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AI

AI in Medicine and the AI Act – Safe AI Systems in Healthcare

Hands-on AI and data analytics workshops — built around your team's real cases.

Duration
16h · 2 days
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Who it's for

Ideal for teams that…

1 AI/ML developers and engineers in the healthcare sector
2 AI system architects
3 Compliance and regulatory specialists
4 Product owners responsible for developing AI-based medical systems
5 QA/Validation teams in MedTech companies
Outcomes after the program

Hands-on AI and data analytics workshops — built around your team's real cases.

✓

AI Act classification of systems – Understand whether your system is “high-risk,” “general purpose,” or “prohibited”

✓

Model safeguards and oversight – Learn how to design AI models resilient to errors, manipulation, and data breaches

✓

Conformity assessment and technical documentation – Master the structure of Technical Documentation and how to build it step by step

✓

Monitoring and continuous improvement – Learn to implement logging, error handling, validation, and retraining processes in line with the AI Act

Requirements

What you should know before we start

  • Good understanding of AI and ML fundamentals
  • Practical knowledge of Python or another ML programming language
  • General awareness of MDR and GDPR regulations
Program · 9 modules

What we actually do

M01
Introduction to the AI Act
  • · Structure and objectives of the AI Act
  • · Types of AI systems and their classification
  • · Relationship between the AI Act, MDR, GDPR, and ISO standards
M02
Risk Classification and Manufacturer Obligations
  • · High-risk vs. other AI systems
  • · Requirements for “high-risk AI” systems
  • · Roles of provider, user, importer, and distributor
M03
Securing AI Models in Healthcare
  • · Protection against errors and adversarial attacks
  • · Data source verification and model version control
  • · Transparent vs. black-box models (in the context of explainability obligations)
M04
AI Technical Documentation
  • · Documentation requirements under the AI Act
  • · How to prepare: model cards, data sheets, algorithm impact assessments
  • · Step-by-step creation of Technical Documentation
M05
Workshop: Classification & Evaluation of AI Systems
  • · Hands-on case studies (e.g., ECG evaluation model, medical triage chatbot)
  • · Defining risk level, documentation requirements, and conformity assessment process
M06
Conformity Assessment and Audits
  • · Overview of notification procedures
  • · Self-assessment vs. third-party assessment
  • · Role of the notified body and declaration of conformity
M07
Validation and Testing of AI Models in Medical Environments
  • · Pre-clinical and clinical testing
  • · Model metric validation vs. clinical validation
  • · Test cases, validation plans, traceability matrices
M08
Post-deployment Monitoring and Oversight Systems
  • · Logging, alerts, and error handling
  • · Documenting corrective actions and updates
  • · Retraining and lifecycle management
M09
Ethics and Accountability under the AI Act
  • · Transparency, human oversight, interpretability
  • · Implementing “human-in-the-loop” principles
  • · Examples of violations and legal consequences
Every module is adapted to your stack and context. The above is a starting point — not a fixed agenda.
How we work

From brief to retro in 30 days.

01

Brief & diagnosis

A call with the team lead + a short survey for participants. We define goals, gap and context.

02

Program customization

We adapt modules, case studies and code examples to your stack. Approval in 5 days.

03

Workshop

Trainer-led sessions, hands-on, code review. Mentor available between sessions too.

04

Retro + report

Outcome report for the team and lead. 30 days of consulting included.

Inquiry

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.

✓Quote within 48h of the brief
✓First session within 30 days
✓Pilot before the full decision
✓VAT invoice, payment in instalments possible

How we handle your data

We process your business data (name, work e-mail, phone number, company, job title) in order to handle your corporate training inquiry and prepare an offer. The data controller is infoShare Academy Sp. z o.o., Al. Grunwaldzka 472B, 80-309 Gdańsk. Providing the data is voluntary but necessary to receive a response. You have the right to access, rectify, erase or restrict the processing of your data and to object to it. Full information is available in our data processing notice.

Optional marketing consents

The controller of your personal data is infoShare Academy sp. z o.o. The rules for processing personal data are set out in the Privacy Policy and the Data Processing Notice.

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