GradCert Artificial Intelligence - Architecture, Design, and Implementation
The Artificial Intelligence (AI) computing paradigm radically changes the functionality and capabilities of computer systems. This greatly increases the possibilities of what businesses can do with this exciting new technology and is causing disruption across all industry sectors. Artificial Intelligence systems can think, learn and take self-directed action in order to maximize the chance of successfully achieving a goal without having to be explicitly programmed or human intervention.This program provides students with the necessary background to become Artificial Intelligence (AI) system designers, programmers, implementers, or machine learning analysts. With a strong focus on applied skills, students learn how to design and implement supervised, unsupervised and reinforcement learning solutions for a variety of situations and solve AI challenges for a diverse set of industries. Advanced study in AI infrastructure, architecture, machine learning frameworks, reinforcement learning, neural networks, vision system, conversational AI and deep learning help students understand how to select, configure and apply the right technology tools to build the correct AI solution to solve a given challenge.
The Artificial Intelligence (AI) computing paradigm radically changes the functionality and capabilities of computer systems. This greatly increases the possibilities of what businesses can do with this exciting new technology and is causing disruption across all industry sectors. Artificial Intelligence systems can think, learn and take self-directed action in order to maximize the chance of successfully achieving a goal without having to be explicitly programmed or human intervention.This program provides students with the necessary background to become Artificial Intelligence (AI) system designers, programmers, implementers, or machine learning analysts. With a strong focus on applied skills, students learn how to design and implement supervised, unsupervised and reinforcement learning solutions for a variety of situations and solve AI challenges for a diverse set of industries. Advanced study in AI infrastructure, architecture, machine learning frameworks, reinforcement learning, neural networks, vision system, conversational AI and deep learning help students understand how to select, configure and apply the right technology tools to build the correct AI solution to solve a given challenge.
