Machine Learning Specialization

This Specialization from leading researchers at the University of Washington introduces you to the exciting, high-demand field of Machine Learning. Through a series of practical case studies, you will gain applied experience in major areas of Machine Learning including Prediction, Classification, Clustering, and Information Retrieval. You will learn to analyze large and complex datasets, create systems that adapt and improve over time, and build intelligent applications that can make predictions from data.

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4 courses

Follow the suggested order or choose your own.

Projects

Designed to help you practice and apply the skills you learn.

Certificates

Highlight your new skills on your resume or LinkedIn.

Projects Overview

Learners will implement and apply predictive, classification, clustering, and information retrieval machine learning algorithms to real datasets throughout each course in the specialization. They will walk away with applied machine learning and Python programming experience.

 

COURSE 1

Machine Learning Foundations: A Case Study Approach

Commitment

6 weeks of study, 5-8 hours/week

Subtitles: English, Korean, Vietnamese, Chinese (Simplified)

About the Course

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classific

 

COURSE 2

Machine Learning: Regression

Commitment: 6 weeks of study, 5-8 hours/week

Subtitles: English

About the Course

Case Study - Predicting Housing Prices In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...).

 

COURSE 3

Machine Learning: Classification

Commitment

7 weeks of study, 5-8 hours/week

Subtitles: English

About the Course

Case Studies: Analyzing Sentiment & Loan Default Prediction In our case study on analyzing sentiment, you will create models that predict a class (positive/negative sentiment) from input features (text of the reviews, user profile information,

 

COURSE 4

Machine Learning: Clustering & Retrieval

Commitment

6 weeks of study, 5-8 hours/week

Subtitles: English

About the Course

Case Studies: Finding Similar Documents A reader is interested in a specific news article and you want to find similar articles to recommend. What is the right notion of similarity? Moreover, what if there are millions of other documents?

 

7-day Free Trial

• Unlimited access to all courses in the Specialization

  Watch lectures, try assignments, participate in discussion forums, and more.

• Cancel anytime.

  No penalties - simply cancel before the trial ends if it's not right for you.

• $49 USD per month to continue learning after trial ends.

  Go as fast as you can - the faster you go, the more you save.

• Certificate when you complete.

  Share on your resume, LinkedIn, and CV.

Emily Fox

Amazon Professor of Machine Learning

Carlos Guestrin

Amazon Professor of Machine Learning

To participate in this training, you can Enroll