Machine Learning in Python: Intermediate

Dive more into Machine Learning

In this course, you'll learn Machine Learning with Python, including multi-class classification, linear regression, k-means clustering, gradient descent and neural networks.

By the end of this course, you'll be able to:

  • Understand and apply intermediate linear regression and logistic regression concepts.
  • Understand how to prevent overfitting, a common problem in machine learning.

Course Info:

Machine Learning in Python: Intermediate


The average completion time for this course is 10-hours.

This course requires a premium subscription and includes four missions and one guided project.  It is the 21st course in the Data Scientist in Python path.


Learn Intermediate Machine Learning Techniques

Logistic Regression

Learn the basics of logistic regression and classification.

Introduction to Evaluating Binary Classifiers

Learn how to evaluate a classification model.

Multiclass Classification

Learn how to use logistic regression with multiple categories.


Learn how to detect overfitting and about the bias-variance tradeoff.

Clustering Basics

Learn how to use clustering to group senators using voting patterns.

K-Means Clustering

Learn to create and interpret scatter plots to explore relationships between variables.

Predicting the Stock Market

Use machine learning techniques to predict the price of the SP500.