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 Duration 21 hours

Course Outline

Introduction to Quantum-AI Integration

  • The rationale for hybrid quantum-classical intelligence.
  • Key opportunities and existing technological barriers.
  • Positioning Google Willow within the broader quantum-AI ecosystem.

Google Willow Architecture and Capabilities

  • System overview and toolchain structure.
  • Supported quantum operations and feature set.
  • APIs designed for advanced experimentation.

Hybrid Quantum-Classical Models

  • Strategies for partitioning tasks between quantum and classical components.
  • Data encoding techniques for quantum-enhanced learning.
  • Workflows for state preparation and measurement.

Quantum Machine Learning Algorithms

  • Variational quantum circuits applied to AI tasks.
  • Quantum kernels and feature mapping.
  • Optimization loops tailored for hybrid models.

Building Quantum-AI Pipelines with Willow

  • End-to-end development of hybrid models.
  • Integrating Willow with TensorFlow Quantum.
  • Testing and validation of quantum-AI prototypes.

Performance Optimization and Resource Management

  • Developing AI models with noise awareness.
  • Managing compute constraints within hybrid systems.
  • Benchmarking quantum-AI performance metrics.

Applications and Emerging Use Cases

  • Quantum-enhanced data analytics.
  • AI-driven optimization accelerated by quantum processing.
  • Potential for cross-industry adoption.

Future Trends in Quantum-AI Convergence

  • Roadmaps for large-scale quantum-AI systems.
  • Architectural advancements and hardware evolution.
  • Research directions defining the quantum-AI frontier.

Summary and Next Steps

Requirements

  • A foundational understanding of quantum computing principles.
  • Practical experience with machine learning frameworks.
  • Familiarity with hybrid quantum-classical workflows.

Audience

  • AI engineers
  • Machine learning specialists
  • Quantum computing researchers

Number of participants


Price per participant

Provisional Upcoming Courses (Require 5+ participants)

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