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Course Outline

Introduction to Federated Learning

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

Core Components of Federated Learning

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

Data Privacy and Security in Federated Learning

  • Data minimisation 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 using 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 modelling
  • Fraud detection and risk analysis with federated approaches
  • Case studies in secure data collaboration within financial institutions

Challenges and the 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

  • A basic understanding of machine learning concepts
  • Familiarity with the fundamentals of data privacy and security

Audience

  • Data scientists and AI researchers focused on privacy-preserving machine learning
  • Healthcare and finance professionals who handle sensitive data
  • IT and compliance managers interested in secure AI collaboration methods
 14 Hours

Number of participants


Price per participant

Open Training Courses require 5+ participants.

Provisional Upcoming Courses (Require 5+ participants)

Federated Learning for Secure AI Collaboration

2026-05-20 09:30
14 hours
Te Pou Toetoe Linwood
6560 NZD (Online)
6560 NZD (Classroom)

Federated Learning for Secure AI Collaboration

2026-06-03 09:30
14 hours
Auckland, ANZ Centre
6560 NZD (Online)
14560 NZD (Classroom)

Federated Learning for Secure AI Collaboration

2026-06-17 09:30
14 hours
Wellington, Plimmer Towers
6560 NZD (Online)
14000 NZD (Classroom)

Federated Learning for Secure AI Collaboration

2026-07-01 09:30
14 hours
Te Pou Toetoe Linwood
6560 NZD (Online)
6560 NZD (Classroom)

Federated Learning for Secure AI Collaboration

2026-07-15 09:30
14 hours
Auckland, ANZ Centre
6560 NZD (Online)
14560 NZD (Classroom)

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