machine Learning on Embedded Systems CS329H - Machine Learning from Human Preferences CS329M - Machine Programming CS329P - Practical Machine Learning CS329R - Race and Natural Language Processing CS329S - Machine Learning Systems Design CS329T - Trustworthy Machine Learning CS225 - Machine Learning for Discrete Optimization CS336 - Language Modeling from Scratch CS353 - Seminar on Logic & Formal Philosophy CS361 - Engineering Design Optimization CS375 - Large-Scale Neural Network Modeling for Neuroscience CS377 - Topics in Human-Computer Interaction CS377E - Designing Solutions to Global Grand Challenges CS377G - Designing Serious Games CS377I - Designing for Complexity CS377J - Designing Systems for Collaboration, Cooperation, and Collective Action CS377N - Introduction to the Design of Smart Products CS377Q - Designing for Accessibility CS377T - Topics in Human-Computer Interaction: Teaching Studio Classes CS377U - Understanding Users CS379C - Computational Models of the Neocortex CS399 - Independent Project CS428A - Probabilistic models of cognition: Reasoning and Learning CS428B - Probabilistic Models of Cognition: Language CS432 - Computer Vision for Education and Social Science Research EE276 - Information Theory EE377 - Information Theory and Statistics ENGR209A - Analysis and Control of Nonlinear Systems MS&E226 - Fundamentals of Data Science: Prediction, Inference, Causality CS373 - Statistical and Machine Learning Methods for Genomics

Lets congratulate our very own Jewel of #CS111 Nehemiah Lawley on an outstanding job at the Scripps National Spelling Bee! 🐝 Shine bright young man ✨ . #JewelofLongIslandCity #communityschools #nycdoe #district30 #longislandcity #scrippsspellingbee @nycdistrict30 @NYCSchools

ティーチャーcs111人は嬉しい。どうにかして全員出してあげたい。 CS出るの無理でも、サブイベント始まるまでの間に楽しいスペース用意するんで、来るだけ来るのアリって思わせるんでね 要は来てね

New for the weekend: CS111 - The Herdwick, with Will Rawling. History, present and future of the iconic lakeland sheep breed, alongside dialect chat (Grike, Sampson's Bratfull) plus Will's wonderful memories of the carthorse days. countrystride.co.uk/single-p…

CS111

🔷CS111🔷CS323🔷المشاريع🔷 أشكر الله أن من علي بفصل دراسي مميز تعرفت فيه على كوكبة من الشخصيات المتميزة ع أصعدة مختلفة مابين تميز دراسي وثقافي وأدبي وفني ورياضي و "برمجي" 😎 بارك الله في جهودكم وكلل مساعيكم بالنجاح أصدق التمنيات بقضاء إجازة سعيدة ولذيذة للجميع 🤍

CS111 🌟Champs🌟 of the week : Hajar @alwaystosucceed 🥇 Bushra @bellociano🥈 Esra @e13s0 🥉 Jumana @Jeem__J 🥉

CS111 🌟Champs🌟 of the week : Bushra @bellociano🥇 Hajar @alwaystosucceed🥈 Esar @e13s0 🥉

CS111 🌟Champs🌟 of the week : Hajar @alwaystosucceed🥇 Jumana🥈 Bushra @bellociano🥉

CS111 🌟Champs🌟 of the week : @alwaystosucceed🥇 @e13s0🥈 @res_pect83🥉

CS111 🌟Champs🌟 of the week : @BelloCiano🥇 @e13s0🥈 LAYAN🥉

CS111 🌟Champs🌟 of the week : @alwaystosucceed 🥇 @BelloCiano 🥈 @e13s0 🥉