AT-410
AI+ Quantum Practitioner™
Harness Quantum Power with AI
At a glance
What is included
Duration
- Instructor-Led: 5 days (live or virtual)
- Self-Paced: 40 hours of content
Recommended background
Examination
About this certification
- 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
Curriculum
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
Who should enrol
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.
Related certifications
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