Browse Course Material
  • Syllabus

  • Readings

  • Lecture and Recitation Notes

  • Assignments

  • Unit Index

  • Unit 1: An Introduction to Analytics

    • 1.1 Welcome to Unit 1
    • 1.2 The Analytics Edge: Intelligence, Happiness, and Health (Lecture Sequence)
    • 1.3 Working with Data: An Introduction to R
    • 1.4 Understanding Food: Nutritional Education with Data (Recitation)
    • 1.5 Assignment 1
  • Unit 2: Linear Regression

    • 2.1 Welcome to Unit 2
    • 2.2 The Statistical Sommelier: An Introduction to Linear Regression
    • 2.3 Moneyball: The Power of Sports Analytics
    • 2.4 Playing Moneyball in the NBA (Recitation)
    • 2.5 Assignment 2
  • Unit 3: Logistic Regression

    • 3.1 Welcome to Unit 3
    • 3.2 Modeling the Expert: An Introduction to Logistic Regression
    • 3.3 The Framingham Heart Study: Evaluating Risk Factors to Save Lives
    • 3.4 Election Forecasting: Predicting the Winner Before any Votes are Cast (Recitation)
    • 3.5 Assignment 3
  • Unit 4: Trees

    • 4.1 Welcome to Unit 4
    • 4.2 Judge, Jury, and Classifier: An Introduction to Trees
    • 4.3 Keeping an Eye on Healthcare Costs: The D2Hawkeye Story
    • 4.4 Location, Location, Location: Regression Trees for Housing Data (Recitation)
    • 4.5 Assignment 4
  • Unit 5: Text Analytics

    • 5.1 Welcome to Unit 5
    • 5.2 Turning Tweets into Knowledge: An Introduction to Text Analytics
    • 5.3 Man vs. Machine: How IBM Built a Jeopardy Champion
    • 5.4 Predictive Coding: Bringing Text Analytics to the Courtroom (Recitation)
    • 5.5 Assignment 5
  • Unit 6: Clustering

    • 6.1 Welcome to Unit 6
    • 6.2 Recommendations Worth a Million: An Introduction to Clustering
    • 6.3 Predictive Diagnosis: Discovering Patterns for Disease Detection
    • 6.4 Seeing the Big Picture: Segmenting Images to Create Data (Recitation)
    • 6.5 Assignment 6
  • Unit 7: Visualization

    • 7.1 Welcome to Unit 7
    • 7.2 Visualizing the World: An Introduction to Visualization
    • 7.3 The Analytical Policeman: Visualization for Law and Order
    • 7.4 The Good, the Bad, and the Ugly: Visualization Recitation (Recitation)
    • 7.5 Assignment 7
  • Unit 8: Linear Optimization

    • 8.1 Welcome to Unit 8
    • 8.2 Airline Revenue Management: An Introduction to Linear Optimization
    • 8.3 Radiation Therapy: An Application of Linear Optimization
    • 8.4 Google AdWords: Optimizing Online Advertising (Recitation)
    • 8.5 Assignment 8
  • Unit 9: Integer Optimization

    • 9.1 Welcome to Unit 9
    • 9.2 Sports Scheduling: An Introduction to Integer Optimization
    • 9.3 eHarmony: Maximizing the Probability of Love
    • 9.4 Operating Room Scheduling: Making Hospitals Run Smoothly (Recitation)
    • 9.5 Assignment 9

Course Info

Instructor:
  • Prof. Dimitris Bertsimas
Course Number:
  • 15.071
Departments:
  • Sloan School of Management
As Taught In: Spring 2017
Level: Graduate

Topics

  • Business
    Management
    Operations Management
  • Mathematics
    Probability and Statistics

Learning Resource Types

theaters Lecture Videos
notes Lecture Notes
assignment_turned_in Problem Sets with Solutions
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Course Info
The Analytics Edge
  • Syllabus

  • Readings

  • Lecture and Recitation Notes

  • Assignments

  • Unit Index

  • Unit 1: An Introduction to Analytics

    • 1.1 Welcome to Unit 1
    • 1.2 The Analytics Edge: Intelligence, Happiness, and Health (Lecture Sequence)
    • 1.3 Working with Data: An Introduction to R
    • 1.4 Understanding Food: Nutritional Education with Data (Recitation)
    • 1.5 Assignment 1
  • Unit 2: Linear Regression

    • 2.1 Welcome to Unit 2
    • 2.2 The Statistical Sommelier: An Introduction to Linear Regression
    • 2.3 Moneyball: The Power of Sports Analytics
    • 2.4 Playing Moneyball in the NBA (Recitation)
    • 2.5 Assignment 2
  • Unit 3: Logistic Regression

    • 3.1 Welcome to Unit 3
    • 3.2 Modeling the Expert: An Introduction to Logistic Regression
    • 3.3 The Framingham Heart Study: Evaluating Risk Factors to Save Lives
    • 3.4 Election Forecasting: Predicting the Winner Before any Votes are Cast (Recitation)
    • 3.5 Assignment 3
  • Unit 4: Trees

    • 4.1 Welcome to Unit 4
    • 4.2 Judge, Jury, and Classifier: An Introduction to Trees
    • 4.3 Keeping an Eye on Healthcare Costs: The D2Hawkeye Story
    • 4.4 Location, Location, Location: Regression Trees for Housing Data (Recitation)
    • 4.5 Assignment 4
  • Unit 5: Text Analytics

    • 5.1 Welcome to Unit 5
    • 5.2 Turning Tweets into Knowledge: An Introduction to Text Analytics
    • 5.3 Man vs. Machine: How IBM Built a Jeopardy Champion
    • 5.4 Predictive Coding: Bringing Text Analytics to the Courtroom (Recitation)
    • 5.5 Assignment 5
  • Unit 6: Clustering

    • 6.1 Welcome to Unit 6
    • 6.2 Recommendations Worth a Million: An Introduction to Clustering
    • 6.3 Predictive Diagnosis: Discovering Patterns for Disease Detection
    • 6.4 Seeing the Big Picture: Segmenting Images to Create Data (Recitation)
    • 6.5 Assignment 6
  • Unit 7: Visualization

    • 7.1 Welcome to Unit 7
    • 7.2 Visualizing the World: An Introduction to Visualization
    • 7.3 The Analytical Policeman: Visualization for Law and Order
    • 7.4 The Good, the Bad, and the Ugly: Visualization Recitation (Recitation)
    • 7.5 Assignment 7
  • Unit 8: Linear Optimization

    • 8.1 Welcome to Unit 8
    • 8.2 Airline Revenue Management: An Introduction to Linear Optimization
    • 8.3 Radiation Therapy: An Application of Linear Optimization
    • 8.4 Google AdWords: Optimizing Online Advertising (Recitation)
    • 8.5 Assignment 8
  • Unit 9: Integer Optimization

    • 9.1 Welcome to Unit 9
    • 9.2 Sports Scheduling: An Introduction to Integer Optimization
    • 9.3 eHarmony: Maximizing the Probability of Love
    • 9.4 Operating Room Scheduling: Making Hospitals Run Smoothly (Recitation)
    • 9.5 Assignment 9

9 Integer Optimization

arrow_back browse course material library_books
  • BackAssignment 8
  • ContinueWelcome to Unit 9

9.1 Welcome to Unit 9

  • 9.1.1 Welcome to Unit 9

9.2 Sports Scheduling: An Introduction to Integer Optimization

  • 9.2.1 Video 1: Introduction
  • 9.2.2 Quick Question
  • 9.2.3 Video 2: The Optimization Problem
  • 9.2.4 Quick Question
  • 9.2.5 Video 3: Solving the Problem
  • 9.2.6 Quick Question
  • 9.2.7 Video 4: Logical Constraints
  • 9.2.8 Quick Question
  • 9.2.9 Video 5: The Edge

9.3 eHarmony: Maximizing the Probability of Love

  • 9.3.1 Video 1: The Goal of eHarmony
  • 9.3.2 Quick Question
  • 9.3.3 Video 2: Using Integer Optimization
  • 9.3.4 Quick Question
  • 9.3.5 Video 3: Predicting Compatibility Scores
  • 9.3.6 Quick Question
  • 9.3.7 Video 4: The Analytics Edge

9.4 Operating Room Scheduling: Making Hospitals Run Smoothly (Recitation)

  • 9.4.1 Welcome to Recitation 9
  • 9.4.2 Video 1: The Problem
  • 9.4.3 Video 2: An Optimization Model
  • 9.4.4 Video 3: Solving the Problem
  • 9.4.5 Video 4: The Solution

9.5 Assignment 9

  • 9.5.1 Even' Star Organic Farm Revisited

  • 9.5.2 Gerrymandering New Mexico

  • BackAssignment 8

  • ContinueWelcome to Unit 9

Course Info

Instructor:
  • Prof. Dimitris Bertsimas
Course Number:
  • 15.071
Departments:
  • Sloan School of Management
As Taught In: Spring 2017
Level: Graduate

Topics

  • Business
    Management
    Operations Management
  • Mathematics
    Probability and Statistics

Learning Resource Types

theaters Lecture Videos
notes Lecture Notes
assignment_turned_in Problem Sets with Solutions
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