Ideal for teams that…
Hands-on AI and data analytics workshops — built around your team's real cases.
AI fundamentals – Understand the differences between AI, ML, and DL, and how these technologies work in medicine
AI applications in healthcare – Learn how AI supports diagnostics, medical image analysis, disease risk prediction, and clinical decision support
Challenges with medical data – Learn how to prepare data for AI analysis, identify errors, and handle sensitive data properly
Ethical and legal aspects – Understand the challenges AI faces in healthcare, including accountability, legal regulations, and privacy issues
What we actually do
We tailor the detailed agenda of this training to your team. Write to us — we'll send a sample agenda and adapt it to your stack.
The AI in Medicine – Fundamentals course is an intensive two-day training that combines theory with practice, focusing on real applications of artificial intelligence in healthcare. Participants will learn the basics of AI, machine learning (ML), and deep learning (DL), understand how to use ready-made tools without the need for programming, and discover how to analyze medical data, diagnostic images, and predict clinical events. The training introduces participants to the world of AI in a medical context. It covers an overview of AI applications in diagnostics, medical image analysis, disease prediction, and clinical decision support.
From brief to retro in 30 days.
Brief & diagnosis
A call with the team lead + a short survey for participants. We define goals, gap and context.
Program customization
We adapt modules, case studies and code examples to your stack. Approval in 5 days.
Workshop
Trainer-led sessions, hands-on, code review. Mentor available between sessions too.
Retro + report
Outcome report for the team and lead. 30 days of consulting included.
Send a brief. We'll reply within 1 day.
After a short brief we'll prepare a program and a quote. No obligations — it's just a starting point.
Thank you!
We'll get back to you within 1 business day.
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