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Course Outline
Foundations of Quantum Mechanics
- Core tenets of quantum mechanics
- Quantum states and the concept of qubits
- Superposition and entanglement phenomena
Basics of Quantum Computing
- Quantum circuits and gate operations
- Measurement techniques and qubit control
- Introduction to quantum algorithm design
Advanced Quantum Algorithms
- Survey of key quantum algorithms
- The Quantum Fourier Transform and its utility
- Grover’s algorithm applied to database search
Quantum AI and Machine Learning Integration
- Algorithms for quantum machine learning
- Architecture of quantum neural networks
- Exploring the practical utility of Quantum AI
Challenges and the Trajectory of Quantum AI
- Technical hurdles in advancing Quantum AI
- Ethical dimensions and societal impact
- Emerging trends and research pathways in the field
Practical Lab Project
- Simulating quantum algorithms via Qiskit or comparable frameworks
- Building a fundamental quantum machine learning model
- Collaborative group work to propose innovative Quantum AI applications
Requirements
- A foundational grasp of linear algebra and quantum mechanics
- Working knowledge of Python programming
Target Audience
- AI professionals
- AI researchers
14 Hours