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Machine Learning for Software Engineers

87 Lessons
8 Quizzes
115 Challenges
163 Playgrounds
36 Illustrations

Part of the Machine Learning Path


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Become a Machine Learning Engineer

Add machine learning to your skillset and equip yourself to push the boundaries of AI technology. Get the hands-on practice you'll need to land a job in ML.

6 Modules

Course Overview

If you're a software engineer looking to add Machine Learning to your skillset, this is the place to start. This course will teach you to write useful code and create impactful Machine Learning applications immediately. From the start, you'll be given all the tools that you need to create industry-level machine learning projects. Rather than reading through dense theory, you’ll learn p... See more

How You'll Learn

Hands-on coding environments

You don’t get better at swimming by watching others. Coding is no different. Practice as you learn with live code environments inside your browser.

Faster than videos

Videos are holding you back. The average video tutorial is spoken at 150 words per minute, while you can read at 250. That‘s why our courses are text-based.

No set-up required

Start learning immediately instead of fiddling with SDKs and IDEs. It‘s all on the cloud.

Progress you can show

Built in assessments let you test your skills. Completion certificates let you show them off.

Hands-on coding environments

You don’t get better at swimming by watching others. Coding is no different. Practice as you learn with live code environments inside your browser.

Faster than videos

Videos are holding you back. The average video tutorial is spoken at 150 words per minute, while you can read at 250. That‘s why our courses are text-based.

No set-up required

Start learning immediately instead of fiddling with SDKs and IDEs. It‘s all on the cloud.

Progress you can show

Built in assessments let you test your skills. Completion certificates let you show them off.

Course Contents

1. What you'll learn from this course
4. Data Preprocessing with scikit-learn
5. Data Modeling with scikit-learn
6. Clustering with scikit-learn
7. Gradient Boosting with XGBoost
8. Deep Learning with TensorFlow
9. Deep Learning with Keras

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