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Course Description

Optimization drives solutions across virtually every area of data science, machine learning, and predictive modeling. Whether powering recommendation systems, solving large-scale data matching, or refining algorithms, optimization provides the tools to make systems efficient and scalable.

In this course, you will explore key optimization techniques, including gradient descent algorithms, constrained and unconstrained methods, and stochastic approaches like stochastic gradient descent (SGD). You’ll adapt these tools to address high-impact computational challenges with precision and confidence. By the end of the course, you’ll understand optimization strategies that are essential for tackling real-world problems effectively.

Faculty Author

David Bindel; Anil Damle

Benefits to the Learner

  • Recognize and classify optimization problems as constrained or unconstrained and formulate solutions using mathematical structures
  • Implement gradient descent to optimize functions and analyze algorithmic convergence properties
  • Execute stochastic gradient descent algorithms for machine learning applications and compare SGD techniques to traditional gradient methods

Target Audience

  • Software engineers building AI-powered applications
  • Data analysts and scientists working with large-scale datasets
  • Engineers applying computational methods to complex systems
  • Web and frontend developers integrating machine learning features
  • Computational biologists and scientific researchers modeling real-world phenomena Investment managers leveraging quantitative analysis
  • Game developers optimizing physics engines and AI behaviors
  • Anyone in a technical role seeking to strengthen their mathematical foundation for AI and machine learning

Applies Towards the Following Certificates

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Enroll Now - Select a section to enroll in
Type
2 week
Dates
Nov 04, 2026 to Nov 17, 2026
Total Number of Hours
20.0
Course Fee(s)
Standard Price $999.00
Type
2 week
Dates
Jan 27, 2027 to Feb 09, 2027
Total Number of Hours
20.0
Course Fee(s)
Standard Price $999.00
Type
2 week
Dates
Apr 21, 2027 to May 04, 2027
Total Number of Hours
20.0
Course Fee(s)
Standard Price $999.00
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