Recent years have seen a dramatic rise in the use of algorithms for solving problems involving strategic decision makers. Deployed algorithms now assist in a variety of economic interactions: assigning medical residents to schools, allocating students to courses, allocating security resources in airports, allocating computational resources and dividing rent.

Recent years have seen a dramatic rise in the use of algorithms for solving problems involving strategic decision makers. Deployed algorithms now assist in a variety of economic interactions: assigning medical residents to schools, allocating students to courses, allocating security resources in airports, allocating computational resources and dividing rent.

This course provides an overview of numerical optimization methods and covers how to implement them in Python. We will discuss common algorithms ranging from gradient descent to stochastic methods, with applications ranging from image processing to neural networks. This course counts as a CS Elective (BS or BA).

This course provides an overview of numerical optimization methods and covers how to implement them in Python. We will discuss common algorithms ranging from gradient descent to stochastic methods, with applications ranging from image processing to neural networks. This course counts as a CS Elective (BS or BA).

Introduction to core machine learning models and algorithms for classification, regression, dimensionality reduction and clustering. The course will cover the mathematical foundations behind the most common machine learning algorithms, and the effective use in solving real-world applications. Requires a strong mathematical background and knowledge of one high-level programming language such as Python.

Introduction to core machine learning models and algorithms for classification, regression, dimensionality reduction and clustering. The course will cover the mathematical foundations behind the most common machine learning algorithms, and the effective use in solving real-world applications. Requires a strong mathematical background and knowledge of one high-level programming language such as Python.

Introduction to core machine learning models and algorithms for classification, regression, dimensionality reduction and clustering. The course will cover the mathematical foundations behind the most common machine learning algorithms, and the effective use in solving real-world applications. Requires a strong mathematical background and knowledge of one high-level programming language such as Python.

Game Programming introduces students to concepts of computer game development, including scene modeling, physics engines, animation, character rigging, game AI, and the basics of game UI, audio effects and networking. The course will help students build the programming skills needed to turn ideas into games. Students will work on various game programming exercises with the Unity game engine and a final game development project.

Game Programming introduces students to concepts of computer game development, including scene modeling, physics engines, animation, character rigging, game AI, and the basics of game UI, audio effects and networking. The course will help students build the programming skills needed to turn ideas into games. Students will work on various game programming exercises with the Unity game engine and a final game development project.

This course is meant for those looking for practical legal knowledge for use in Internet related endeavors. This course provides basic legal knowledge for Internet related legal issues with a focus on practical information for use by computer professionals. Topics covered are basics of the internet, basics of law and contract law, substantive laws, intellectual property law, basic ethical dealings, dealing with third parties, and policy issues.