
Description
This course will provide a rigorous and hands-on introduction to the central ideas and algorithms that constitute the core of the modern algorithms toolkit. Emphasis will be on understanding the high-level theoretical intuitions and principles underlying the algorithms we discuss, as well as developing a concrete understanding of when and how to implement and apply the algorithms. The course will be structured as a sequence of one-week investigations; each week will introduce one algorithmic idea, and discuss the motivation, theoretical underpinning, and practical applications of that algorithmic idea. Each topic will be accompanied by a mini-project in which students will be guided through a practical application of the ideas of the week. Topics include hashing, dimension reduction and LSH, boosting, linear programming, gradient descent, sampling and estimation, and an introduction to spectral techniques.
Prerequisites
Dates: | March 29 - June 4, 2021 |
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Units: | 3.00-4.00 |
Instructors: | Greg Valiant |
Delivery Option: |
Online
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For Credit | $4,056.00-$5,408.00 |
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Computer Science Department Requirement
Students taking graduate courses in Computer Science must enroll for the maximum number of units and maintain a B or better in each course in order to continue taking courses under the Non Degree Option.
Pre-registration for this course will secure your enrollment request and ensure timely processing of your application for potential course approval. Please note: course enrollment will be confirmed after March 19, 2021; after completing your pre-registration, no further action is required on your part.
This course may not currently be available to learners in some states and territories.