AI Is Changing The World. Be Part Of The Change.

Become part of a changing world and discover Nipissing University’s Post-Baccalaureate Diploma (PBD) in Artificial Intelligence and Machine Learning Application.

This two-year program is designed for international students who already have an undergraduate degree in computer science or a related discipline and who are ready to explore advanced, state-of-the-art knowledge of new computational techniques and paradigms, including machine learning, artificial intelligence, advance visualization and graphics, and data science. 

This program will enhance your knowledge of emerging and increasingly important interdisciplinary professions in areas such as data analytics, “Big Data”, high performance computing and parallel computing, game artificial intelligence and other technologies, geomatics information systems, and computational tools and techniques in the humanities. 

Digital Ethics

PHIL 2816

Examine ethical issues that have emerged in relation to digital technologies, such as: the meaning and value of privacy; the right to be forgotten; the power of search engines; the use of Big Data and Big Data analytics; equality and the “digital divide”; censorship and free speech online; the ethics of the online self, including questions of reification, catfishing; polarization and the internet; artificial intelligence; and the ethics of hacking and hacktivism.

Human-Computer Interaction

COSC 3106

Explore the interactions between people and computers; learn about tradeoffs in human-computer interaction (HCI) design and evaluate alternative solutions. Topics include usability and affordances, direct manipulation, systematic design methods, user conceptual models and interface metaphors, human cognitive models, physical ergonomics, information and interactivity structures, design tools and environments, user-centered design, and universal design.

Machine Learning

COSC 3006

Learn about the main machine learning technologies and tools used in data science and data analytics, including clustering, decision trees, recurrent and convolutional neural networks, support vector machines, Bayesian learning, reinforcement learning. Students explore and apply methods from computational intelligence through a variety of applications and solutions to problems in data science and data analytics.

Computer Graphics

COSC 3207

This course introduces the principles and methods of computer graphics and their applications. Topics include: PC video cards and storage; display devices; representing objects; raster algorithms for lines, circles and region filling; 2-D and 3-D graphics software; object transformations, fractal construction and animation software.