courseraАнализ данных

Data Science Decisions in Time: Information Theory & Games

Курс от Johns Hopkins University

Средний≈ 24.1 чАнглийский

О курсе

This is part of our specialization on Making Decision in Time. For this third course we start with an intriguing study on SFPark and build new insights into the ideas that flow from this direction. The ending point should bring new code and new algorithm insights into perspective, and use, by many computer and data scientists.

Навыки, которые вы освоите

Game Theory Algorithms Data Science Cybersecurity Cyber Security Strategy Machine Learning Decision Intelligence Data-Driven Decision-Making

Программа курса

6 модулей · 32 учебных материалов

01Dynamically Changing Environments and Game Theory6 материалов

Introduction to Sequential Games

SFPark as an Example of a Dynamic GameВидео Non-cooperative Games as an Entry Point To Game TheoryВидео Game of Diplomacy as a Sequential Model of Asymmetric InformationВидео How to Win at a Quiz GameЗадание

Учитесь у экспертов

Thomas Woolf

Professor

Data Science Decisions in Time: Information Theory & Games

О курсе

Навыки, которые вы освоите

Программа курса

Introduction to Sequential Games

Учитесь у экспертов

Thomas Woolf

Cooperative Games as a Model for Decision Making

Can We Learn How to Design a Game to Stabilize an Outcome?

Learning How to Play a Complex Social Game With Machine Learning

Discovering the Power of MinMax Ideas