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Audio CourseHugging Face
Generative AI ProgramStanford University
Large Language Models (LLMs)Stanford University
Taught byHugging FaceTier 2: excellent universities and the companies that build the technologyStanford UniversityTier 1: world-leading universities and India's top institutesBest hereStanford UniversityTier 1: world-leading universities and India's top institutesBest here
Institution score88/10097/100Best here97/100Best here
UniversityNoYesYes
PlatformHugging FaceYouTubeYouTube
TypeCourseVideo playlistVideo playlist
PriceFree courseFree videoFree video
CertificateNot statedNo certificateNo certificate
RatingNo ratingsNo ratingsNo ratings
Learners or viewsNot stated3,181,431Best here2,849,971
TimeNot stated24 videos, 2 hoursBest here26 videos, 42 hours
PaceSelf-pacedSelf-pacedSelf-paced
LevelNot statedNot statedNot stated
LanguageEnglishEnglishEnglish
SubtitlesNot statedNot statedNot stated
StartsAny timeAny timeAny time
TeachersNot statedNot statedNot stated
SyllabusNot listed24 videos26 videosBest here
Skills only this one coversNoneNoneNone
SubjectsArtificial Intelligence, Generative AI, Large Language Models, Natural Language ProcessingArtificial Intelligence, Generative AIArtificial Intelligence, Generative AI, Large Language Models
Before you startNot statedNot statedNot stated
Advantages
  • From Hugging Face, a well-regarded name.
  • Completely free.
  • Self-paced: start any time.
  • Free and complete: every lecture is in the playlist, in order.
  • Watch at 1.5x, skip what you know, rewatch what you don't.
  • The actual Stanford lectures (CS229, CS224N, CS231N…): the deepest free material on AI anywhere.
  • Taught by Stanford University, one of the strongest names in its field.
  • 3,181,431 views, so help and notes are easy to find.
  • Completely free.
  • Self-paced: start any time.
  • A clear syllabus (24 videos) you can see before you start.
Best here
  • Free and complete: every lecture is in the playlist, in order.
  • Watch at 1.5x, skip what you know, rewatch what you don't.
  • The actual Stanford lectures (CS229, CS224N, CS231N…): the deepest free material on AI anywhere.
  • Taught by Stanford University, one of the strongest names in its field.
  • 2,849,971 views, so help and notes are easy to find.
  • Completely free.
  • Self-paced: start any time.
  • A clear syllabus (26 videos) you can see before you start.
Best here
Disadvantages
  • None we know of
Best here
  • No certificate, deadlines or graded work.
  • Quality and depth vary: check that the playlist is finished before you start.
  • Graduate level: needs linear algebra, probability and programming first.
  • No certificate.
  • No graded assignments or feedback.
  • No certificate, deadlines or graded work.
  • Quality and depth vary: check that the playlist is finished before you start.
  • Graduate level: needs linear algebra, probability and programming first.
  • No certificate.
  • No graded assignments or feedback.
Technifyed score77/10093/100Best here93/100
Syllabus side by side
Audio Course
  1. Not listed
Generative AI Program
  1. Overview: Business Opportunities and Applications of Generative AI
  2. Course Overview - Business Opportunities and Applications of Generative AI
  3. These AI Skills Are the Most Valuable
  4. James Landay Explains Why AI Should Be Human-Centered
  5. Stanford Course - Technical Fundamentals of Generative AI
  6. Course Overview - Technical Fundamentals of Generative AI
  7. Stanford Webinar - Human-Centered AI: Designing Systems People Trust
  8. Top 5 Generative AI Trends: James Landay Reacts and Responds
  9. Generative AI: Looking Beyond the Hype with James Landay
  10. Generative AI at a Glance: An Overview from James Landay
  11. Move Forward Faster with Flexible Evals - Stanford Professor Chris Potts #generativeai #evals #ai
  12. Successful Startups Share This Trait - Michelle Pokrass, Post-Training Research Lead at OpenAI
  13. The Importance of Few-Shot Examples - Stanford Professor Chris Potts #generativeai #ai
  14. The Capabilities Overhang - Michelle Pokrass, Post-Training Research Lead at OpenAI #generativeai
  15. Where Might AI Be Underused? - Stanford Professor Chris Potts #generativeai #ai
  16. The State of AI and Trust Among Business Leaders - Aditya Challapally, ML Engineer at Microsoft #ai
  17. Who Decides How Models Behave? - Aditya Challapally, ML Engineer at Microsoft #generativeai
  18. Stanford Webinar - Making GenAI Useful: Lessons from Research and Deployment
  19. Generative AI Program: Technology, Business & Society
  20. Course Overview - Business Opportunities and Applications of Generative AI
  21. Course Overview - Human-Centered Generative AI
  22. Course Overview - Technical Fundamentals of Generative AI
  23. Business Opportunities and Applications of Generative AI
  24. Course Overview - Human-Centered Generative AI
Large Language Models (LLMs)
  1. Stanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 8 - Trending Topics
  2. Stanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 7 - Evaluation
  3. Stanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 6 - Model Training
  4. Stanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 5 - Architectures
  5. Stanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 4 - Latent Space & Guidance
  6. Stanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 3 - Flow matching
  7. Stanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 2 - Score matching
  8. Stanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 1 - Diffusion
  9. Stanford CME295 Transformers & LLMs | Autumn 2025 | Lecture 9 - Recap & Current Trends
  10. Stanford CME295 Transformers & LLMs | Autumn 2025 | Lecture 8 - LLM Evaluation
  11. Stanford CME295 Transformers & LLMs | Autumn 2025 | Lecture 7 - Agentic LLMs
  12. Stanford CME295 Transformers & LLMs | Autumn 2025 | Lecture 6 - LLM Reasoning
  13. Stanford CME295 Transformers & LLMs | Autumn 2025 | Lecture 5 - LLM tuning
  14. Stanford CME295 Transformers & LLMs | Autumn 2025 | Lecture 4 - LLM Training
  15. Stanford CME295 Transformers & LLMs | Autumn 2025 | Lecture 2 - Transformer-Based Models & Tricks
  16. Stanford CME295 Transformers & LLMs | Autumn 2025 | Lecture 1 - Transformer
  17. Stanford CME295 Transformers & LLMs | Autumn 2025 | Lecture 3 - Tranformers & Large Language Models
  18. Stanford CS25: V5 I On the Biology of a Large Language Model, Josh Batson of Anthropic
  19. Stanford CS25: V5 I Large Language Model Reasoning, Denny Zhou of Google Deepmind
  20. Stanford CS336 Language Modeling from Scratch | Spring 2025 | Lecture 1: Overview and Tokenization
  21. Stanford CS224N: NLP w/ DL | Spring 2024 | Lecture 12 - Efficient Training, Shikhar Murty
  22. Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 11 - Benchmarking by Yann Dubois
  23. Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 10 - Post-training by Archit Sharma
  24. Stanford CS224N: NLP w/ DL | Spring 2024 | Lecture 7 - Attention, Final Projects and LLM Intro
  25. Stanford Webinar - Large Language Models Get the Hype, but Compound Systems Are the Future of AI
  26. Stanford CS229 I Machine Learning I Building Large Language Models (LLMs)

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