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Program Requirements

The 15-credit Graduate Certificate in Data Analysis for Complex Systems is designed to equip learners who do not necessarily have a technical background with the fundamentals of complex systems. The program focusses on applying data analysis techniques to better understand different phenomena in fields such as financial technology, organizational management, or digital marketing.

Required Courses (9 credits)

• CCCS 610 Digital Thinking for Data Analysis (3 credits)

  Offered by: Technology & Innovation (School of Continuing Studies)

  Overview

  Computer Science (CCE) : Examination of programmable tools for data analysis. Application methods to implement fundamental algorithms making use of data structures.

  Terms: Fall 2023

  Instructors: Schaeffer, Satu Elisa (Fall)

• CCCS 620 Data Analysis and Modelling (3 credits)

  Offered by: Technology & Innovation (School of Continuing Studies)

  Administered by: Graduate Studies

  Overview

  Computer Science (CCE) : Analysis of fundamental concepts and techniques for data analysis and modelling; basic mathematical and computational concepts needed for data analysis. Application of programmable tools to real-world examples.

  Terms: Fall 2023

  Instructors: Schaeffer, Satu Elisa (Fall)

  • Not open to students who have taken CCS2 505.

• CCCS 630 Complex Systems (3 credits)

  Offered by: Technology & Innovation (School of Continuing Studies)

  Overview

  Computer Science (CCE) : Tools and techniques for modelling and simulating diverse complex systems; network analysis with applications in social, biological, and infrastructure networks; and chaotic systems.

  Terms: Fall 2023

  Instructors: Gutierrez Lopez, Alejandro (Fall)

Complementary Courses (6 credits)

6 credits from:

• CCCS 670 Information Visualization (3 credits)

  Offered by: Technology & Innovation (School of Continuing Studies)

  Overview

  Computer Science (CCE) : 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: This course is not scheduled for the 2023-2024 academic year.

  Instructors: There are no professors associated with this course for the 2023-2024 academic year.

• CCCS 680 Scalable Data Analysis (3 credits)

  Offered by: Technology & Innovation (School of Continuing Studies)

  Overview

  Computer Science (CCE) : 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: Summer 2024

  Instructors: Havas, Michael (Summer)

  • Not open to students who have taken CMIS 550.

• CCCS 690 Applied Computational Research (3 credits)

  Offered by: Technology & Innovation (School of Continuing Studies)

  Overview

  Computer Science (CCE) : 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.

  Terms: This course is not scheduled for the 2023-2024 academic year.

  Instructors: There are no professors associated with this course for the 2023-2024 academic year.

  • Prerequisites: CCCS 630 or CCCS 640

Or another 600-level course offered by the School of Continuing Studies and approved by the academic unit.