Introduction to Quantum AI Training Course

This instructor-led, live training in Malaysia (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.
• Optimize AI models using quantum computing resources.
• Overcome challenges in scaling and integrating quantum AI systems.

Google Willow serves as a cloud-accessible quantum computing platform intended to facilitate experimentation, algorithm development, and applied quantum research.

This instructor-led live training, available either online or on-site, targets intermediate-level professionals eager to explore practical industry use cases of quantum computing via Google Willow.

Upon finishing this training, participants will be able to:

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

Course Format

• 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 serves as a cloud-based quantum computing platform, empowering developers and researchers to design, test, and execute quantum algorithms.

This instructor-led live training, available either online or onsite, targets intermediate-level professionals seeking to build and run quantum algorithms on Google Willow.

Upon completing this training, participants will be able to:

• Create and structure quantum circuits for both experimental and practical applications.
• Deploy quantum algorithms utilizing Google Willow’s interface and APIs.
• Assess algorithm performance and refine quantum workflows.
• Integrate quantum techniques into broader computational pipelines.

Course Format

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

Customization Options

• Tailored training programs for specialized quantum algorithm research are available upon request.

In this instructor-led live training in Malaysia, participants will learn the fundamentals of quantum computing while stepping through the development of algorithms targeted at quantum computers.

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

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

This instructor-led, live training session in Malaysia (online or on-site) is designed for beginners who wish to understand the fundamentals of quantum computing, explore the capabilities of Google Willow, and learn how to start with quantum programming.

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

• Understand the principles of quantum computing and qubits.
• Explore Google Willow and its advancements in quantum error correction.
• Write and execute basic quantum programs using Qiskit.
• Identify real-world applications of quantum computing.

ProjectQ is an open-source quantum computing software framework written in Python. It empowers users to define quantum circuits and translate them for execution on various backend quantum hardware platforms or simulators. The framework provides support for sophisticated optimizations, compiler engines, and flexible backend targeting.

This instructor-led live training (available online or onsite) is designed for intermediate-level developers who wish to gain a deep understanding of and practical experience with ProjectQ for quantum programming and backend translation.

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

• Explain the architecture and core objectives of ProjectQ.
• Develop quantum circuits using ProjectQ's Python API.
• Leverage ProjectQ's compiler engines and optimization capabilities.
• Direct quantum programs to different backend systems or simulators using ProjectQ.

Course Format

• Engaging lectures paired with interactive discussions.
• Practical coding exercises focused on building quantum circuits.
• Live laboratory sessions where participants target either simulator or hardware backends.

Customization Options

• To arrange a customized version of this course, please get in touch with us.

Quantum cryptography represents a cutting-edge security paradigm that utilises the principles of quantum mechanics to protect data. <\/p>

This instructor-led live training, available either online or onsite, is designed for intermediate-level specialists aiming to construct secure systems using quantum-resistant and quantum-enhanced techniques on the Google Willow platform. <\/p>

After completing this training, participants will be able to: <\/p>

• Develop quantum-safe communication workflows using Google Willow. <\/li>
• Assess quantum threats directed at classical security protocols. <\/li>
• Apply quantum key distribution concepts within modern infrastructures. <\/li>
• Implement and test quantum-enhanced cryptographic primitives. <\/li> <\/ul>

  Course Format<\/strong> <\/p>

  • Instructor-led presentations coupled with guided discussions. <\/li>
  • Comprehensive hands-on exercises and applied problem-solving activities. <\/li>
  • Practical experimentation with Google Willow in a controlled laboratory environment. <\/li> <\/ul>

    Course Customization Options<\/strong> <\/p>

    • To tailor this training to meet your organisation’s specific needs, please reach out to us for customization options. <\/li> <\/ul>