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Gurobi to Launch Free Massive Open Online Course (MOOC) on Optimization for Data Scientists
[April 10, 2024]

Gurobi to Launch Free Massive Open Online Course (MOOC) on Optimization for Data Scientists


Gurobi Optimization, LLC, the leader in decision intelligence technology, in collaboration with Dr. Joel Sokol, Harold E. Smalley Professor in Georgia Tech's H. Milton Stewart School of Industrial and Systems Engineering, and founding Director of Georgia Tech's Master of Science in Analytics degree, today announced the launch of a new free online course: "Introduction to Optimization Through the Lens of Data Science." The course, which aims to introduce optimization to data science learners, is now available online on Udemy.

In today's data-driven world, the ability to make informed, optimal decisions is more crucial than ever. Data scientists are adept at extracting insights from data, but leveraging those insights to make the best possible decisions requires a deep understanding of optimization. This course fills a critical gap in the current educational landscape, offering a comprehensive introduction to optimization tailored for data science professionals.

Course Features:

  • Expert Instruction: Led by Dr. Joel Sokol, this course draws on his extensive experience in optimization and analytics to provide learners with both theoretical knowledge and practical skills.
  • Tailored for Data Scientists: The curriculum is designed with data scientists in mind, focusing on practical applications of optimization in data science rather than deep theoretical concepts.
  • Comprehensive Curriculum: The course covers motivation, modeling, and real-world cases, nsuring learners understand not only how to use optimization, but also why it's important.
  • Hands-On Learning: Through interactive examples, case studies, and the use of the Gurobi Optimizer and Python's gurobipy library, students will gain hands-on experience in solving optimization problems.
  • Code-Focused Examples: The course is designed to meet data scientists where they are in their problem-solving journey, presenting the Python code right alongside the mathematical and English language versions of each problem.



Students can enroll for free on Udemy and work through the course and 130+ examples at their own pace. Educators are also encouraged to integrate this course material into their curriculum to provide students with a cutting-edge blend of data science and optimization skills. The course is designed to prepare students for the challenges of the modern world, equipping them with highly sought-after skills in the industry.

"We're excited to partner with Dr. Joel Sokol to launch this much-needed online course," explained Gurobi CEO, Duke Perrucci. "By making this learning accessible to data scientists around the world, we are not just educating the next generation of decision-makers-we're empowering them to solve some of the world's most challenging problems."


"Introduction to Optimization Through the Lens of Data Science, Parts 1 - 4" is now open for enrollment on Udemy. Data scientists, educators, and students interested in expanding their skill set and understanding of optimization are invited to register for this innovative, free course.

For more information and to enroll, please visit the Gurobi website.

About Gurobi Optimization

With Gurobi's decision intelligence technology, customers can make optimal business decisions in seconds. From workforce scheduling and portfolio optimization to supply chain design and everything in between, Gurobi identifies the optimal solution, out of trillions of possibilities.

As the leader in decision intelligence, Gurobi delivers easy-to-integrate, full-featured software and best-in-class support, with an industry-leading 98% customer satisfaction rating.

Founded in 2008, Gurobi has operations in the Americas, Europe, and Asia. It serves customers in nearly all industries, including organizations like SAP, Air France, and the National Football League. For more information, please visit https://www.gurobi.com/ or call +1 713 871 9341.


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