Practical quantum computing
The training introduces participants to the world of quantum computing and its practical applications in artificial intelligence. The program covers the implementation of quantum algorithms and their integration with classical ML solutions. Practical workshops allow participants to create and test quantum circuits on their own. The classes combine theory and practice, enabling understanding of fundamental concepts and their application.
Issues
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Fundamentals of quantum mechanics
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Qubits and quantum operations
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Quantum neural networks
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Hybrid ML approaches
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Quantum optimization
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Quantum simulators
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Debugging layouts
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Testing algorithms
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Business use cases
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Performance analysis
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Practical implementation
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Integration with classic systems
Benefits
- The participant will acquire a working knowledge of the implementation of quantum algorithms in machine learning
- He or she will develop the ability to design and test quantum systems in real-world applications
- Will gain the ability to combine classical and quantum approaches in AI solutions
- Will learn to identify use cases where quantum computing can bring business value
- Will learn methods for optimizing algorithms using quantum techniques
- Will be able to analyze and compare the performance of different computing approaches
- Will gain the ability to work with quantum simulators
- Will develop the ability to debug and test quantum algorithms
Who is this training for?
Prerequisites
- Knowledge of the basics of quantum mechanics
- Experience in the implementation of ML algorithms
- A solid mathematical foundation (linear algebra, probability calculus)
- Python programming skills
Training program
Qubits and quantum gates
- Entangled states and superposition
Multicubit systems
- Quantum measurements
- Quantum algorithms in ML
- Quantum neural networks
- Quantum machine learning
Hybrid classical-quantum approaches
- Quantum optimization
- Practical implementation
- Quantum simulation environments
- Quantum circuit programming
- Debugging algorithms
Testing solutions
- Business applications
- Portfolio optimization
Anomaly detection
- Natural language processing
- Pattern recognition
Delivery Methods
Online
- Convenience of participating from anywhere
- Interactive live sessions with trainer
- Materials available for 30 days
- No travel costs
On-site
- Direct contact with trainer and group
- Intensive hands-on workshops
- Networking with other participants
- Full focus on learning
Frequently asked questions
What are the prerequisites for this training?
For Practical quantum computing we recommend: Knowledge of the basics of quantum mechanics; Experience in the implementation of ML algorithms; A solid mathematical foundation (linear algebra, probability calculus).
What is the format and duration of this training?
The training lasts 2 days and is available in online and on-site format. Sessions run from 9:00 AM to 4:00 PM. We can also customize the schedule to fit your team's needs.
Who is this training designed for?
This training is designed for: ML engineers interested in quantum computing; AI systems developers looking for new solutions; Machine learning researchers.
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Funding Options
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Development Services Database
Up to 80% funding for SMEs from EU funds
Check availabilityNational Training Fund
Up to 100% funding for employers
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