crème de la crème of AI courses
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This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI). Whether you're a beginner or an experienced learner, there's something here for everyone!
👀 looking for ideas
I am looking for a good free course on statistics, linear algebra, integrals and derivatives that could be a good mathematical training for people who want to start a career in ML. I look forward to hearing your ideas!
🧑🎓courses & resources
|Deep Learning||website||2023||free||Deep Learning Fundamentals -- Learning Deep Learning Using a Modern Open-Source Stack. by Sebastian Raschka|
|Large Language Models||YouTube playlist||2023||free||LLM Bootcamp - Spring 2023 by The Full Stack|
|Python||YouTube playlist||2023||free||CS50: Introduction to Programming with Python by Harvard University x freeCodeCamp.org|
|Stable Diffusion and Deep Learning||website||2023||free||Practical Deep Learning for Coders part 2: Deep Learning Foundations to Stable Diffusion by fast.ai|
|Deep Learning||YouTube playlist||2023||free||6.S191: Introduction to Deep Learning by Massachusetts Institute of Technology|
|Deep Learning||YouTube playlist||2023||free||Neural Networks: Zero to Hero by Andrej Karpathy|
|Large Language Models and Prompt Engineering||website||2023||free||Prompt Engineering Guide by DAIR.AI|
|Computer Vision||YouTube playlist||2023||free||Computer Vision in Practice by Piotr Skalski x Roboflow|
|Natural Language Processing||YouTube playlist||2023||free||CS685: Advanced Natural Language Processing by University of Massachusetts|
|MLOps||YouTube playlist||2022||free||Machine Learning Engineering for Production by Andrew Y. Ng|
|Multimodal Machine Learning||YouTube playlist||2022||free||11-777: Multimodal Machine Learning by Carnegie Mellon University|
|Deep Multi-Task and Meta Learning||YouTube playlist||2022||free||CS330 Deep Multi-Task and Meta Learning by Stanford University|
|Deep Learning||YouTube playlist||2022||free||Practical Deep Learning for Coders by fast.ai|
|Natural Language Processing||YouTube playlist||2021||free||CS224U: Natural Language Understanding by Stanford University|
|Transformers||YouTube playlist||2021||free||CS25: Transformers United by Stanford University|
|Deep Learning||YouTube playlist||2021||free||NYU-DLSP21: NYU Deep Learning Spring by New York University|
|Natural Language Processing and Transformers||website||2021||free||NLP Course by Hugging Face|
|Deep Learning||book||2021||free||Dive into Deep Learning by d2l.ai|
|Reinforcement Learning||YouTube playlist||2021||free||Reinforcement Learning Course by DeepMind x University College London|
|Natural Language Processing||YouTube playlist||2021||free||CS224N: Natural Language Processing with Deep Learning by Stanford University|
|Deep Learning||YouTube playlist||2020||free||Deep Learning Lecture Series by DeepMind x University College London|
|Linear Algebra||website||2019||free||Advanced Linear Algebra - Foundations to Frontiers by Margaret E. Myers & Robert A. van de Geijn|
|Artificial Intelligence||Youtube playlist||2019||free||Stanford CS221: Artificial Intelligence: Principles and Techniques by Stanford University|
|Computer Vision||Youtube playlist||2019||free||University of Michigan EECS 498.008 / 598.008: Deep Learning for Computer Vision by University of Michigan|
|Computer Vision||YouTube playlist||2018||free||CS231n: Deep Learning for Computer Vision by Stanford University|
We would love your help in making this repository even better! If you know of an amazing AI course that isn't listed here, or if you have any suggestions for improvement, feel free to open an issue or submit a pull request. If you feel up to the task, please take a peek at our contribution guide.
Together, let's make this the best AI learning hub on GitHub!