Machine Learning with Python by IBM on Coursera

Learn ML with this great IBM Machine Learning course on Coursera

This course will teach you the basics of Machine Learning and Data Science with the most used programming language for advanced analytics in the world: Python.

We really like this course, as it is not just a course that will teach you the main concepts of Machine Learning like regression, classification, clustering, or the different Machine Learning algorithms, but also show you the main purpose of the field and where it is succesfully applied in the real world.

Many times courses fail to teach the practical applications of the subjects they teach. This is not the case, as you will see real-life examples of Machine Learning and how the affect society.

It is a very easy to follow course, that explains complicated concepts in a simple manner that follows a very well defined flow covering the maths behind the main concepts and also how to implement them in Python.

Organised in a series of videos with quizzies, exercises or labs in Jupyter Notebooks, assessments and a final project (which could have been a little better defined in our opinion), this course will teach you the basics of Machine Learning and you will just need a little Python programming knowledge and some basic math skills.

Coursera as always provides great forums in case you have any questions or get stuck in a certain exercise (the quizzies are challenging for beginners but doable if you have absorbed well the main concetps). Lets see what it contains!

Contents

1. Introduction to Machine Learning: Applications of Machine learning in different sectors like healthcare, banking and telco, and get a main overview of the fundamental concepts of Machine Learning.
2. Regression: As most ML courses we start with Linear and multiple regression, along with their applications like for example house price estimation. In the labs you will apply regression in two different datasets and learn how to evaluate the quality of your regression models.
3. Classification: Different classification algorithms like K-nearest neighbours, Decision tress, Logistic Regression and Support vector machines and how each method compares to the rest. Lastly you will see different classification metrics and learn about the Confusion Matrix.
4. Clustering: Now it is the time for un-supervised learning, widely used for real life applications like customer segmentation for Marketing purposes. You will learn about Hierarchical and Density Based clustering.
5. Recommender systems: one of the most famous applications of Machine Learning – Learn how Netflix knows what show you are going to watch next or how Amazon always spots that product that you were thinking about.
6. Final project: apply everything you have learned and submit a project for peer evaluation. In our opinion this project could have been a little better defined, and more challenging, but it is the only but that we give to this course.

Who is IBM Machine Learning with Python on Coursera for?

In our opinion this course is for enthusiast that want to learn about Machine Learning with no previous experience in the field. To complete it easily and make the most out of it, we recommend some previous Python programming knowledge and some very basic math skills.

If you need to learn Python, don’t worry, we’ve got the resources for you to do so. Some beginner Python books that you might want to check out are:

• Python Crash Course.
• Automating the Boring Stuff with Python.
• Learning Python by Mark Lutz.

Some other great resources for Learning Python, after which you will be able to tackle this course easily are:

• Kaggle Learn Python Tutorials.
• Learning Python Course on Codeacademy.
• Real Python Website.

Course summary:

IBM Machine Learning with Python is a great course for those that want both, to learn the fundamental technical concepts underlying machine learning and the real world applications of the field.

You will learn how to turn this theoretical knowledge into practice by programming in Python, and test your skill with many quizzies, exercises and labs.

This is a great course to begin with before tackling books like the following, which for us is the perfect book to take your knowledge from begginer to expert:

Duration: The course says that on total it can be completed in about 25 hours, but we recommend taking it slowly, embracing the content, and taking the time to complete the exercises.

Cost: This course can be taken for free like most Coursera courses, auditing it, however you will not get a certificate, and you will not be able to access some of the exercises.

As always, we hope you enjoyed the post on this IBM Machine Learning course with Python on Coursera. Learn a lot and come back to read How to Learn Machine Learning! Until then, take care 🙂

Tags: Machine Learning with Python, Machine Learning course for beginners, IBM Machine learning Coursera.