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AI+ Quantum™ Self-Paced Learning
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Introduction
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Lab Instructions
Module 1: Introduction to Overview of Artificial Intelligence (AI) and Quantum Computing
1.0 Introduction: Introduction to Overview of Artificial Intelligence (AI) and Quantum Computing
1.1 Introduction to Artificial Intelligence Refresher
1.2 Machine Learning Fundamentals
1.3 Supervised Learning Algorithms
1.4 Deep Learning Fundamentals
1.5 Introduction to Other Models
1.6 Quantum Computing Refresher
1.7 Introduction to Quantum Computing
1.8 Introduction to Qiskit SDK
1.9 Introductory Tutorial
1.10 Summary: Introduction to Overview of Artificial Intelligence (AI) and Quantum Computing
Module 1: Overview of Artificial Intelligence (AI) and Quantum Computing
Quiz
Lab Practice 1.1
Python File Download
Module 2: Quantum Computing Gates, Circuits, and Algorithms
2.0 Introduction: Quantum Computing Gates, Circuits, and Algorithms
2.1 Quantum Gates and their Representations
2.2 Single-Qubit Gates
2.3 Measurement
2.4 Multi Qubits Systems and Multi Qubit Gates
2.5 Multi-Qubit Systems
2.6 Multi-Qubit Gates
2.7 Summary: Quantum Computing Gates, Circuits, and Algorithms
Module 2: Quantum Computing Gates, Circuits, and Algorithms
Quiz
Module 3: Quantum Algorithms for AI
3.0 Introduction: Quantum Algorithms for AI
3.1 Core Quantum Algorithms
3.2 Deutsch-Jozsa Algorithm
3.3 Bernstein-Vazirani Algorithm
3.4 Grover’s Algorithm
3.5 QFT and Variational Quantum Algorithms
3.6 Quantum Fourier Transform
3.7 Variational Theory
3.8 Quantum Approximate Optimization Algorithm (QAOA)
3.9 Summary: Introduction to Quantum Algorithms for AI
Module 3: Quantum Algorithms for AI
Quiz
Lab Practice 3.1
Lab Practice 3.2
Python File Download
Module 4: Quantum Machine Learning
4.0 Introduction: Introduction to Quantum Machine Learning
4.1 Algorithms for Regression and Classification
4.2 Introduction to Quantum Machine Learning
4.3 Algorithms for Dimensionality and Clustering
4.4 Quantum Support Vector Machines
4.5 Summary: Introduction to Quantum Machine Learning
Module 4: Quantum Machine Learning
Quiz
Lab Practice 4.1
Python File Download
Module 5: Quantum Deep Learning
5.0 Introduction: Introduction to Quantum Deep Learning
5.1 Introduction: Algorithms for Neural Networks- Part I
5.2 Quantum Neural Networks (QNNs)
5.3 Quantum Convolutional Neural Networks (QCNNs)
5.4 Quantum Generative Adversarial Networks (QGANs)
5.5 Introduction: Algorithms for Neural Networks – Part II
5.6 Quantum Recurrent Neural Networks (QRNNs)
5.7 Quantum Variational Autoencoders (QVAEs)
5.8 Summary: Introduction to Quantum Deep Learning
Module 5: Quantum Deep Learning
Quiz
Lab Practice 5.1
Lab Practice 5.2
Python File Download
Module 6: Ethical Considerations
6.0 Introduction: Introduction to Ethical Considerations
6.1 Ethics for Artificial Intelligence
6.2 Risks, Challenges, and Ethics
6.3 Framework and Guidelines
6.4 Ethics for Quantum Computing
6.5 Current Scenario
6.6 Guidelines
6.7 Considerations
6.8 Summary: Introduction to Ethical Considerations
Module 6: Ethical Considerations
Quiz
Module 7: Trends and Future Outlook
7.0 Introduction: Introduction to Trends and Future Outlook
7.1 Current Trends and Tools
7.2 Current Trends
7.3 Quantum Tools
7.4 Future Outlook and Investment
7.5 Future Predictions
7.6 Funding and Investment
7.7 Summary: Introduction to Trends and Future Outlook
Module 7: Trends and Outlook
Quiz
Module 8: Use Cases & Case Studies
8.0 Introduction: Use Cases & Case Studies
8.1 Introduction: Quantum Use Cases
8.2 Use Cases
8.3 Quantum Sensing
8.4 Quantum Cryptography
8.5 Financial Constructing
8.6 Logistics Optimization and Environmental, Social, and Governance
8.7 Introduction: QML Case Studies
8.8 IBM
8.9 Comparing quantum and classical classifiers
8.10 CERN: The New IBM Quantum Hub
8.11 WitsQ: The Wits Quantum Initiative
8.12 Quantum Machine Learning in KwaZulu-Natal
8.13 Quantinuum
8.14 Rigetti
8.15 Summary: Use Cases & Case Studies
Module 8: Use Cases & Case Studies
Quiz
Lab Practice 8.1
Python File Download
Module 9: Workshop
9.0 Introduction: Introduction to Workshop
9.1 Project – I: QSVM for Iris Dataset
9.2 Project – II: VQC for Iris Dataset
9.3 Bonus: IBM Quantum Computers
9.4 Summary: Introduction to Workshop
Module 9: Workshop
Quiz
Resources
AI+ Quantum Tools
AI+ Quantum Blueprint
AI+ Quantum Detailed Curriculum
AI+ Quantum Resources and References
AI CERTs Exam Guidelines
AI CERTs Exam Guidelines
AI+ Quantum Examination
AI+ Quantum Examination
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AI+ Quantum™ Self-Paced Learning
