Data Science

Data Science: Machine Learning

Provided by Harvard University (HarvardX)
$49 USD
for a certificate
Study for free
Introductory
See Prerequisites

Learn the basics of machine learning, the science behind the most popular and successful data science techniques, to build a movie recommendation system.

Part of Professional Certificate: Data Science
Course Format:Instructor-Led
Start Date:Oct 12, 2018

What you will learn

  • The basics of machine learning
  • How to perform cross-validation to avoid overtraining
  • Several popular machine learning algorithms
  • How to build a recommendation system
  • What is regularization and why it is useful?

Overview

Perhaps the most popular data science methodologies come from machine learning. What distinguishes machine learning from other computer guided decision processes is that it builds prediction algorithms using data. Some of the most popular products that use machine learning include the handwriting readers implemented by the postal service, speech recognition, movie recommendation systems, and spam detectors.

In this course, part of our Professional Certificate Program in Data Science, you will learn popular machine learning algorithms, principal component analysis, and regularization by building a movie recommendation system.

You will learn about training data, a set of data used to discover potentially predictive relationships and how the data can come in the form of the outcome we want to predict and features that we will use to predict this outcome. As you build the movie recommendation system, you will learn how to train algorithms using training data so you can predict the outcome for future datasets. You will also learn about overtraining and techniques to avoid it such as cross-validation. All of these skills are fundamental to machine learning.

Before you start

This course is part of our Professional Certificate Program in Data Science and we recommend the preceeding courses in the series as prerequisites.
  • Instructor-Led: course contains assignments and exams that have specific due dates, and you complete the course within a defined time period.
  • Course ends: Nov 14, 2018

Meet Your Instructors

FAQ

Who can take this course?
Unfortunately, learners from Iran and Cuba will not be able to register for this course. While edX has received a licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer courses to learners from these countries, our licenses do not cover this course. EdX truly regrets that US sanctions prevent us from offering all of our courses to everyone, no matter where they live.

How often will the courses be offered?
Courses in the program are offered frequently, with overlap - so if now isn’t a good time for you to start one of the courses you need as a prerequisite or if you missed a deadline, there will be another offering of the course you need coming soon!
*please note that progress does not carry over from one offering to another.

Does the order of courses in the Professional Certificate Program matter?
Yes, order does matter, particularly for the first four courses in the sequence. For the later courses, depending on your previous experience, you may be able to swap the sequence of some of the courses. The courses are designed to be taken in the following order:
1. R Basics
2. Visualization
3. Probability
4. Inference and Modeling
5. Productivity Tools
6. Wrangling
7. Linear Regression
8. Machine Learning
9. Capstone

Do I need to register for all of the courses at once in order to be eligible for the Professional Certificate?
No! You can take courses individually - once you have obtained an ID Verified Certificate in each course, you will be eligible for the Professional Certificate. If you choose to pre-pay for the entire program, you receive a discount on the total registration cost.

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