What will you be able

After taking this course you will be able to use Python to search for inaccurate data points and then reformat the data to make it more useful, You’ll also understand when to use techniques like clustering, regressions, or classifications. And you’ll be able to use predictive modeling to suggest other things people might like based on past data, similar to sites like Amazon or Netflix.

Recommended duration: 3 months (24 hours) 
If you have any questions or concerns, feel free to reach out to us at [email protected]

What will you

Introduction to Machine Learning
Learn the most important concepts about machine learning.

Supervised Learning: Regression

Use algorithms to find a data line and use it to predict future data.

Regression Cumulative Project

Practice your regression skills on a real-world problem.

Supervised Learning: Introduction to Classification

Learn to identify which sets of categories observations belong in.

Supervised Learning: Advanced Classification

Learn more complicated data classification.

Supervised Machine Learning Cumulative Project

Use your understanding of supervised machine learning models to interpret data.

Unsupervised Learning

Complete the K-Means clustering algorithm to learn how unsupervised machine learning works.

Unsupervised Machine Learning Cumulative Project

Make a project that shows your knowledge of unsupervised machine learning.

Perceptrons and Neural Networks

Learn the building blocks of neural networks and begin to create your own.

Machine Learning Project
A project based on your interests.