The Analytics Edge [edX] Summer 2015

The Analytics Edge [edX] Summer 2015 (319 files)
2 Linear Regression/2_10.mp4 124.20MB
6 Clustering/6_1.mp4 4.89MB
6 Clustering/6_22.mp4 8.47MB
6 Clustering/6_11.mp4 14.41MB
6 Clustering/6_19.mp4 12.76MB
6 Clustering/6_6.mp4 7.51MB
6 Clustering/6_3.mp4 11.42MB
6 Clustering/6_13.mp4 9.14MB
6 Clustering/6_14.mp4 3.30MB
6 Clustering/6_20.mp4 17.35MB
6 Clustering/6_17.mp4 27.29MB
6 Clustering/6_15.mp4 3.28MB
6 Clustering/6_7.mp4 38.15MB
6 Clustering/6_16.mp4 8.45MB
6 Clustering/6_12.mp4 12.56MB
6 Clustering/6_5.mp4 13.22MB
6 Clustering/6_10.mp4 6.22MB
6 Clustering/6_21.mp4 32.58MB
6 Clustering/6_8.mp4 30.15MB
6 Clustering/6_18.mp4 29.66MB
6 Clustering/6_4.mp4 7.94MB
6 Clustering/6_9.mp4 8.22MB
3 Logistic Regression/3_5.mp4 43.44MB
3 Logistic Regression/3_8.mp4 19.54MB
3 Logistic Regression/3_13.mp4 6.47MB
3 Logistic Regression/3_16.mp4 2.89MB
3 Logistic Regression/3_10.mp4 10.98MB
3 Logistic Regression/3_4.mp4 9.03MB
3 Logistic Regression/3_15.mp4 10.89MB
3 Logistic Regression/3_11.mp4 9.68MB
3 Logistic Regression/3_2.mp4 8.83MB
3 Logistic Regression/3_18.mp4 23.56MB
3 Logistic Regression/3_1.mp4 4.69MB
3 Logistic Regression/3_9.mp4 6.55MB
3 Logistic Regression/3_12.mp4 33.19MB
3 Logistic Regression/3_17.mp4 11.32MB
3 Logistic Regression/3_7.mp4 21.93MB
3 Logistic Regression/3_3.mp4 8.44MB
3 Logistic Regression/3_19.mp4 19.00MB
3 Logistic Regression/3_6.mp4 21.00MB
3 Logistic Regression/3_14.mp4 4.37MB
3 Logistic Regression/3_21.mp4 12.54MB
3 Logistic Regression/3_20.mp4 27.93MB
8 Linear Optimization/8_22.mp4 43.29MB
8 Linear Optimization/8_20.mp4 11.17MB
8 Linear Optimization/8_18.mp4 11.81MB
8 Linear Optimization/8_12.mp4 34.85MB
8 Linear Optimization/8_4.mp4 8.45MB
8 Linear Optimization/8_1.mp4 4.25MB
8 Linear Optimization/8_19.mp4 7.37MB
8 Linear Optimization/8_15.mp4 4.30MB
8 Linear Optimization/8_8.mp4 12.46MB
8 Linear Optimization/8_23.mp4 31.17MB
8 Linear Optimization/8_5.mp4 21.85MB
8 Linear Optimization/8_3.mp4 4.96MB
8 Linear Optimization/8_16.mp4 4.67MB
8 Linear Optimization/8_17.mp4 11.31MB
8 Linear Optimization/8_13.mp4 7.62MB
8 Linear Optimization/8_21.mp4 30.45MB
8 Linear Optimization/8_7.mp4 16.94MB
8 Linear Optimization/8_11.mp4 15.19MB
8 Linear Optimization/8_9.mp4 7.79MB
8 Linear Optimization/8_2.mp4 8.56MB
8 Linear Optimization/8_14.mp4 8.98MB
8 Linear Optimization/8_24.mp4 13.11MB
8 Linear Optimization/8_10.mp4 12.26MB
8 Linear Optimization/8_6.mp4 6.19MB
4 Trees/4_2.mp4 14.67MB
4 Trees/4_9.mp4 8.65MB
4 Trees/4_6.mp4 25.36MB
4 Trees/4_24.mp4 7.13MB
4 Trees/4_14.mp4 8.88MB
4 Trees/4_16.mp4 15.45MB
4 Trees/4_13.mp4 8.43MB
4 Trees/4_10.mp4 9.69MB
4 Trees/4_11.mp4 11.39MB
4 Trees/4_5.mp4 22.97MB
4 Trees/4_23.mp4 22.33MB
4 Trees/4_19.mp4 13.60MB
4 Trees/4_18.mp4 2.22MB
4 Trees/4_4.mp4 6.36MB
4 Trees/4_8.mp4 14.86MB
4 Trees/4_17.mp4 7.25MB
4 Trees/4_22.mp4 20.58MB
4 Trees/4_20.mp4 41.39MB
4 Trees/4_12.mp4 4.99MB
4 Trees/4_1.mp4 5.81MB
4 Trees/4_15.mp4 7.69MB
4 Trees/4_21.mp4 21.47MB
4 Trees/4_7.mp4 19.48MB
4 Trees/4_3.mp4 16.77MB
4 Trees/4_25.mp4 23.61MB
1 Introduction to Analytics/1_9.mp4 12.32MB
1 Introduction to Analytics/1_7.mp4 2.54MB
1 Introduction to Analytics/1_10.mp4 16.39MB
1 Introduction to Analytics/1_19.mp4 16.02MB
1 Introduction to Analytics/1_1.mp4 5.59MB
1 Introduction to Analytics/1_15.mp4 3.22MB
1 Introduction to Analytics/1_11.mp4 36.86MB
1 Introduction to Analytics/1_3.mp4 52.15MB
1 Introduction to Analytics/1_6.mp4 4.28MB
1 Introduction to Analytics/1_16.mp4 5.60MB
1 Introduction to Analytics/1_5.mp4 5.94MB
1 Introduction to Analytics/1_2.mp4 10.92MB
1 Introduction to Analytics/1_20.mp4 15.47MB
1 Introduction to Analytics/1_18.mp4 32.29MB
1 Introduction to Analytics/1_14.mp4 8.60MB
1 Introduction to Analytics/1_8.mp4 4.40MB
1 Introduction to Analytics/1_21.mp4 12.81MB
1 Introduction to Analytics/1_12.mp4 21.20MB
1 Introduction to Analytics/1_13.mp4 14.92MB
1 Introduction to Analytics/1_4.mp4 4.53MB
1 Introduction to Analytics/1_17.mp4 14.64MB
9 Integer Optimization/9_8.mp4 7.76MB
9 Integer Optimization/9_3.mp4 28.72MB
9 Integer Optimization/9_13.mp4 87.83MB
9 Integer Optimization/9_1.mp4 12.90MB
9 Integer Optimization/9_9.mp4 3.44MB
9 Integer Optimization/9_14.mp4 58.89MB
9 Integer Optimization/9_7.mp4 6.90MB
9 Integer Optimization/9_5.mp4 5.68MB
9 Integer Optimization/9_6.mp4 8.42MB
9 Integer Optimization/9_4.mp4 18.23MB
9 Integer Optimization/9_2.mp4 18.35MB
9 Integer Optimization/9_12.mp4 10.98MB
9 Integer Optimization/9_10.mp4 2.78MB
9 Integer Optimization/9_11.mp4 16.04MB
5 Text Analytics/5_14.mp4 14.53MB
5 Text Analytics/5_9.mp4 4.03MB
5 Text Analytics/5_17.mp4 8.55MB
5 Text Analytics/5_4.mp4 11.36MB
5 Text Analytics/5_5.mp4 16.15MB
5 Text Analytics/5_21.mp4 9.07MB
5 Text Analytics/5_24.mp4 1.80MB
5 Text Analytics/5_7.mp4 25.49MB
5 Text Analytics/5_1.mp4 4.70MB
5 Text Analytics/5_3.mp4 6.06MB
5 Text Analytics/5_23.mp4 7.80MB
5 Text Analytics/5_2.mp4 5.75MB
5 Text Analytics/5_15.mp4 31.66MB
5 Text Analytics/5_16.mp4 3.25MB
5 Text Analytics/5_10.mp4 23.83MB
5 Text Analytics/5_20.mp4 15.59MB
5 Text Analytics/5_12.mp4 6.15MB
5 Text Analytics/5_13.mp4 9.21MB
5 Text Analytics/5_19.mp4 21.36MB
5 Text Analytics/5_11.mp4 9.63MB
5 Text Analytics/5_22.mp4 12.24MB
5 Text Analytics/5_18.mp4 32.26MB
5 Text Analytics/5_6.mp4 34.41MB
5 Text Analytics/5_8.mp4 9.22MB
7 Visualization/7_12.mp4 20.27MB
7 Visualization/7_16.mp4 9.58MB
7 Visualization/7_19.mp4 38.22MB
7 Visualization/7_8.mp4 10.68MB
7 Visualization/7_11.mp4 48.15MB
7 Visualization/7_1.mp4 5.80MB
7 Visualization/7_15.mp4 4.85MB
7 Visualization/7_18.mp4 3.51MB
7 Visualization/7_13.mp4 2.67MB
7 Visualization/7_7.mp4 35.37MB
7 Visualization/7_6.mp4 28.08MB
7 Visualization/7_3.mp4 3.54MB
7 Visualization/7_4.mp4 12.08MB
7 Visualization/7_17.mp4 22.21MB
7 Visualization/7_21.mp4 8.69MB
7 Visualization/7_14.mp4 3.11MB
7 Visualization/7_5.mp4 38.43MB
7 Visualization/7_9.mp4 31.12MB
7 Visualization/7_20.mp4 11.81MB
7 Visualization/7_2.mp4 6.83MB
7 Visualization/7_10.mp4 18.87MB
Working Files/r/Unit1_Recitation.R 2.98kB
Working Files/r/Unit3_Framingham.R 0.96kB
Working Files/r/Unit4_SupremeCourt.R 2.38kB
Working Files/r/Unit7_Recitation.R 3.55kB
Working Files/r/Unit6_Netflix.R 1.62kB
Working Files/r/Unit6_Recitation.R 2.20kB
Working Files/r/Unit2_Moneyball.R 0.63kB
Working Files/r/Unit7_Crime.R 5.99kB
Working Files/r/Unit3_ModelingExpert.R 1.75kB
Working Files/r/Unit5_Twitter.R 2.62kB
Working Files/r/Unit2_WineRegression.R 1.23kB
Working Files/r/Unit4_Recitation.R 3.36kB
Working Files/r/Unit4_D2Hawkeye.R 2.19kB
Working Files/r/Unit3_Recitation.R 1.58kB
Working Files/r/Unit7_WHO.R 2.48kB
Working Files/r/Unit2_Recitation.R 1.53kB
Working Files/r/Unit5_Recitation.R 2.11kB
Working Files/r/Unit1_IntroductionR.R 1.88kB
Working Files/xlsx/AirlineRM_Connecting.xlsx 41.56kB
Working Files/xlsx/PfizerReps (1).xlsx 39.93kB
Working Files/xlsx/Gerrymandering.xlsx 41.82kB
Working Files/xlsx/AirlineRM_Complete.xlsx 43.98kB
Working Files/xlsx/IMRT_SimpleExample_Complete.xlsx 42.09kB
Working Files/xlsx/IMRT_SimpleExample.xlsx 41.37kB
Working Files/xlsx/Investment.xlsx 43.17kB
Working Files/xlsx/SportsScheduling_Complete.xlsx 42.09kB
Working Files/xlsx/SelectingHotels.xlsx 44.84kB
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Type: Course
Tags: machine learning, analytics, MIT, R

title= {The Analytics Edge [edX] Summer 2015},
journal= {},
author= {},
year= {},
url= {},
abstract= {The Analytics Edge
Through inspiring examples and stories, discover the power of data and use analytics to provide an edge to your career and your life.
About this course Skip Course Description
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

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.},
keywords= {Machine Learning, Analytics, MIT, R},
terms= {},
license= {},
superseded= {}

10 day statistics (45 downloads)

Average Time 6 hrs, 50 mins, 50 secs
Average Speed 124.43kB/s
Best Time 3 mins, 44 secs
Best Speed 13.69MB/s
Worst Time 3 days,19 hrs, 01 mins, 00 secs
Worst Speed 9.36kB/s