Field Notes Daily — since 2021

Teaching AI as a practical discipline, not a trend

Field Notes Daily started from a straightforward observation: most AI education was either too shallow to be useful or too abstract to be applied. We built a different kind of platform.

Our masterclasses are designed around real workflows, concrete tools, and the kind of decision-making that professionals actually face. Each programme is built by practitioners who work with AI systems daily — not by generalists summarising what they've read. Instructors bring specific domain knowledge, whether that's training data pipelines, prompt engineering for production systems, or evaluating model outputs in regulated environments.

The format is deliberately focused. Short enough to complete, dense enough to matter. Participants work through structured sequences that build understanding progressively, with each module connecting to the next rather than standing alone.

Curriculum depth: Each course maps to a specific skill gap, not a general topic area.
Instructor standard: All instructors are vetted on active professional practice, not credentials alone.
Global access: Content is available asynchronously with no regional restrictions on enrolment.
Honest scope: We describe what participants will be able to do, not what they might become.

38+ Structured masterclass modules across AI fundamentals

14 Countries with active enrolled participants

6 Domain specialists contributing to current curriculum

4 Programme tracks from foundations to applied systems

AI masterclass session in progress, instructor demonstrating a machine learning workflow

The people behind the platform

Instructors and builders

Tobias Vreeland

Lead AI Curriculum Designer

Tobias spent eight years building data products for logistics and supply chain companies before moving into education. He designs the structural backbone of each programme — sequencing concepts so that each builds on the last without unnecessary repetition. His background in applied statistics shapes how the curriculum handles uncertainty and model evaluation.

Mirela Okonkwo

Senior Instructor, Applied ML

Mirela leads instruction across the applied machine learning track. She has worked on classification systems in healthcare administration and currently consults on responsible AI deployment for mid-sized organisations. Her sessions focus on the gap between a working model and a deployable one — a distinction that most introductory courses skip entirely.

Applied machine learning workshop environment showing a participant working through a model evaluation exercise

Applied ML track — model evaluation workshop

Dagmar Fleischhauer

Programme Director

Dagmar oversees the overall programme direction and instructor onboarding process. She came from corporate learning and development, where she spent six years designing technical upskilling programmes for engineering teams. She is responsible for ensuring that each course meets the platform's standard for specificity — that every lesson teaches something a participant can act on within the same week.

Onboarding: All new instructors complete a structured review of existing modules before contributing.
Feedback loop: Participant responses are reviewed quarterly to update module content.