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Randomized Algorithms for Data Analysis (RAD)

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README.md
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README.md

Randomized Algorithms for Data Analysis (RAD)

Introduction

This course is like AD mixed with MASD/MAD in terms of the amount of probability theory discussed.

The book is very "dense" in the amount of information per page, so it is advisable to attend the lectures. At the 2019 version of the course there weren't slides. It can therefore be advisable to take a look at the Randomized Algorithms slides (do note however what stuff isn't needed from them, and what you should learn in addition).

Exam (based on RAD-2019)

The exam structure is exactly like Algorithms and Data Structures. Therefore you should probably read the advice at the AD folder.

You can view example dispositions (as well as some lecture notes) at shmulvad's RAD-repo. A set of dispositions, based on shmulvad's but in a slightly different form, can be found on Notion.