Über diesen Kurs

You should take this course if you have an interest in machine learning and the desire to engage with it from a theoretical perspective. Through a combination of classic papers and more recent work, you will explore automated decision-making from a computer-science perspective. You will examine efficient algorithms, where they exist, for single-agent and multi-agent planning as well as approaches to learning near-optimal decisions from experience. At the end of the course, you will replicate a result from a published paper in reinforcement learning.

Kursgebühren
Kostenlos
Niveau
Profis
Vorteile

Rich Learning Content

Interactive Quizzes

Taught by Industry Pros

Self-Paced Learning

Student Support Community

Begib' dich auf den Weg des Erfolgs

Dieser kostenlose Kurs ist der erste Schritt auf dem Weg zu einer neuen Karriere mit dem Machine Learning Engineer Programm.

Kostenlose Kurse

Bestärkendes Lernen

mit Georgia Institute of Technology

Erweitere deine Fähigkeiten und Karriere durch innovatives und unabhängiges Lernen.

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Tutoren

Charles Isbell
Charles Isbell

Tutor

Michael Littman
Michael Littman

Tutor

Chris Pryby
Chris Pryby

Tutor

Voraussetzungen

Before taking this course, you should have taken a graduate-level machine-learning course and should have had some exposure to reinforcement learning from a previous course or seminar in computer science (students who have completed CS 7641 will be well prepared for this course).

Additionally, you will be programming extensively in Java during this course. If you are not familiar with Java, we recommend you review Udacity's Intro to Java Programming course materials to get up to speed beforehand.

Detaillierte technische Voraussetzungen

Was spricht für diesen Kurs?

This course will prepare you to participate in the reinforcement learning research community. You will also have the opportunity to learn from two of the foremost experts in this field of research, Profs. Charles Isbell and Michael Littman.

Was bekomme ich?
Instructor videos Learn by doing exercises Taught by industry professionals