Audience:
This course is for practitioners and front-line staff who work with data, or with the people who do, and want a practical foundation in data science and AI. It suits early-career and experienced staff in the public, non-profit and private sectors. No programming or statistics background is needed. Leaders deciding whether and how to adopt AI may prefer AI Fundamentals for Professionals.
Duration:
2 Days
Delivery:
Virtual (4 half days) or in-person (2 full days). Delivered live-virtual across Canada and the US, and in-person in Ottawa–Gatineau (National Capital Region). On-site delivery available for Government of Canada and private-sector teams.
Course description:
We work in environments saturated with information, far more than organizations have ever had to manage before. It is increasingly important for policy leaders, analysts, and program managers to understand how data science can strengthen decision‑making. Data science skills are now highly valued across government, non‑profit, and business sectors. With the right foundation, we can forecast trends, identify emerging behaviours, uncover patterns, inform policy, and extract meaning from the continuous flow of data in our workplaces.
This course gives participants a solid grounding in core data science concepts, how to apply them in daily work, and how to adopt a data‑oriented mindset.
Programming and statistical skills are not essential.
Course overview:
Data, demystified: what data and data science are; how statistics, machine learning, AI and large language models relate; framing a problem; where data comes from; bias and ethics
Getting data ready: how organizations hold data; joining data; the eight dimensions of data quality; missing data, outliers and binning; stopping errors at the source
Finding meaning: describing and exploring data; how charts mislead; correlation, causation and regression; probability and base rates; simulation; choosing the simplest method that works
From analysis to AI: how machines learn and find patterns; generative AI and agents; people in the loop; model drift; how real projects run; the risk of acting and of not acting
By the end of this course, participants will be able to:
Interactive Data Tools for This Course
These tools are free to use anytime — browse them before the course as a preview, work through them live during a session, or come back to them afterward as a refresher.