Learn about linear programming if you want to be able to use more tools for data modeling and analysis. Linear programming is a mathematical technique. It's used to maximize or minimize a linear function, similar to a regression, that includes such variables as production output or inventory cost. It is related to regression analysis. Linear programming can be used to solve problems in the face of different restraints. Linear programming can help you pull insights and make decisions from the information that's been collecting for a long time. It's used in financial analysis, financial modeling, and strategic planning. It's often part of algorithms written by computer programmers, too, although it does not necessarily require computer programming to learn it.‎

Career opportunities that arise from learning linear programming are mostly in computer programming, financial analysis, and quantitative data modeling. It can be applied to any field where data is generated, resources are limited, and decisions have to be made. Also, it is important to understand that the role of linear programming generates results with discrete optimization so that the outcomes are used effectively. It is also useful to understand the power and limitations of linear programming if you will be using reports and making decisions based on its results. It is a powerful component of computer programs that include advanced algorithms or game theory.‎

Online courses on Coursera can help you learn linear programming in a way that works best for how you will use it. Several courses help you learn linear programming in the context of financial analysis. Some emphasize mathematics, others concentrate on game theory or computer programming. Some involve spreadsheets, and others call for work with specific programming languages. Courses are at the beginning, intermediate, and advanced levels to accommodate a range of experience. The courses include lectures, readings, and projects so that you can apply what you learn. There are also Guided Projects that let you apply and refine your current knowledge of linear programming.‎