Comparing AI and Machine Learning MOOCs: UC Berkeley vs Stanford

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The discussion centers around a high school student considering two MOOCs: an AI course from UC Berkeley taught by Dan Klein and a Machine Learning course from Stanford led by Andrew Ng. The student expresses a preference for the Berkeley course but seeks input from others. Suggestions include researching the instructors' backgrounds, specialties, and teaching styles through videos to make an informed decision. One participant favors the Machine Learning course, noting its recent prominence in the news and suggesting that the AI course may only cover machine learning superficially. The emphasis is on conducting thorough research to choose the most suitable course.

Which course on AI?

  • Artificial Intelligence by Dan Klein from UC Berkeley

    Votes: 0 0.0%

  • Machine Learning by Andrew Ng from Stanford

    Votes: 1 100.0%
  • Total voters
    1
sarvesh0303
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I am a high school student and an avid learner through MOOCs. This spring, there are two MOOCs coming up which caught my interest- one on AI from UC Berkeley(Dan Klein) and the other on Machine Learning from Stanford(Andrew Ng). Though I am inclined towards the Berkeley course, I wanted to get opinions from other people on which one to take. So what do you think guys?
 
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It seems no one is responding to your survey. Perhaps you should check out the backgrounds of the teachers like what their specialities are and what they've published... You could also Google for videos of them to see which ones teaching style suits you more and do a resonant pros and cons evaluation to pick the best one.

Personally without doing any research I would choose the machine learning one as that has been the news more recently. The AI course will probably cover machine learning but in a more superficial way. However don't take my word do some due diligence and then decide.
 

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