Curriculum for Game Programming Degree

Students learn the history and basics of computing, as well as the fundamentals of programming. General topics include: the history of computing, number systems and classical computing, Boolean logic, algorithm design and implementation, and modern computer organization. Programming topics include: memory and variables, mathematical operations, basic input and output, decision making, repetitions, functions, and arrays.

This course builds on the content from Introduction to Programming. Students study the Object Oriented Programming (OOP) Paradigm with topics such as objects, classes, encapsulation, abstraction, modularity, inheritance, and polymorphism. Students examine and use structures such as arrays, structs, classes, and linked lists to model complex information. Pointers and dynamic memory allocation are covered, as well as principles such as overloading and overriding. Students work to solve problems by selecting implementation options from competing alternatives.

Students compare and contrast a variety of data structures. Students compare algorithms for tasks such as searching and sorting, while articulating efficiency in terms of time complexity. Students implement data structures and algorithms to support solution designs.

This course takes a shaders-first dive into modern computer graphics programming. Students are introduced to vertex and fragment shaders, 2D and 3D coordinate spaces, drawing primitives, lighting and shading, data flow and manipulation, and modern GPU capabilities. Linear algebra and 3D math concepts will be refreshed and/or introduced for applicable topics.

Students will learn the concepts, techniques, and structures of discrete mathematics necessary for the software engineer, including logic, sets, functions, relations, Boolean algebra, and combinatorics. The course also introduces the concept of mathematical proof.

Matrices, Vectors, and 3D Math introduces students to applied Linear Algebra, including systems of linear equations, matrix and vector operations, change of basis, and transformations. Additionally, it presents a variety of topics from 3D mathematics including vector mathematics, lines and planes, vector-valued functions, velocity, acceleration, and surfaces. Students will write computer programs and use mathematical software to explore all aspects of the topic.

Game designers need an essential skill set that allows them to realize their concepts through working prototypes. In Game Technology I students learn how to develop and manipulate game mechanics and environments through visual and traditional scripting tools. This class is the first in a series that supports skills needed for level editing and design, prototyping, and working in game engines.

Game Architecture explores components and subsystems of electronic games and their associated architectures. Topics include game state representation, time management, the main game loop and game subsystems. Game design and planning from first concept to start of development are explored in detail. In addition to game architecture, we will also look into the issues of game design, team building, and management. The focus will be on those implementations that work well, and will include situations to avoid and how to fix errors.

Students will gain a profound appreciation for the graphics pipeline by implementing 3D rendering tools, post-processing algorithms and industry-standard shaders. The animation side introduces mesh manipulation techniques, such as morphing and skeletal animation, using modern GPU-based algorithms. Linear algebra and 3D math concepts will be refreshed and/or introduced for applicable topics.

This course provides a technical introduction to the core concepts of artificial intelligence (AI). Students will be introduced to the history of AI, agents (agent architecture and multi-agent behavior), search (search space, uninformed and informed search, constraint satisfaction, game playing), knowledge representation (logical encoding of domain knowledge, logical reasoning systems), planning (search over plan space, partial-order planning, practical planning), uncertainty and probability, learning (inductive learning, linear separators, decision trees, boosting, reinforcement learning), and perception and cognition (natural language, machine vision, robotics).

Students learn the theory and practical application of techniques used in games to simulate real-world physical interactions. Implementation of 2D and 3D algorithms to effect movement, particle systems, collision detection, gravitational forces, kinematics, and spring systems are covered. Implementations trade-offs of efficiency for accuracy are adapted for real time games.