Dans le programme du Certificat d’études supérieures en prise de décisions fondée sur des données (15 crédits), les étudiant(e)s acquièrent des notions de base en intelligence informatique. Le programme met l’accent sur les rôles de leadership dans des organisations de plus en plus numériques évoluant dans les nombreux domaines qui intègrent les données à leurs décisions, notamment les soins de santé numériques, l’entretien d’infrastructures essentielles et la gestion de l’approvisionnement. Le programme est offert enligne.
Required Courses (9 credits)
Course List
Course
Title
Credits
CCCS 640
Applied Decision Science.
3
Applied Decision Science.
Terms offered: this course is not currently offered.
Analysis of concepts, tools, and techniques provided by mathematical and computational
sciences for decision making in its diverse formats. Examination of decision science
techniques and their applicability.
Terms offered: this course is not currently offered.
Analysis of techniques provided by statistics and computational sciences for machine learning and data science. Examination of real-world applications.
Terms offered: this course is not currently offered.
Analysis of tools provided by mathematical and computational sciences for artificial intelligence as well as an examination of the numerous contexts in which computational intelligence can be applied.
Examination of the application of computational and mathematical concepts, tools, and techniques to visualize quantitative multi-dimensional information. Qualitative information in static, animated, and interactive digital formats. Guidelines and best practices from cognitive psychology, UX, and graphic design, including dashboard tools and storytelling methods.
Terms offered: this course is not currently offered.
Concepts, tools, and metrics related to scaling up data analysis to handle massive amounts of data. Examination of methods for enabling technologies and applications such as big data and cloud computing.
Terms offered: this course is not currently offered.
Analysis of a real-world case study of choice. Examination of version-controlled repositories and project management tools for tracking the tasks. Identification,
formulation, and application of data-driven projects in areas of interest.
