Course curriculum

    1. Artificial Intelligence, Machine Learning and Predictions

    2. Ingredients of an ML pipeline

    3. Meet your Instructor

    1. Data: from structured to unstructured

    1. Introduction

    2. Supervised Learning

    3. Supervised Learning: Regression

    4. Supervised Learning: Classification

    5. Ensembles: The Wisdom of the Crowd

    6. Deep Learning

    7. Unsupervised Learning

    8. Wrap-up

    1. Model Evaluation

    2. Common Problems

    1. Next Steps

About this course

  • Free
  • 15 lessons
  • 1 hour of video content

Main Learning Outcomes

By enrolling in this course, we will show you in one hour:

  • All the concepts your Data Scientist colleague use on a daily basis, so you know what they say!

  • An introduction to Machine Learning, from supervised to unsupervised learning.

  • Practical tips from experts in the field.

About the instructor

Kelwin Fernandes

Kelwin is the co-founder and CEO of NILG.AI, a consulting company in Artificial Intelligence. He holds a Ph.D. in Machine Learning and has helped dozens of companies to introduce Machine Learning into their daily operations.


  • Who is this course for?

    This course was built considering no prior knowledge in Machine Learning. We use a simple language so anyone can learn the fundamentals in Machine Learning.

  • Do I need a deep understanding of maths and programming?

    No, you don't. The course is built for general people that feel curiosity about Machine Learning.

  • How long does the subscription last?

    You will have access to the platform for one year starting at your enrollment date, including all updates to the course content during this period. The referred price is a one-time fee for this period.