About this courseSkip About this course
Machine learning uses computers to run predictive models that learn from existing data in order to forecast future behaviors, outcomes, and trends.
In this data science course, you will be given clear explanations of machine learning theory combined with practical scenarios and hands-on experience building, validating, and deploying machine learning models. You will learn how to build and derive insights from these models using R, and Azure Notebooks.
edX offers financial assistance for learners who want to earn Verified Certificates but who may not be able to pay the fee. To apply for financial assistance, enroll in the course, then follow this link to complete an application for assistance.
What you'll learnSkip What you'll learn
After completing this course, you will be familiar with the following concepts and techniques:
- Data exploration, preparation and cleaning
- Supervised machine learning techniques
- Unsupervised machine learning techniques
- Model performance improvement
- Introduction to Machine Learning
- Exploring Data
- Data Preparation and Cleaning
- Getting Started with Supervised Learning
- Improving Model Performance
- Machine Learning Algorithms
- Unsupervised Learning
Note: This syllabus is preliminary and subject to change.
Meet your instructors
Pursue a Verified Certificate to highlight the knowledge and skills you gain $99.00
Official and Verified
Receive an instructor-signed certificate with the institution's logo to verify your achievement and increase your job prospects
Add the certificate to your CV or resume, or post it directly on LinkedIn
Give yourself an additional incentive to complete the course
Support our Mission
EdX, a non-profit, relies on verified certificates to help fund free education for everyone globally
Frequently asked questions
Q: The prerequisites include R Programming?
A: R is used extensively in the machine learning and artificial intelligence fields. The practical elements of this course involve writing code in R. For the most part, you'll be given the code you need to complete the exercises; but a basic knowledge of R syntax will improve your understanding of what's going on in the labs and demonstrations. Consider taking course DAT204x: Introduction to R for Data Science before taking this class.
Q: What hardware and software do I need to complete this class?
A: You will need a computer running Windows, Mac OSX, or Linux and a web browser. Optionally, you can install R - but you will be able to complete the labs using a free online environment, so this is not required.
Q: Will I need a Microsoft Azure subscription to complete this class?
A: No. You will be able to complete the labs using a local R installation or the Microsoft Azure Notebooks service, which is a free service that does not require an Azure subscription.
Who can take this course?
Unfortunately, learners from one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. EdX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.