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Introduction to GitHub ActionsDuke University
Generative AI ProgramStanford University
Taught byDuke UniversityTier 2: excellent universities and the companies that build the technologyStanford UniversityTier 1: world-leading universities and India's top institutesBest here
Institution score86/10097/100Best here
UniversityYesYes
PlatformCourseraYouTube
TypeCourseVideo playlist
PriceFree videoBest here
CertificatePaid certificateBest hereNo certificate
Rating3.223 ratingsNo ratings
Learners or viewsNot stated3,181,431
Time2 hoursBest here24 videos, 2 hours
PaceSelf-pacedSelf-paced
LevelNot statedNot stated
LanguageEnglishEnglish
SubtitlesNot statedNot stated
StartsAny timeAny time
TeachersAlfredo DezaNot stated
Syllabus1 parts24 videosBest here
Skills only this one coversNoneNone
SubjectsSoftware Engineering, DevOps, Artificial Intelligence, Machine Learning, Git and GitHubArtificial Intelligence, Generative AI
Before you startNot statedNot stated
Advantages
  • Structured courses with graded quizzes, assignments and deadlines you can reset.
  • A shareable certificate from the university or company when you pay.
  • Financial aid is often approved for students in India (apply 15 days before you need it).
  • From Duke University, a well-regarded name.
  • Self-paced: start any time.
  • A clear syllabus (1 parts) you can see before you start.
  • Hands-on: you build or practise, not just watch.
  • 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
Disadvantages
  • Paid after a 7-day free trial (Coursera Plus or per course).
  • Some courses can be audited for free, but graded work and certificates need payment.
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.
Technifyed score65/10093/100Best here
Syllabus side by side
Introduction to GitHub Actions
  1. Project Overview
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

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