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Feature Engineering for BeginnersCodeSignal
Generative AI ProgramStanford University
Taught byCodeSignalStanford UniversityTier 1: world-leading universities and India's top institutesBest here
Institution score55/10097/100Best here
UniversityNoYes
PlatformedXYouTube
TypeCourseVideo playlist
PriceFree to auditCertificate $30Free videoBest here
CertificatePaid certificateBest hereNo certificate
RatingNo ratingsNo ratings
Learners or views33,181,431Best here
TimeNot stated24 videos, 2 hours
PaceSelf-pacedSelf-paced
LevelBeginnerNot stated
LanguageEnglishEnglish
SubtitlesNot statedNot stated
StartsAny timeAny time
TeachersNot statedNot stated
SyllabusNot listed24 videos
Skills only this one coversNoneNone
SubjectsData Analysis, Artificial Intelligence, Machine LearningArtificial Intelligence, Generative AI
Before you startBeginner: Data Cleaning and Preprocessing (Numpy, Pandas, Python, Scikit-learn) Beginner: Data Ingestion and Extraction (Numpy, Pandas, Python, Scikit-learn)Not stated
Advantages
  • University courses you can audit for free, with lectures, readings and practice quizzes.
  • A verified certificate from the university if you pay for it.
  • 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
Disadvantages
  • Graded assignments and the certificate need the paid track.
  • Audit access can expire a few weeks after the course ends.
  • Learning is free, but the certificate costs money.
  • Some parts (graded work, certificate) are paid.
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 score55/10093/100Best here
Syllabus side by side
Feature Engineering for Beginners
  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

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