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AI Fundamentals

Learn the fundamentals of AI. No programming experience required!

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4 Hours14 Videos49 Exercises15,886 Learners
3350 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?

    Play Chapter Now
    Do androids dream of electric sheep?
    50 xp
    General vs Narrow AI
    50 xp
    Why Python?
    50 xp
    The elephant in the room
    100 xp
    All models are wrong but some are useful
    50 xp
    Parameters & hyper-parameters
    100 xp
    Too much of a good thing
    100 xp
    Three flavors of Machine Learning
    50 xp
    Guess the flavor I
    50 xp
    Guess the flavor II
    50 xp
    Simple digit recognition
    100 xp
  2. 2

    Supervised Learning

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

    Play Chapter Now
    Supervised Learning Fundamentals
    50 xp
    Regression or Classification I
    50 xp
    When regression means classification
    100 xp
    Training and evaluating classification models
    50 xp
    SPAMtastic!
    50 xp
    Hold-out
    100 xp
    Training and evaluating regression models
    50 xp
    Tailor made
    50 xp
    Going non-linear
    100 xp
  3. 3

    Unsupervised Learning

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

    Play Chapter Now
    Dimensionality reduction
    50 xp
    Principal Component Analysis
    50 xp
    Visitors from outer space
    100 xp
    Clustering
    50 xp
    Lucky number K
    50 xp
    Elbow reading
    100 xp
    DBSCAN
    100 xp
    Anomaly detection
    50 xp
    How unsupervised really?
    50 xp
    The go-to algorithm
    50 xp
    The odd one out
    100 xp
    Elon's tweets
    100 xp
    Selecting the right model
    50 xp
    Fruits of knowledge
    50 xp
    Predicting customer churn
    100 xp
  4. 4

    Deep Learning & Beyond

    Learn about deep learning, create your first neural networks, and train a model to recognize digits.

    Play Chapter Now
    Deep Learning & Beyond
    50 xp
    The nucleus
    50 xp
    How to train your dragon
    50 xp
    Your first neural net
    100 xp
    Deep Learning
    50 xp
    Layers
    50 xp
    Guess the architecture
    50 xp
    Rolling in the deep
    100 xp
    Convolutional Neural Networks
    50 xp
    The Beauty of the Beast
    50 xp
    One-liner modeling
    100 xp
    One-line evaluation
    100 xp
    Deep Learning for Digit Recognition
    100 xp
    Congratulations!
    50 xp

In the following tracks

Data Skills for Business

Datasets

Customer ChurnMNIST

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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Decision Science Analytics, USAA