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Course Outline

Introduction to Federated Learning

  • Defining federated learning and its differences from centralized learning
  • Benefits of federated learning for secure AI collaboration
  • Applications in sectors requiring sensitive data handling

Key Elements of Federated Learning

  • Federated data, client roles, and model aggregation
  • Communication protocols and update mechanisms
  • Addressing heterogeneity in federated settings

Data Privacy and Security in Federated Learning

  • Principles of data minimization and privacy
  • Methods for securing model updates (e.g., differential privacy)
  • Ensuring compliance with data protection regulations

Implementing Federated Learning

  • Establishing a federated learning environment
  • Distributed model training using federated frameworks
  • Considerations for performance and accuracy

Federated Learning in Healthcare

  • Secure data sharing and privacy issues in healthcare
  • Collaborative AI for medical research and diagnosis
  • Case studies: federated learning in medical imaging and diagnosis

Federated Learning in Finance

  • Leveraging federated learning for secure financial modeling
  • Fraud detection and risk analysis using federated approaches
  • Case studies of secure data collaboration in financial institutions

Challenges and Future of Federated Learning

  • Technical and operational hurdles in federated learning
  • Emerging trends and advancements in federated AI
  • Exploring opportunities for federated learning across various industries

Summary and Next Steps

Requirements

  • Foundational understanding of machine learning concepts
  • Familiarity with the basics of data privacy and security

Audience

  • Data scientists and AI researchers specializing in privacy-preserving machine learning
  • Professionals in healthcare and finance dealing with sensitive data
  • IT and compliance managers keen on secure AI collaboration methods
 14 Hours

Custom Corporate Training

Training solutions designed exclusively for businesses.

  • Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
  • Flexible Schedule: Dates and times adapted to your team's agenda.
  • Format: Online (live), In-company (at your offices), or Hybrid.
Investment

Price per private group, online live training, starting from 3200 € + VAT*

Contact us for an exact quote and to hear our latest promotions

(*The final price may vary depending on the technical specialization of the course, the level of customization, the method of delivery and the number of learners)

Need help picking the right course?
opleidingen@nobleprog.com or +31 208 080 666

Provisional Upcoming Courses (Contact Us For More Information)

Federated Learning for Secure AI Collaboration

2026-08-31 09:30
14 hours
Zwolle

Federated Learning for Secure AI Collaboration

2026-09-14 09:30
14 hours
Tilburg

Federated Learning for Secure AI Collaboration

2026-09-28 09:30
14 hours
Eindhoven

Federated Learning for Secure AI Collaboration

2026-10-12 09:30
14 hours
Maastricht

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