Course Outline

Introduction to Federated Learning

  • What is federated learning, and how does it differ from centralized learning?
  • Advantages of federated learning for secure AI collaboration
  • Use cases and applications in sensitive data sectors

Core Components of Federated Learning

  • Federated data, clients, and model aggregation
  • Communication protocols and updates
  • Handling heterogeneity in federated environments

Data Privacy and Security in Federated Learning

  • Data minimization and privacy principles
  • Techniques for securing model updates (e.g., differential privacy)
  • Federated learning in compliance with data protection regulations

Implementing Federated Learning

  • Setting up a federated learning environment
  • Distributed model training with federated frameworks
  • Performance and accuracy considerations

Federated Learning in Healthcare

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

Federated Learning in Finance

  • Using federated learning for secure financial modeling
  • Fraud detection and risk analysis with federated approaches
  • Case studies in secure data collaboration within financial institutions

Challenges and Future of Federated Learning

  • Technical and operational challenges in federated learning
  • Future trends and advancements in federated AI
  • Exploring opportunities for federated learning across industries

Summary and Next Steps

Requirements

  • Basic understanding of machine learning concepts
  • Familiarity with data privacy and security fundamentals

Audience

  • Data scientists and AI researchers focused on privacy-preserving machine learning
  • Healthcare and finance professionals handling sensitive data
  • IT and compliance managers interested in 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)

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Upcoming Courses

Federated Learning for Secure AI Collaboration

2026-01-20 09:30
14 hours
Bilbao

Federated Learning for Secure AI Collaboration

2026-02-03 09:30
14 hours
Madrid - Chamartín Business Area

Federated Learning for Secure AI Collaboration

2026-02-17 09:30
14 hours
Malaga City Center

Federated Learning for Secure AI Collaboration

2026-03-03 09:30
14 hours
Barcelona City

Federated Learning for Secure AI Collaboration

2026-03-17 09:30
14 hours
Valencian Community

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