你将学到什么
Data exploration, preparation and cleaning
Supervised machine learning techniques
Unsupervised machine learning techniques
Model performance improvement
课程概况
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.
课程大纲
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.
预备知识
To complete this course successfully, you should have:
A basic knowledge of math
Some programming experience - R is preferred.
A willingness to learn through self-paced study.
常见问题
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.
