Introduction to Quantum AI Training Course
Quantum Artificial Intelligence (Quantum AI) is the interdisciplinary field that combines quantum computing with artificial intelligence to potentially solve complex problems more efficiently than classical computers.
This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level AI professionals and AI researchers who wish to understand the fundamentals of Quantum AI and its potential applications.
By the end of this training, participants will be able to:
- Grasp the basic principles of quantum mechanics as they apply to quantum computing.
- Understand the workings of quantum algorithms and their implementation.
- Recognize the potential of Quantum AI in revolutionizing various industries.
- Develop a foundational quantum machine learning model.
- Evaluate the challenges and ethical considerations of Quantum AI.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Course Outline
Introduction to Quantum Mechanics
- Basic principles of quantum mechanics
- Quantum states and qubits
- Superposition and entanglement
Quantum Computing Basics
- Quantum circuits and quantum gates
- Quantum measurement and qubit manipulation
- Introduction to quantum algorithms
Quantum Algorithms
- Overview of quantum algorithms
- Quantum Fourier transform and its applications
- Grover's algorithm for database search
Quantum AI and Machine Learning
- Quantum machine learning algorithms
- Quantum neural networks
- Potential applications of Quantum AI
Challenges and Future of Quantum AI
- Technical challenges in Quantum AI
- Ethical considerations and societal impact
- Future trends and research directions in Quantum AI
Lab Project
- Simulating quantum algorithms using Qiskit or similar quantum computing frameworks
- Developing a basic quantum machine learning model
- Collaborating on a group project to propose an innovative application of Quantum AI
Summary and Next Steps
Requirements
- Basic understanding of linear algebra and quantum mechanics
- Familiarity with Python programming
Audience
- AI professionals
- AI researchers
Open Training Courses require 5+ participants.
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Testimonials (1)
Quantum computing algorithms and related theoretical background know-how of the trainer is excellent. Especially I'd like to emphasize his ability to detect exactly when I was struggling with the material presented, and he provided time&support for me to really understand the topic - that was great and very beneficial! Virtual setup with Zoom worked out very well, as well as arrangements regarding training sessions and breaks sequences. It was a lot of material/theory to cover in "only" 2 days, wo the trainer had nicely adjusted the amount according to the progress related to my understanding of the topics. Maybe planning 3 days for absolute beginners would be better to cover all the material and content outlined in the agenda. I very much liked the flexibility of the trainer to answer my specific questions to the training topics, even additionally coming back after the breaks with more explanation in case neccessary. Big thank you again for the sessions! Well done!
Giorgi Ediberidze
Course - Quantum Computing with IBM Quantum Experience
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