This course is designed for:
CPAs and financial professionals who want to enhance their data literacy and help their organizations gain a competitive advantage with valuable predictive analytic skills:
- Managers or Directors interested in career advancement and gaining a deeper understanding of data analytics.
- Executives who want to enhance their financial expertise, keeping up to date with the changing needs in data, analytics and insights.
Learn how to contribute to the effective use of predictive analytics in your organization
The University of Waterloo and CPA Ontario have collaborated to deliver a professional development certificate program tailored for CPAs who want to advance their careers with analytics-driven decision making.
This program allows CPAs to work comfortably and confidently with predictive analytics. The program’s modules combine a broad understanding of industry-standard data analytics process with a focus on forecasting models, a type of predictive analytics particularly relevant for accounting and finance applications.
Through exposure to a variety of forecasting models, participants learn when and how existing CPA competencies add value to a predictive analytics project. Successful completion of the program is determined by each participant’s engagement in a financial forecasting group project.
This course will strengthen your ability to:
- identify when and how to leverage non-financial data in your forecasting models
- assess the accuracy, consistency, timeliness and completeness of large data sets
- communicate with colleagues who bring deep statistical knowledge to data analytics projects
This course is delivered virtually in four modules and includes 20 hours of learning. Participants will be expected to start the self-paced module on their own and come prepared to the first instructor-led session. Expect live and interactive instructor-led sessions, group project work, peer review groups with feedback, presentation opportunities, debrief sessions and self-paced learning activities.