APTPUO Winter 2027- MIA5150 A- (ONLINE)

University of Ottawa•Ottawa, ON

9d•Remote

About The Position

This course explores the principles, techniques, and applications of Generative AI to drive innovation, improve operational efficiency, and support data-driven decision-making across modern enterprises. Delve into key techniques, including AI integration, AutoML, workflow automation, prompt engineering, and human-AI interaction approaches for designing and implementing practical AI solutions. The course also examines AI strategy, governance frameworks, risk management, and responsible AI practices to ensure ethical and effective deployment. Learn to work with pre-trained and custom AI models to enhance productivity and business workflows. Hands-on activities using no-code and low-code tools to build prototypes, dashboards, automated workflows, reports, and AI-driven solutions.

Requirements

Master’s or PhD degree, with a specialization or demonstrated academic focus in Artificial Intelligence, Machine Learning, NLP, or closely related areas.
3-5 years of industry experience applying Generative AI technologies to business innovation, digital transformation, process improvement, or AI-enabled business solutions.
Expertise in Generative AI concepts, tools, and applications, including prompt engineering, AI assistants, workflow automation, AI integration, and human-AI collaboration.
Experience in AI strategy, governance, risk management, responsible AI practices, and enterprise AI adoption.
Hands-on experience using no-code, low-code, or AI-enabled development platforms to create workflows, dashboards, or business solutions.

Nice To Haves

Relevant industry certifications or professional experience in AI, cloud platforms, analytics, or digital transformation.
Previous teaching experience in AI or related fields, and/or experience designing and delivering professional or technical training in AI-related topics.

Responsibilities

Teach the course 'Topics in Interdisciplinary Artificial Intelligence' (MIA5150 Section c).
Develop and deliver course content covering Generative AI principles, techniques, and applications.
Incorporate hands-on activities using no-code and low-code tools for building prototypes, dashboards, automated workflows, reports, and AI-driven solutions.
Address AI strategy, governance frameworks, risk management, and responsible AI practices.
Facilitate learning with pre-trained and custom AI models.
Engage students in prompt engineering, AI integration, AutoML, workflow automation, and human-AI interaction.