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The Analytics Edge

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.

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Massachusetts Institute of Technology

Rating 4.7 based on 118 ratings
Length 13 weeks
Effort 10 - 15 hours per week
Starts Oct 15 (in 13 weeks)
Cost $150
From Massachusetts Institute of Technology, MITx via edX
Instructors Dimitris Bertsimas, Allison O'Hair, John Silberholz, Iain Dunning, Angie King, Velibor Misic, Nataly Youssef, Alex Weinstein, Jerry Kung
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science
Tags Data Analysis & Statistics

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What people are saying

According to other learners, here's what you need to know

data science in 9 reviews

You'll get understanding of some most famous problems in data science (IBM Watson etc.)

I'd definitely recommend this course to anyone who is interested in pursuing career in data science.

One of the best and more thorough courses on data science.

I was thinking that it would be difficult for me to learn data science using R. But, it proved to be amazing.

Very useful class for data analysts.You learn a lot of cool R tricks and basic concepts,but if you are a student and not engaging in a data science project,it's very easy to forget everything you have learned.

If you are interested in having a first contact with R and to learn about some of the capabilities of data science, this course give a really good first idea.

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very well in 9 reviews

It is very well-structured with exercises and excellent explanation along the whole course.

The objective are very well developed and explained in a way that is very comfortable to follow.

This course goes very well with Intro Statistical Learning from Stanford Online.

The homework problems for this course are very well crafted and look at a variety of interesting data sets from basketball stats to tweets about Apple.

It is very practical, very well designed, and have many applications drilled into us so that we remember.

Lot of practice exams, the concepts are drilled very well.

Very practicle and very well designed.

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machine learning in 8 reviews

This would give the right blend of R programming as well as the concepts of data science & machine learning.

It's one of the best courses for introduction to data science including machine learning.

Lots of interesting subjects (regression, machine learning, optimization, ...) with a practical hands-on approach.

Every discussed concepts of machine learning field was accompanied with real world problems and solutions.

Some other MOOCs had introduced even more challenging concepts (Stanford's excellent Introduction to Statistical Learning and Andrew Ng's Machine Learning course on Coursera).

This is one of the best courses on the topic of Analytics/Data Science/Machine Learning that is out there.

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kaggle competition in 7 reviews

I did the Kaggle competition and finished in the middle of the pack (in the lower 0.6xx accuracy).

7 weeks into the class you take the training wheels off by participating in a Kaggle competition (open only to the class) where you apply the tools you have learned to predict happiness based on demographic and survey data from an app.

Is very well designed, also the most fun part was the Kaggle competition where you have to put all your knowledge that you have learned in the course.

Relevant Kaggle competition.

You'll feel empowered after this course as you'll have learned quite a bit of R. I would pair this course with the first courses of Coursera's Johns Hopkins Data Science Specialization, especially R Programming, to make the Kaggle competition more manageable.

The required kaggle competition was a fun interlude, and might well have served as a gateway to a future addiction.

The best part of this course is by far the Kaggle competition.

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case studies in 5 reviews

There are several case studies discussed as part of the course which give a good understanding of data analysis and application of various algorithms.

Lectures are detailed yet concise, focused on interesting case studies, combined with plenty of practical exercises to make sure you have understood the material presented.

Excellent course, well structured and with very interesting case studies.

The case studies were quite unique and exhaustive.

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real world in 5 reviews

The course uses real world examples of how analytics have been used to gain a competitive edge.

Excellent introduction of real world analytics using R I have taken several online statistics courses and a couple basic courses on using R software.

Thanks to all the instructors & support staff for a great course This courses use real world examples to teach several basic but important statistical models, in order to gain analytical edge.

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Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

BUSINESS ANALYTICS SPECIALIST - ENTERPRISE ANALYTICS $53k

Analytics/F&B Management $77k

Global Analytics $89k

V.P. Analytics $89k

Analytics Scientist $89k

Business Analytics & Advanced Analytics $90k

Digital Analytics $93k

Analyst, Analytics $94k

BI & Analytics $106k

Product Analytics $116k

Mobile Analytics $116k

Senior Analytics $198k

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edX

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Massachusetts Institute of Technology

Rating 4.7 based on 118 ratings
Length 13 weeks
Effort 10 - 15 hours per week
Starts Oct 15 (in 13 weeks)
Cost $150
From Massachusetts Institute of Technology, MITx via edX
Instructors Dimitris Bertsimas, Allison O'Hair, John Silberholz, Iain Dunning, Angie King, Velibor Misic, Nataly Youssef, Alex Weinstein, Jerry Kung
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science
Tags Data Analysis & Statistics

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