Yale本科没有，研究生课程有一门： CPSC581b: Introduction to Machine Learning。有人会说，Yale的CPSC470（现在是CPSC370）AI 有ML的内容。不错，CMU也有Yale370一样的课，如07-180，15-281等等，但他们不能取代 Intro to ML.
而 CMU有5门：
10301 Introduction to Machine Learning 10315 Introduction to Machine Learning 10601 Introduction to Machine Learning 10701 Introduction to Machine Learning 10715 Introduction to Machine Learning
这里不看 计算机系的 15288 ML, 15442 ML System,
语言处理系的 11344 ML
人机交互系的 05434 ML，
Information System系的 95828，
电子工程系的
18461 Introduction to Machine Learning， 18661 Introduction to Machine Learning
生物工程系的：
42656 Introduction to Machine Learning
设计院的：
49781 Introduction to Machine Learning
等等等等，好像每个系都有机器学习的课，比如 introduction to Machine Learning in Chemical engineering, in Production, in Bioinformatics, etc
这些课都是 counter-requisite, 只能选一门。但难易程度差别很大。现在仅仅看这五门课： 10301 Introduction to Machine Learning 10315 Introduction to Machine Learning 10601 Introduction to Machine Learning 10701 Introduction to Machine Learning 10715 Introduction to Machine Learning
这五门课相同的是都用 Pytorch和Tensorflow 做 projects，其他 AI 和 ML入门课有较大不同
Algorithms and Complexity Computational Biology Computer Graphics Computer Systems Human-Computer Interaction Language Technologies Machine Learning Principles of Programming Languages Robotics Security and Privacy Software Engineering
Here is a list of 10 colleges from which AI startup founders have graduated:
Stanford University University of California, Berkeley Harvard University University of Southern California University of Illinois Urbana-Champaign Columbia University Princeton University University of California, Los Angeles University of Wisconsin-Madison University of Pennsylvania Wharton
These colleges have produced a significant number of AI startup founders, contributing to the innovation and success of the AI industry.
Here's a list of 10 colleges from which many AI startup founders have graduated:
pen_spark Stanford University - Stanford is consistently ranked among the top universities for computer science and artificial intelligence. Stanford alumni have founded some of the most successful AI startups in the world, including Google, Tesla, and Nvidia. Opens in a new windowwww.shiksha.com Stanford University Massachusetts Institute of Technology (MIT) - MIT is another powerhouse in computer science and AI research. MIT alumni have founded many notable AI startups, including Dropbox, iRobot, and DeepMind. Opens in a new windownews.mit.edu Massachusetts Institute of Technology (MIT) ON Massachusetts Institute of Technology (.edu) mit.edu Carnegie Mellon University (CMU) - CMU's School of Computer Science is world-renowned, and the university is home to a number of top AI research labs. CMU alumni have founded influential AI startups such as Uber, Duolingo, and Plaid. Opens in a new windowwww.cmu.edu Carnegie Mellon University (CMU) University of California, Berkeley (UC Berkeley) - UC Berkeley is another top public university with a strong computer science and AI program. UC Berkeley alumni have founded many successful AI startups, including OpenAI, Pinterest, and AngelList. Opens in a new windowwww.estudarfora.org.br University of California, Berkeley (UC Berkeley) University of Toronto - The University of Toronto is a leading research institution with a strong focus on artificial intelligence. The university's AI lab, the Vector Institute, has been at the forefront of deep learning research. Toronto alumni have founded some notable AI startups such as Thalmic Labs (creators of the MYO armband) and Vector Institute. Opens in a new windowutoronto.ca University of Toronto University of Washington (UW) - The University of Washington has a strong computer science program and is home to a number of AI research labs. UW alumni have founded influential AI startups such as Zillow, OfferUp, and Remitly. Opens in a new windowartsci.washington.edu University of Washington (UW) Imperial College London - Imperial College London is a top university in the United Kingdom with a world-class computer science program. Imperial College London alumni have founded notable AI startups such as DeepMind (acquired by Google) and Magic Leap. Opens in a new windowwww.imperial.ac.uk Imperial College London École Polytechnique Fédérale de Lausanne (EPFL) - EPFL is a leading research university in Switzerland with a strong focus on computer science and artificial intelligence. EPFL alumni have founded successful AI startups such as GetYourGuide and Dacama. Opens in a new windowfr.wikipedia.org École Polytechnique Fédérale de Lausanne (EPFL) National University of Singapore (NUS) - The National University of Singapore is a leading university in Asia with a strong computer science program. NUS alumni have founded many successful AI startups in the region, including Grab and Garena. Opens in a new windowwww.master-maestrias.com National University of Singapore (NUS) Peking University - Peking University is a top university in China with a strong computer science program. Peking University alumni have founded many successful AI startups in China, including Megvii and SenseTime. ChatGPT：
Here is a list of 10 colleges from which AI startup founders have graduated:
Stanford University Massachusetts Institute of Technology (MIT) University of California, Berkeley Carnegie Mellon University Harvard University University of Cambridge University of Oxford California Institute of Technology (Caltech) University of Illinois at Urbana-Champaign University of Toronto
上一贴，引发不少争议 甚至误解。我的初衷是不同意很多人这个观点：“每个大学CS教的都一样，所以上哪个都一样”。
从上一贴看出，同样CS本科毕业，学的东西差别巨大。你可以争论学的越多就越蠢，但学的内容不一样是事实。
我查了一下，CMU提供的有关ML的课程非常多，而且是不同系科提供，有计算机系的十几门课，人工智能系的十几门，机器学习系的二十几门，语言处理系的十几门，机器人系的十几门，还有其他学院比如 统计和人工智能系的。所以CMU贵在选择。
上次我给大家一个误解是，很多人以为CMU难读，造成困惑，使得有人没有信心去CMU读书。我特此说一下，这是误解。我从来没有说过，也不相信就读CMU的平均智力能力会比Yale的高，而几乎所有读CMU的还是Yale的，都顺利毕业了。当然藤校打分比较宽松，而CMU是另一种方法，那就是同一门课，开设难度不同的课。
比如看这门课：Introduction to Machine Learning
Yale本科没有，研究生课程有一门： CPSC581b: Introduction to Machine Learning。有人会说，Yale的CPSC470（现在是CPSC370）AI 有ML的内容。不错，CMU也有Yale370一样的课，如07-180，15-281等等，但他们不能取代 Intro to ML.
而 CMU有5门：
10301 Introduction to Machine Learning
10315 Introduction to Machine Learning
10601 Introduction to Machine Learning
10701 Introduction to Machine Learning
10715 Introduction to Machine Learning
这里不看 计算机系的 15288 ML, 15442 ML System,
语言处理系的 11344 ML
人机交互系的 05434 ML，
Information System系的 95828，
电子工程系的
18461 Introduction to Machine Learning，
18661 Introduction to Machine Learning
生物工程系的：
42656 Introduction to Machine Learning
设计院的：
49781 Introduction to Machine Learning
等等等等，好像每个系都有机器学习的课，比如 introduction to Machine Learning in Chemical engineering, in Production, in Bioinformatics, etc
这些课都是 counter-requisite, 只能选一门。但难易程度差别很大。现在仅仅看这五门课：
10301 Introduction to Machine Learning
10315 Introduction to Machine Learning
10601 Introduction to Machine Learning
10701 Introduction to Machine Learning
10715 Introduction to Machine Learning
这五门课相同的是都用 Pytorch和Tensorflow 做 projects，其他 AI 和 ML入门课有较大不同
其中 301， 315是本科课程，601是硕士，701，715是博士，在CMU，存在对硕士的歧视，具体在这里就是公认 601是最容易的课程。
其他难易程度依次是：301，315，701，715.
SCS学生的标配是 315，但是很多本科学生选择更有挑战性的 701，比如我上次贴给大家的学生，还有我儿子。更有本科生直接挑战 715.
当然 如果你觉得 315吃力，可以选 301. 所有 CS minor的都是 301，轻轻松松拿 A，也不影响做 QR QD
不仅仅这门课，很多CMU课程都有相同内容但难度不同的课程，互为 counter-requisite, 不能选两门，如果选了，学分只能算一门。
由此可见，CMU并不是代表难，而是提供一个多样性的选择，在yale，想修 Introduction to Machine Learning，只能选 CPSC581b，而在CMU，你可以选比耶鲁CPSC581b更难的，也可以选比CPSC581b更容易的。也包括和CPSC581b差不多的。
如果把Yale和CMU比做餐馆，CMU 菜单上的菜更多，而且同一个菜，还提供不同烹饪方法出的不同口味的。当然如果你说，你肚子就那么大，吃不了几个菜，就喜欢Yale的那个菜，也无可厚非。
有人害怕进了CMU跟不上进度，不存在这样的问题。生源不如Yale的CMU学生，也都毕业了。工资可能还更高，多样性，选择性 也是择校的一个可以考虑的因素
卡梅特点除了严格，另一个是细分，专业方向碎片化，可能因为硕士收人多，程度又不同，细分方便管理。
藤校高阶课有可能同一个课两个课号，让本科生和研究生分别打最后成绩，虽然在一起上课。
Algorithms and Complexity Computational Biology Computer Graphics Computer Systems Human-Computer Interaction Language Technologies Machine Learning Principles of Programming Languages Robotics Security and Privacy Software Engineering
其他的也还可以吧，没有一个一个研究过。
年轻人多，灌水文章多
https://www.usnews.com/education/best-global-universities/computer-science
https://coursetable.com/catalog，拿掉Fall2024,搜索machine learning 看看. Y 提供很多相关的课给各个学科。真的不要用你的熟悉的东西来一概而论误导别人了！
我家两娃上高中的时候我就灌输了这个观点。无惧才能尝试才能有所得。
猜耶鲁哥在学校里没人会觉得他不行，可能他的特点本来也不在技术方面而在其他方面，同学也不相互比较。但他如果去了划一的学校，肯定不会在另个油管说认为自己四年大学是人生最好时光。
申请M，S，甚至penn都行，为什么要申请Y，一个刚开始重视STEM，刚开始招人的学校？再过十年看看发展在考虑还合理。
Here is a list of 10 colleges from which AI startup founders have graduated:
Stanford University University of California, Berkeley Harvard University University of Southern California University of Illinois Urbana-Champaign Columbia University Princeton University University of California, Los Angeles University of Wisconsin-Madison University of Pennsylvania WhartonThese colleges have produced a significant number of AI startup founders, contributing to the innovation and success of the AI industry.
AI 行华人娃最多了，从硬件到软件，真的是爆发。
养，优越的校园生活体验，毕竟选一个大学是要多方面考虑的。
全是男娃MOP，女娃MOP/AMO/JMO。
认识两个男娃AMO的，一个去了Y，一个去了CMU。
CMU太小众了，曲高和寡 仍然还是无数小中CS娃的梦校。
但H一年招1700+，CMU SCS一年招200，H里面即使一半是文科娃，另一半理科生里面的MOP/AMO也比CMU的SCS里面的多多了。
他们之间有Network， 数据最精确。 其他的都是自己估计。
Gemini：
Here's a list of 10 colleges from which many AI startup founders have graduated:
pen_spark Stanford University - Stanford is consistently ranked among the top universities for computer science and artificial intelligence. Stanford alumni have founded some of the most successful AI startups in the world, including Google, Tesla, and Nvidia.Here is a list of 10 colleges from which AI startup founders have graduated:
Stanford University
Massachusetts Institute of Technology (MIT)
University of California, Berkeley
Carnegie Mellon University
Harvard University
University of Cambridge
University of Oxford
California Institute of Technology (Caltech)
University of Illinois at Urbana-Champaign
University of Toronto
这么说有啥毛病？
大赞兄贵！能再请你比较一下CMU和康的CS吗？尤其是课程和任何你觉得值得的地方，多谢！
大家都是只见树木不见森林，争论一些不重要的细节。曾经看到一个统计，85%IT的女性从业人员在15之内都转行改做管理，法律，Corporate finance等等，还在一线做码农的凤毛麟角。因此如果你家的是学CS的女儿，进Y肯定比进CMU好得多，因为反正十年之后都要转行。曾经认识一个这样的华裔女孩，她说据她所见，一般十年之后想转了，但是因为有家庭和工作的拖累，脱不了身，开始时往往只能边工作边学习，相当辛苦，一般要5年左右才能完成这个转移过程。