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Harness Quantum Power with AI

AI + Quantum Integration: Explore Quantum Gates, Circuits, and AI applications


Advanced Learnings: Includes Quantum Deep Learning and transformative AI methodologies


Industry-Oriented: Real-world case studies and trend analysis


Ethical Focus: Learn implications of quantum AI responsibly and efficiently

Price of the certification exam is included in the price of the course. Demand for AI and Quantum Technology Experts:
Organizations are seeking certified experts who can integrate AI with quantum technologies to optimize data processing and accelerate problem-solving.
Mitigating Risks in AI and Quantum Integration:
Mismanagement of quantum computing systems and AI integration can result in inefficiencies and inaccurate results in critical applications.
Developing Reliable Quantum Strategies with AI:
Certified professionals play a key role in developing quantum strategies that ensure performance, reliability, and alignment with industry standards.
Gaining a Competitive Edge:
As quantum computing and AI continue to revolutionize industries, this certification provides professionals with a competitive edge, preparing them for advanced roles.

IBM Qiskit
D-Wave Leap
Google TensorFlow Quantum (TFQ)
Amazon Braket

Obsah kurzu

Module 1: Overview of Artificial Intelligence (AI) and Quantum Computing

1.1 Artificial Intelligence Refresher
1.2 Quantum Computing Refresher

Module 2: Quantum Computing Gates, Circuits, and Algorithms

2.1 Quantum Gates and their Representation
2.2 Multi Qubit Systems and Multi Qubit Gates

Module 3: Quantum Algorithms for AI

3.1 Core Quantum Algorithms
3.2 QFT and Variational Quantum Algorithms

Module 4: Quantum Machine Learning

4.1 Algorithms for Regression and Classification
4.2 Algorithms for Dimensionality and Clustering

Module 5: Quantum Deep Learning

5.1 Algorithms for Neural Networks – Part I
5.2 Algorithms for Neural Networks – Part II

Module 6: Ethical Considerations

6.1 Ethics for Artificial Intelligence
6.2 Ethics for Quantum Computing

Module 7: Trends and Outlook

7.1 Current Trends and Tools
7.2 Future Outlook and Investment

Module 8: Use Cases & Case Studies

8.1 Quantum Use Cases
8.2 QML Case Studies

Module 9: Workshop

9.1 Project – I: QSVM for Iris Dataset
9.2 Project – II: VQC/QNN on Iris Dataset
9.3 Bonus: IBM Quantum Computers

Optional Module: AI Agents for Quantum

1. What Are AI Agents
2. Key Capabilities of AI Agents in Quantum Computing
3. Applications and Trends for AI Agents in Quantum Computing
4. How Does an AI Agent Work
5. Core Characteristics of AI Agents
6. Types of AI Agents

Cieľová skupina

Quantum Computing Engineers: Enhance quantum system design and performance using AI for optimization and control.
Physics Engineers: Apply AI techniques to improve quantum simulations and computational models.
AI Specialists: Leverage AI and quantum algorithms to create intelligent solutions for complex problems.
IT Specialists & System Integrators: Integrate AI-driven quantum computing systems to optimize infrastructure and solve large-scale challenges.
Students & New Graduates: Gain foundational skills in AI and quantum computing to excel in the rapidly advancing quantum technology field.
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