📺 The best Stanford, CMU, and MIT courses for AI (with YouTube playlists)
- With a multitude of AI courses available online, coming up with an study plan for AI can easily lead to decision fatigue.
- I often get asked about which courses have been useful to me to build a foundation in AI. Here’s my list of courses along with their respective YouTube playlists.
- Check out my watch list with all of the below pointers (and a much larger list of such resources and more):Â https://aman.ai/watch
📚 Stanford University
🔹 CS221 - Artificial Intelligence: Principles and Techniques by Percy Liang and Dorsa Sadigh: https://lnkd.in/grECwbD4
🔹 CS229 - Machine Learning by Andrew Ng: https://lnkd.in/gY8a2yZN
🔹 CS230 - Deep Learning by Andrew Ng: https://lnkd.in/gTk-gKPm
🔹 CS231n - Convolutional Neural Networks for Visual Recognition by Fei-Fei Li and Andrej Karpathy: https://lnkd.in/gGUMZH_G
🔹 CS224n - Natural Language Processing with Deep Learning by Christopher Manning: https://lnkd.in/giWDZGVX
🔹 CS234 - Reinforcement Learning by Emma Brunskill: https://lnkd.in/gwZKQ-28
🔹 CS330 - Deep Multi-task and Meta Learning by Chelsea Finn: https://lnkd.in/gvVr_Y4M
🔹 CS25 - Transformers United by Divyansh Garg, Steven Feng, and Rylan Schaeffer: https://lnkd.in/gEtKgHGC
📚 Carnegie Mellon University
🔹 CS/LTI 11-711: Advanced NLP by Graham Neubig: https://lnkd.in/gSt29ZVt
🔹 CS/LTI 11-747: Neural Networks for NLP by Graham Neubig: https://lnkd.in/gRRrY8uq
🔹 CS/LTI 11-737: Multilingual NLP by Graham Neubig: https://lnkd.in/g8QkaTfy
🔹 CS/LTI 11-777: Multimodal Machine Learning by Louis-Philippe Morency: https://lnkd.in/gKFJDbU4
🔹 CS/LTI 11-785: Introduction to Deep Learning by Bhiksha Raj and Rita Singh:
https://lnkd.in/gVp96GdB
🔹 CS/LTI Low Resource NLP Bootcamp 2020 by Graham Neubig: https://lnkd.in/grYqa3YZ
📚 Massachusetts Institute of Technology
🔹 6.S191 - Introduction to Deep Learning by Alexander Amini and Ava Amini: https://lnkd.in/gWMUpMQg
🔹 6.S094 - Deep Learning by Lex Fridman: https://lnkd.in/gcDgqbH6
🔹 6.S192 - Deep Learning for Art, Aesthetics, and Creativity by Ali Jahanian: https://lnkd.in/gEyRbEZx
📚 University College London (UCL)
🔹 COMP M050 Reinforcement Learning by David Silver: https://lnkd.in/gEpkWmqh
#artificialintelligence #machinelearning #ai #ml
- With a multitude of AI courses available online, coming up with an study plan for AI can easily lead to decision fatigue.
- I often get asked about which courses have been useful to me to build a foundation in AI. Here’s my list of courses along with their respective YouTube playlists.
- Check out my watch list with all of the below pointers (and a much larger list of such resources and more):Â https://aman.ai/watch
📚 Stanford University
🔹 CS221 - Artificial Intelligence: Principles and Techniques by Percy Liang and Dorsa Sadigh: https://lnkd.in/grECwbD4
🔹 CS229 - Machine Learning by Andrew Ng: https://lnkd.in/gY8a2yZN
🔹 CS230 - Deep Learning by Andrew Ng: https://lnkd.in/gTk-gKPm
🔹 CS231n - Convolutional Neural Networks for Visual Recognition by Fei-Fei Li and Andrej Karpathy: https://lnkd.in/gGUMZH_G
🔹 CS224n - Natural Language Processing with Deep Learning by Christopher Manning: https://lnkd.in/giWDZGVX
🔹 CS234 - Reinforcement Learning by Emma Brunskill: https://lnkd.in/gwZKQ-28
🔹 CS330 - Deep Multi-task and Meta Learning by Chelsea Finn: https://lnkd.in/gvVr_Y4M
🔹 CS25 - Transformers United by Divyansh Garg, Steven Feng, and Rylan Schaeffer: https://lnkd.in/gEtKgHGC
📚 Carnegie Mellon University
🔹 CS/LTI 11-711: Advanced NLP by Graham Neubig: https://lnkd.in/gSt29ZVt
🔹 CS/LTI 11-747: Neural Networks for NLP by Graham Neubig: https://lnkd.in/gRRrY8uq
🔹 CS/LTI 11-737: Multilingual NLP by Graham Neubig: https://lnkd.in/g8QkaTfy
🔹 CS/LTI 11-777: Multimodal Machine Learning by Louis-Philippe Morency: https://lnkd.in/gKFJDbU4
🔹 CS/LTI 11-785: Introduction to Deep Learning by Bhiksha Raj and Rita Singh:
https://lnkd.in/gVp96GdB
🔹 CS/LTI Low Resource NLP Bootcamp 2020 by Graham Neubig: https://lnkd.in/grYqa3YZ
📚 Massachusetts Institute of Technology
🔹 6.S191 - Introduction to Deep Learning by Alexander Amini and Ava Amini: https://lnkd.in/gWMUpMQg
🔹 6.S094 - Deep Learning by Lex Fridman: https://lnkd.in/gcDgqbH6
🔹 6.S192 - Deep Learning for Art, Aesthetics, and Creativity by Ali Jahanian: https://lnkd.in/gEyRbEZx
📚 University College London (UCL)
🔹 COMP M050 Reinforcement Learning by David Silver: https://lnkd.in/gEpkWmqh
#artificialintelligence #machinelearning #ai #ml
