Intro to Artificial Intelligence Free Course - Le Wagon

Overview

Artificial Intelligence is an innovative and versatile field that enables machines to mimic human intelligence.

It's applicable in numerous sectors like healthcare, finance, and entertainment, significantly impacting how we live and work.

Course Contents

  1. Machine Learning Essentials

Discover the fundamentals of Machine Learning, one of the most innovative and widely-used applications of Artificial Intelligence. Learn about what it really means, and optionally explore advanced topics such as K-Nearest Neighbors to build a robust foundation for your AI journey.

  1. Python & Scikit-learn 101

Understand the significance of Python and Scikit-learn in AI programming. Learn how to set up and practice with Python and Jupyter to effectively manage your Machine Learning workflows.

  1. Predictive Modeling

Dive into the world of predictive models in AI. Learn how to create predictions with Python, from salary forecasting to customer churn and even Apple stock predictions, enhancing the practicality and versatility of your AI applications.

  1. Real-World Applications

Get hands-on experience with AI through a series of practical exercises. Learn how to apply Machine Learning concepts in real-life scenarios and solve tangible problems, bolstered by supportive resources like cheat sheets and further learning suggestions.

Tools & frameworks

Notebooks

All notebooks are available in /lab repository.

What from here?

If you want to go further and do not know what course to take next, this great blog post from @lewagon might answer all your question, just as it did mines.

References

Dataset

Tools

  • setosa.io (blog)
  • ml-playground.com (model playground)

Virtual environment:

ML API:

Papers: