15.053x | Spring 2021 | Undergraduate

Optimization Methods in Business Analytics

Course Description

This course will examine optimization through a business analytics lens. Students will learn the theoretical aspects of linear programming, basic Julia programming, and proficiency with linear and nonlinear solvers. Theoretical components of the course are made approachable and require no formal background in linear …

This course will examine optimization through a business analytics lens. Students will learn the theoretical aspects of linear programming, basic Julia programming, and proficiency with linear and nonlinear solvers. Theoretical components of the course are made approachable and require no formal background in linear algebra or calculus.

The primary focus of the course is optimization modeling. As a six-week subject, it covers about half of the material of the MIT OpenCourseWare version, 15.053 Spring 2013. The topics of the 2013 subject were optimization modeling, algorithms, and theory.

As part of the Open Learning Library (OLL), this course is free to use. You have the option to sign up and enroll if you want to track your progress, or you can view and use all the materials without enrolling. Resources on OLL allow learners to learn at their own pace while receiving immediate feedback through interactive content and exercises.

Learning Resource Types
Lecture Videos
Recitation Videos
Problem Sets with Solutions
A diagram of a 5x5 grid of circles, with one red circle and its adjacent circles highlighted.
The game of Fiver involves a grid of circles that are green on one side and red on the other. Starting with all the green sides showing, in each move, the player flips one circle and its four adjacent circles until all the red sides are showing. Optimizing the Fiver solution is used to illustrate integer programming techniques. (Image by Prof. James Orlin.)