• Length:
    13 Weeks
  • Effort:
    10–15 hours per week
  • Price:

    FREE
    Add a Verified Certificate for $150 USD

  • Institution
  • Subject:
  • Level:
    Intermediate
  • Language:
    English
  • Video Transcript:
    English

Prerequisites

Basic mathematical knowledge (at a high school level). You should be familiar with concepts like mean, standard deviation, and scatterplots. Mathematical maturity and prior experience with programming will decrease the estimated effort required for the class, but are not necessary to succeed.

About this course

In the last decade, the amount of data available to organizations has reached unprecedented levels. Data is transforming business, social interactions, and the future of our society. In this course, you will learn how to use data and analytics to give an edge to your career and your life. We will examine real world examples of how analytics have been used to significantly improve a business or industry. These examples include Moneyball, eHarmony, the Framingham Heart Study, Twitter, IBM Watson, and Netflix. Through these examples and many more, we will teach you the following analytics methods: linear regression, logistic regression, trees, text analytics, clustering, visualization, and optimization. We will be using the statistical software R to build models and work with data. The contents of this course are essentially the same as those of the corresponding MIT class (The Analytics Edge). It is a challenging class, but it will enable you to apply analytics to real-world applications.

The class will consist of lecture videos, which are broken into small pieces, usually between 4 and 8 minutes each. After each lecture piece, we will ask you a “quick question” to assess your understanding of the material. There will also be a recitation, in which one of the teaching assistants will go over the methods introduced with a new example and data set. Each week will have a homework assignment that involves working in R or LibreOffice with various data sets. (R is a free statistical and computing software environment we’ll use in the course. See the Software FAQ below for more info). At the end of the class there will be a final exam, which will be similar to the homework assignments.

What you'll learn

  • An applied understanding of many different analytics methods, including linear regression, logistic regression, CART, clustering, and data visualization
  • How to implement all of these methods in R
  • An applied understanding of mathematical optimization and how to solve optimization models in spreadsheet software

Meet your instructors

Dimitris Bertsimas
Boeing Professor of Operations Research
MIT
Allison O'Hair
Lecturer
Stanford University
John Silberholz
Assistant Professor of Technology and Operations at U. of Michigan's Ross School of Business
University of Michigan
Iain Dunning
Senior Research Engineeer
DeepMind Technologies Ltd
Angie King
Data Scientist
End-to-End Analytics
Velibor Misic
Assistant Professor at UCLA's Decisions, Operations and Technology Management Anderson School of Management
University of California, Los Angeles
Nataly Youssef
President
MyA Health

Pursue a Verified Certificate to highlight the knowledge and skills you gain $150.00

View a PDF of a sample edX certificate
  • Official and Verified

    Receive an instructor-signed certificate with the institution's logo to verify your achievement and increase your job prospects

  • Easily Shareable

    Add the certificate to your CV or resume, or post it directly on LinkedIn

  • Proven Motivator

    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

What do I need to know about the topic prior to enrolling in the course?

You only need to know basic mathematics. For most people, this is equivalent to basic high school mathematics. You should know concepts like mean, standard deviation, and histograms. This course is also useful for those who already have experience in the subject. In each lecture, recitation, and homework assignment, we use a different dataset and case to illustrate the method. Even if you are familiar with all of the methods taught, you can still learn a lot from the different examples.

What software will be used in the course?

We’ll be using two software programs in this class: R and LibreOffice. Both are free online, and you don’t need to be familiar with either of them to take the course. R is a free statistical and computing software environment and LibreOffice is similar to MS Office but a free open source program. Specifically we’ll use the LibreOffice module, Calc in this course. Don’t worry though - we’ll teach everything from scratch!