Explain it like we are sitting around a fire.
Fireside Analytics was founded on a simple belief: data science and AI should not feel like a locked room. It should feel like sitting around a fire with friends, learning, questioning, and making sense of the world together.
For schools, organizations, public-sector teams, and communities.
Not watered down. Not overcomplicated. Clear enough for beginners, rigorous enough for serious decisions.
That has been the thread through the company’s work with learners, schools, organizations, governments, and communities that are too often left outside technical conversations.
Why Fireside Analytics exists.
Fireside Analytics started in 2015 to close the distance between powerful technical ideas and the people expected to live with them.
The name was intentional. A fireside is where hard things can be explained plainly, where questions are welcome, and where people learn through story, context, and trust. That became the company’s method for teaching data science, AI, data privacy, coding, analytics, and digital literacy.
Over the years, the work has expanded from customized curricula and online courses into high-school credit, family-friendly AI education, professional learning, public-sector programs, executive workshops, children’s books, and public conversations about responsible technology.
The throughline has not changed: bring more people into the AI conversation, especially learners and communities who have historically had less access to technical education, power, and opportunity.
Built for access Plain language · Case studies · Responsible use · Real tools · Human judgment
The company arc.
Fireside Analytics is not just a speaking platform. It is an education company that has built curriculum, courses, workshops, and learning experiences for people at very different starting points.
Custom data and AI curriculum
Fireside Analytics develops educational programming for digital literacy, coding, data analytics, data visualization, AI, data privacy, and computer programming. The work is designed for real audiences, not abstract “users.”
CurriculumOnline learning at scale
Fireside Analytics courses have reached more than 500,000 registered learners through platforms and programs connected to IBM CognitiveClass.ai, Coursera, and Fireside Analytics’ own learning ecosystem.
ScaleHigh school data science before it was obvious
Fireside Analytics built a Ministry of Education-inspected high school data science course for Grades 10 to 12, giving students a real credit pathway into data science, not just a coding club on the margins.
SchoolsAI education for everyday life
The Academy extends the work to students, families, working professionals, educators, and community leaders, with a focus on understanding, using, and living with AI responsibly.
AI LiteracyAccess as a design requirement
Fireside Analytics’ teaching model is beginner-friendly, hands-on, family-friendly, and built for people who may not see themselves in technical fields yet. The goal is confidence, not gatekeeping.
InclusionResponsible AI, not as a footnote
Every lesson connects capability to judgment: fairness, privacy, quality, accountability, and the social impact of automated systems.
GovernanceThe early bet on young learners.
Before AI literacy became a mainstream policy conversation, Fireside Analytics was already building pathways for young people to learn data science seriously, ethically, and with credit-bearing structure.
Credit-bearing data science
A Ministry-inspected high school data science course gives learners a formal pathway into data, business, statistics, and programming.
Real-world case studies
The course model uses practical scenarios so learners can solve problems with data, not just memorize tools.
AI education for everyone
The Academy now frames the work around understanding, using, and living with AI responsibly, across ages and backgrounds.
Different rooms, same mission.
Fireside Analytics’ clients and audiences include schools, colleges and universities, policymakers, executives, analysts, non-profit teams, working professionals, parents, and community learners.
The point was never to make AI sound easy. The point was to make it learnable, so more people could participate in shaping what comes next.
Fireside Analytics founding philosophyThe story in public.
These public conversations trace the evolution of the work, from data science capacity and classroom learning to AI governance, bias, and agentic systems. The YouTube videos are embedded directly so they can play on the page.
Not everyone needs to become technical. Everyone deserves technical confidence.
Begin with context
We start with the learner’s world: the classroom, policy file, community problem, business decision, or family conversation in front of them.
Make it concrete
We use stories, case studies, demos, and practical assignments so abstract ideas become usable knowledge.
Build judgment
Capability without responsibility is incomplete. Learners leave with better questions, better habits, and more confidence.
Bring more people into the AI conversation.
Based in Toronto. Working with learners, teams, schools, institutions, and communities wherever AI education is needed.