SDSC8005 - Optimization | ||||||||
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| * The offering term is subject to change without prior notice | ||||||||
Course Aims | ||||||||
In this course we will learn how to formulate, analyze and solve various optimization problems. Topics include convex analysis, classifying different types of optimization problems, optimality conditions, duality, unconstrainted optimization, and optimization under uncertainty. No prior optimization background is required for this class. However, students should have workable knowledge in multivariable calculus, linear algebra and matrix theory. | ||||||||
Assessment (Indicative only, please check the detailed course information) | ||||||||
Continuous Assessment: 100% | ||||||||
Examination Duration: 0 hours | ||||||||
Detailed Course Information | ||||||||
| SDSC8005.pdf | ||||||||
Useful Links | ||||||||
| School of Data Science | ||||||||
