AI+ Quantum™

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

1. 1.1 Artificial Intelligence Refresher 
2. 1.2 Quantum Computing Refresher 

Module 2: Quantum Computing Gates, Circuits, and Algorithms .

1. 2.1 Quantum Gates and their Representation 
2. 2.2 Multi Qubit Systems and Multi Qubit Gates 

Module 3: Quantum Algorithms for AI.

1. 3.1 Core Quantum Algorithms 
2. 3.2 QFT and Variational Quantum Algorithms 

Module 4: Quantum Machine Learning .

1. 4.1 Algorithms for Regression and Classification 
2. 4.2 Algorithms for Dimensionality and Clustering 

Module 5: Quantum Deep Learning .

1. 5.1 Algorithms for Neural Networks – Part I 
2. 5.2 Algorithms for Neural Networks – Part II 

Module 6: Ethical Considerations .

1. 6.1 Ethics for Artificial Intelligence 
2. 6.2 Ethics for Quantum Computing 

Module 7: Trends and Outlook .

1. 7.1 Current Trends and Tools 
2. 7.2 Future Outlook and Investment 

Module 8: Use Cases & Case Studies.

1. 8.1 Quantum Use Cases 
2. 8.2 QML Case Studies 

Module 9: Workshop .

1. 9.1 Project – I: QSVM for Iris Dataset 
2. 9.2 Project – II: VQC/QNN on Iris Dataset 
3. 9.3 Bonus: IBM Quantum Computers 

Optional Module: AI Agents for Quantum.

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