AI+ Quantum™

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

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