Opti 202: Intermediate Mathematical Optimization for Data Scientists
Introduction to Optimization Through the Lens of Data Science
Unlock the power of optimized decision-making with this online course developed by Gurobi in partnership with Dr. Joel Sokol, professor at Georgia Tech.
Learn Optimization for Free with Gurobi
Dive into the world of mathematical optimization with our free resources! From interactive games to comprehensive guides, we’ve got you covered.
The Gurobi Python Modeling and Development Environment
When building an optimization model, one must choose from among two alternatives: Using Gurobi with a proprietary modeling language such as AMPL or GAMS, or using Gurobi with a full programming language such as C, C++, C#, Java, Python, VB, MATLAB or R.
Chapter 5 – Is there an example where Machine Learning and Optimization work together?
Chapter 4 – How can Machine Learning and Mathematical Optimization help with decisions?
Chapter 3 – Where do you see the opportunity to integrate Machine Learning and Mathematical Optimization?
Chapter 2 – What is Mathematical Optimization
Chapter 1 – What is Machine Learning?
Level 1 (Part 2) – Introduction for Data Scientists
Explore how data scientists can use tools such as MO in tandem with ML technologies to drive optimal decision-making and business outcomes.
