Learn Optimization for Free with Gurobi

NEW! MOOC: Introduction to Optimization Through the Lens of Data Science

This massive open online course (MOOC) has been developed by Gurobi in partnership with Dr. Joel Sokol, professor at Georgia Tech. It provides a unique opportunity for data scientists to enhance their skill sets with optimization. It also equips educators to bring cutting-edge, practical optimization knowledge into their classrooms.

Access the free course, “Introduction to Optimization Through the Lens of Data Science.”

If you haven’t already checked out the resources in the blog article, “Getting Started with Mathematical Optimization in Python,” we suggest you start there. In just minutes, you’ll be tinkering around inside the Gurobi Python interface, engaging with optimization models, and seeing how optimization and machine learning can work together. Once you’ve done that, come back here to take your learning to the next level.

Read the article, “Getting Started with Mathematical Optimization in Python.”

Opti101: Optimization Training for Data Scientists

In this on-demand, self-paced training, optimization experts will guide you through the basics and give you the tools to formulate and code a comprehensive application that will optimize rebalancing of bike-share stations using a machine learning-based forecast.

Watch the training series, “Opti101.” Our popular Opti201 series will be available on-demand later in 2024.

Functional Code Examples

Gurobi’s Functional Code Examples dive into how to use Gurobi, across various programming languages, including C, C++, C#, Java, Visual Basic, and Python. The examples include reading a model from a file and building simple models, to implementing more complex applications such as workforce scheduling and the classic diet problem. They also demonstrate the use of specific features like multi-objective optimization, solution pools, and piecewise-linear objective functions.

View our Functional Code Examples library.

The Burrito Optimization Game is an interactive, web-based game that introduces the concepts of mathematical optimization in a fun and engaging way. Players run a burrito shop and make decisions about what ingredients to buy, how many burritos to make, and what prices to set, with the goal of maximizing profit. The game comes with a comprehensive game guide and a teaching guide, making it a valuable resource for both individual learners and educators.

Watch the webinar, “Gamifying Optimization with the Burrito Optimization Game.”

The Gurobipy Card Game is another innovative tool that makes learning optimization modeling more approachable. The game consists of two sets of cards—one representing the elements of an optimization model and the other representing the modeling constructs and data structures used when building a model in Gurobi’s Python interface. The goal is to match each element card with the corresponding construct card, making it a fun and interactive way to learn the key elements of optimization modeling in Python.

Read the article, “Optimization Gamification: Introducing the Gurobipy Card Game.”

To help data scientists explore the world of optimization, we created Gurobi Machine Learning—an open-source Python project to embed trained machine learning models directly into Gurobi. It allows you to add a trained machine learning model as a constraint to a Gurobi model (e.g., from scikit-learn, TensorFlow/Keras, or PyTorch). This way, you can easily connect your forecasting with optimization.

Read more about Gurobi Machine Learning.

Optimization Application Demos

Our optimization application demos are helpful for demonstrating industry-specific use cases, including location planning, cutting stock, resource matching, and workforce scheduling. You just enter your sample information and watch the solver quickly output an answer. Keep in mind that businesses that try to solve these problems manually will need months of dedicated resources simply to generate a “good enough” solution. But with optimization, you can generate the best-possible solution in under a second.

View all of our application demos.

Mathematical Modeling Training Series

Our linear programming and mixed integer programming training videos walk you step-by-step through how to create mathematical models.

View all of our training videos.

Take your optimization projects to the next level with Gurobi’s Generative AI tools.

For users new to mathematical optimization: the AI Modeling Documentation provides best practices, examples, and resources to help you understand and apply AI-driven optimization. Use the Prompt Engineer to define optimization-ready problem statements, and let the Modeling Assistant generate formulations, Python code, and solutions.

For experienced modelers: Gurobot, our custom AI chatbot, is here to assist with optimization modeling, API questions, and troubleshooting—ensuring your projects run smoothly. Discover more and get started with Gurobot.

Learn more from our Senior DevOps Engineer, Thomas Braam, in this video overview.

Check out our Prompt Engineering Demo and AI Modeling Assistant Demo to help you get started.

Events and Webinars

Learn from the experts! We host live and virtual learning events regularly throughout the year.

Check out our Gurobi Events page to stay in-the-know!