Introduction to Quantum AI Training Course

This instructor-led, live training in Australia (online or onsite) is aimed at advanced-level professionals who wish to leverage quantum computing to enhance AI capabilities.

By the end of this training, participants will be able to:

• Understand hybrid AI-quantum systems and their potential applications.
• Implement quantum machine learning algorithms.
• Optimise AI models using quantum computing resources.
• Overcome challenges in scaling and integrating quantum AI systems.

Google Willow is a cloud-accessible quantum computing platform designed to support experimentation, algorithm development, and applied quantum research.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to explore practical industry use cases of quantum computing using Google Willow.

Upon completing this training, participants will gain the ability to:

• Navigate the Google Willow environment effectively.
• Evaluate real-world quantum computing applications across industries.
• Run and interpret quantum algorithms for business and research contexts.
• Assess the feasibility and impact of emerging quantum solutions.

Format of the Course

• Expert-led presentations and applied discussions.
• Hands-on exercises incorporating quantum tools and workflows.
• Real-time experimentation within the Google Willow environment.

Course Customization Options

• Customized versions of this course can be arranged to support specific industry requirements or research objectives.

Google Willow is a cloud-based quantum computing platform that empowers developers and researchers to design, test, and execute quantum algorithms.

This instructor-led, live training (available online or onsite) targets intermediate-level professionals keen on building quantum algorithms and running them on Google Willow.

By the end of this training, participants will be equipped to:

• Create and structure quantum circuits for experimental and applied use.
• Deploy quantum algorithms using Google Willow’s interface and APIs.
• Evaluate algorithm behaviour and optimize quantum workflows.
• Integrate quantum techniques into broader computational pipelines.

Format of the Course

• Guided presentations with technical demonstrations.
• Practical assignments and coding exercises.
• Hands-on experimentation in a live Google Willow environment.

Course Customization Options

• Custom-tailored training programs for specialized quantum algorithm research are available upon request.

In this instructor-led, live training in Australia, participants will learn the fundamentals of quantum computing as they step through the development of algorithms targeting quantum computers.

By the end of this training, participants will be able to:

• Set up the necessary development environment to start creating quantum circuits.
• Control gate behaviour using the gate's native counterpart.
• Improve on quibit inaccuracies using Cirq.
• Write and execute a quantum circuit to run against a NISQ based quantum computer simulator.

This instructor-led, live training in Australia (online or onsite) is designed for beginners keen on grasping the fundamentals of quantum computing, investigating the capabilities of Google Willow, and learning the basics of quantum programming.

Upon completing this training, participants will be able to:

• Grasp the core principles of quantum computing and qubits.
• Explore Google Willow and its advancements in quantum error correction.
• Write and execute fundamental quantum programs using Qiskit.
• Identify practical, real-world applications of quantum computing.

ProjectQ is an open-source quantum computing software framework written in Python. It allows users to define quantum circuits and compile them for various backend quantum hardware platforms or simulators. The framework features advanced optimization capabilities, compiler engines, and flexible back-end targeting.

This instructor-led live training, available online or on-site, is designed for intermediate developers who wish to understand and apply ProjectQ for practical quantum programming and back-end translation.

Upon completion of this training, participants will be able to:

• Explain the architecture and purpose of ProjectQ.
• Write quantum circuits using ProjectQ’s Python API.
• Utilise ProjectQ’s compiler engines and optimisation features.
• Target different quantum back-ends or simulators using ProjectQ.

Course Format

• Interactive lectures and group discussions.
• Hands-on coding exercises and circuit construction.
• Live lab implementation targeting simulator or hardware back-ends.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

Quantum cryptography represents an emerging security paradigm that leverages the principles of quantum mechanics.

This instructor-led, live training (available online or onsite) is designed for intermediate-level specialists aiming to design secure systems using quantum-resistant and quantum-enhanced techniques on Google Willow.

Upon completing this training, participants will be able to:

• Build quantum-safe communication workflows using Google Willow.
• Evaluate quantum threats to classical security protocols.
• Apply quantum key distribution concepts to modern infrastructures.
• Implement and test quantum-enhanced cryptographic primitives.

Format of the Course

• Instructor-led presentations and guided discussions.
• Extensive hands-on exercises and applied problem-solving.
• Practical experimentation using Google Willow in a controlled lab setup.

Course Customization Options

• To tailor this training to your organisation’s needs, please contact us for customization options.

Quantum error correction serves as a fundamental strategy for ensuring reliable computation on noisy quantum hardware.

This instructor-led, live training (available online or onsite) is designed for advanced-level specialists who wish to design, test, and optimise fault-tolerant quantum algorithms using Google Willow.

Upon successful completion of this training, participants will be able to:

• Apply quantum error correction principles in both real and simulated Willow environments.
• Construct and analyse logical qubits for fault-tolerant computation.
• Evaluate the performance of quantum codes under various noise models.
• Develop workflows for scalable, resilient quantum algorithm design.

Format of the Course

• Expert-led discussions supported by technical demonstrations.
• Extensive applied exercises focused on error correction and stability testing.
• Hands-on experimentation with Google Willow in a dedicated quantum-lab environment.

Course Customisation Options

• If your organisation requires a tailored version of this training, please contact us for customisation options.

This instructor-led, live training in Australia (online or onsite) is aimed at beginner-level to intermediate-level business and technology leaders who wish to understand the fundamentals of quantum computing and its potential impact on industries such as cryptography, logistics and financial modeling, and learn how quantum computing could be applied within their sectors.

By the end of this training, participants will be able to:

• Understand the fundamental principles of quantum computing, including qubits and quantum entanglement.
• Identify potential applications of quantum computing in cryptography, logistics, and financial modeling.
• Gain insight into the current limitations and future developments of quantum technology.
• Recognize the basics of quantum algorithms and their impact on business challenges.

Google Willow is an emerging quantum platform designed to accelerate research and development in quantum-AI systems.

This instructor-led, live training (online or onsite) is aimed at advanced-level practitioners who wish to explore, design, and implement next-generation quantum-AI workflows using Google Willow.

Upon completion of this training, participants will be able to:

• Integrate quantum capabilities into AI pipelines using Willow’s development tools.
• Evaluate hybrid computation models for performance, scalability, and precision.
• Develop and test quantum-enhanced machine learning algorithms.
• Assess the future potential and limitations of quantum-AI convergence.

Format of the Course

• Theory-driven sessions enriched with hands-on experimentation.
• Extensive practice exercises focused on hybrid modelling and algorithm design.
• Practical lab work using Willow and supporting ML frameworks.

Course Customization Options

• Should your team require a tailored version of this course, we invite you to contact us to discuss customization options.