AI Fundamentals

Learn the fundamentals of AI. No programming experience required!
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Clock4 HoursPlay14 VideosCode49 ExercisesGroup8,658 Learners
Database3350 XP

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Course Description

So what is all this AI fuss about? Machine Learning, Deep Learning, Predictive Analytics -- what is the reality behind the hype? How do machines actually learn and what are their limits? How can we use Machine Learning to recognize written digits, predict customer churn and find structure in Elon Musk's tweets? All this -- and much more -- is the topic of this course, which will introduce you to the world of AI in a gentle, but firm and very practical manner.

  1. 1

    Introduction to AI

    Free
    Understand the definition of AI ( “general” and “narrow”), the relationship between AI and Machine Learning, and will the robots take over the world - soon?
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  2. 2

    Supervised Learning

    Learn about supervised learning, work with labeled data and train regression models.
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  3. 3

    Unsupervised Learning

    Learn about unsupervised learning, divide data into clusters, detect anomalies and select the right model for the job.
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  4. 4

    Deep Learning & Beyond

    Learn about deep learning, create your first neural networks, and train a model to recognize digits.
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In the following tracks
Data Skills for Business
Collaborators
Hadrien LacroixHillary Green-Lerman
Nemanja Radojković Headshot

Nemanja Radojković

Senior Data Scientist @ Dataroots
Nemanja's areas of expertise include Machine Learning, Text Mining and Computer Vision. He is currently a Senior Data Scientist at Dataroots, where he helps businesses to harvest the power of their data. He has worked with industries as varied as manufacturing, life sciences & healthcare, and transportation services & infrastructure.
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Lloyds Banking Group

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Harvard Business School

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Decision Science Analytics, USAA

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