Computer Science

This course covers how JavaScript works and how to use JavaScript to improve the richness of web interactions with simple, life-like examples. With hands-on examples, students will be able to understand from the ground up. The course has a series of sections and recorded segments, so learning is more flexible and efficient.

This course covers the fundamentals of generative computer graphics: homogeneous coordinates, rendering pipeline, and global illumination. Topics include input and output devices, transformations, raster algorithms, visibility, color, local illumination, global illumination, and textures.

This course covers the core ability of computer related specialty programming and cultivates computing thinking and engineering literacy to solve complex problems using programming methods. The course examines the basic concepts and principles of programming, and the basic grammar and structure of C language. Students use the C programming platform for programming and debugging, and C language to design and implement a program of the scale of a text interface life game.

This course is a broad introduction to computer vision for data science. Topics include various low-level image processing methods and high-level vision tasks like image classification and object detection, with modern approaches based on deep learning. Student learn computer vision algorithms and implement them in python. Students should be proficient in python programming with numpy for assignments. Other python libraries, such as opencv (cv2), scipy, and matplotlib will be used, but students do not have to be proficient with them.

This course introduces the following topics: operating-system structure, processes, threads, CPU scheduling, process synchronization, deadlocks, main memory, virtual memory, and file-system interface. Students attend two UNIX tutorials. Prerequisite: a course in computer organization and structure.

This course is designed for beginners with some programming experience; those who have some knowledge of Python but are ready to utilize their skills for data analysis and Machine Learning, or experienced developers looking to transition to Data Science. Enrollees must have taken courses related to or on Python programming, or must have an understanding of Python.

This course offers an introduction to videogame design. Topics include: the process-- from concept to implementation; specification and creation of documentation; mechanics; interfaces; interactive storytelling; controls; balance; 2D game design; 3D game design; design of space and location of resources; controls and navigation; multiplayer game design.