Develop your programming skills with IBM’s free Machine Learning course in Python!


This course will help you delve into the basics of machine learning and how to apply them in the real world.

Python is an easy-to-understand programming language that is accessible for those who want to learn programming for the first time.

The course focuses on two main components of machine learning. Firstly, you will learn about the purpose and applications of machine learning.

Secondly, you will get an overview of machine learning topics such as supervised or unsupervised learning, model evaluation, and machine learning algorithms.

One of the advantages of this course is that you will be able to practice with real-life examples of machine learning. You will also see how machine learning affects society in ways you may not have imagined.

Upon completion of this course, you will be able to add new skills to your resume, such as regression, classification, clustering, sci-kit learning, and SciPy.

In addition, you will have new projects to add to your portfolio, such as cancer detection, economic trend prediction, customer churn prediction, recommendation engines, and many more.


The course is available online for free. You just need to choose the “audit course” option to access the course video content.

However, you will not be able to take exams or obtain the completion certificate. If you do not see the audit course option, please check the bottom using the scroll (in the form of a link).

Learning to program in Python and create machine learning algorithms is a highly valued skill in today’s job market.

Join Facialix’s official channel for more news, courses, and tutorials

Don’t miss the opportunity to learn these skills and add them to your resume. Enroll in IBM’s free course today!

Access the course using this link.

Julio Del Angel
Julio Del Angel

Information about courses, scholarships, programs, tutorials, whatever I find.

Articles: 2855

Leave a Reply

Your email address will not be published. Required fields are marked *