AI+ Quantum (AT-410 Self-Paced Training)
Ziele der Schulung
The AI+ Quantum™ certification bridges the gap between Artificial Intelligence and Quantum Computing by equipping learners with foundational and advanced skills in quantum gates, circuits, quantum algorithms, quantum machine learning, and quantum deep learning. It also addresses ethical implications and industry trends, providing practical workshops and real-world case studies to prepare participants to innovate at the intersection of AI and quantum technologies.
Zielgruppe Seminar
- Individuals seeking expertise in integrating AI with quantum computing
- Professionals aiming to develop quantum strategies with AI for performance and industry relevance
- Students and graduates wishing to build foundational skills in AI and quantum computing.
Voraussetzungen
- Foundational knowledge of AI concepts (no advanced technical skills required)
- Openness to unconventional problem-solving approaches in AI and quantum contexts
- Willingness to engage with ethical considerations related to AI and quantum practices.
Seminarinhalt
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
- What Are AI Agents
- Key Capabilities of AI Agents in Quantum Computing
- Applications and Trends for AI Agents in Quantum Computing
- How Does an AI Agent Work
- Core Characteristics of AI Agents
- Types of AI Agents
Hinweise
Prüfung und Zertifizierung
- Duration: 90 minutes
- Format: 50 multiple-choice/multiple-response questions
- Passing Score: 70% (35/50)
- Delivery Method: Online proctored exam
- Exam Blueprint: Covered across modules on AI & quantum topics.
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