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Duration 14 hours
Course Outline
Quantum Mechanics Foundations
- Core principles of quantum mechanics
- Understanding quantum states and qubits
- Exploring superposition and entanglement
Essentials of Quantum Computing
- Quantum circuits and the function of quantum gates
- Techniques for quantum measurement and qubit control
- An introduction to the landscape of quantum algorithms
Advanced Quantum Algorithms
- A comprehensive overview of quantum algorithmic strategies
- The Quantum Fourier Transform and its practical uses
- Grover’s algorithm applied to database search problems
Intersection of Quantum AI and Machine Learning
- Algorithms designed specifically for quantum machine learning
- The architecture of quantum neural networks
- Exploring the diverse potential applications of Quantum AI
Challenges and the Future Landscape of Quantum AI
- Current technical obstacles in Quantum AI development
- Ethical frameworks and the broader societal impact
- Emerging trends and future research pathways in Quantum AI
Practical Lab Project
- Simulating quantum algorithms utilizing Qiskit or comparable quantum computing platforms
- Building a rudimentary quantum machine learning model
- Collaborating in teams to design and propose a novel application for Quantum AI
Requirements
- A solid grasp of linear algebra and the fundamentals of quantum mechanics
- Proficiency in Python programming
Target Audience
- Professionals in Artificial Intelligence
- Researchers focused on AI development