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Duration 14 hours
Course Outline
Introduction to Quantum Mechanics
- Core principles of quantum mechanics
- Quantum states and the concept of qubits
- Exploring superposition and entanglement
Basics of Quantum Computing
- Quantum circuits and gate structures
- Measurement techniques and qubit control
- Fundamental overview of quantum algorithms
Quantum Algorithms
- General overview of quantum algorithmic strategies
- The Quantum Fourier transform and its use cases
- Grover's algorithm for efficient database searching
Quantum AI and Machine Learning
- Algorithms tailored for quantum machine learning
- Structure and function of quantum neural networks
- Real-world application scenarios for Quantum AI
Challenges and the Future of Quantum AI
- Current technical limitations in Quantum AI
- Ethical considerations and broader societal impact
- Emerging trends and future research pathways in Quantum AI
Lab Project
- Simulation of quantum algorithms using Qiskit or comparable quantum computing frameworks
- Creation of a basic quantum machine learning model
- Group collaboration to design a novel Quantum AI application proposal
Requirements
- A solid grasp of linear algebra and the basics of quantum mechanics
- Proficiency in Python programming
Target Audience
- AI professionals
- AI researchers