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

Delivery Options

Private Group Training

Our identity is rooted in delivering exactly what our clients need.

  • Pre-course call with your trainer
  • Customisation of the learning experience to achieve your goals -
    • Bespoke outlines
    • Practical hands-on exercises containing data / scenarios recognisable to the learners
  • Training scheduled on a date of your choice
  • Delivered online, onsite/classroom or hybrid by experts sharing real world experience

Private Group Prices RRP from £3800 online delivery, based on a group of 2 delegates, £1200 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.

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Public Training

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Provisional Upcoming Courses (Contact Us For More Information)

Federated Learning for Secure AI Collaboration

2025-05-06 09:30
14 hours
Edinburgh

Federated Learning for Secure AI Collaboration

2025-05-20 09:30
14 hours
Cambridge

Federated Learning for Secure AI Collaboration

2025-06-03 09:30
14 hours
Oxford

Federated Learning for Secure AI Collaboration

2025-06-17 09:30
14 hours
Plymouth

Federated Learning for Secure AI Collaboration

2025-07-01 09:30
14 hours
Swansea

Federated Learning for Secure AI Collaboration

2025-07-15 09:30
14 hours
Bradford

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Federated Learning
Federated Learning