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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
- Superposition and entanglement phenomena
Quantum Computing Basics
- Quantum circuits and gate operations
- Measurement techniques and qubit manipulation
- Overview of fundamental quantum algorithms
Quantum Algorithms
- Broad overview of quantum algorithmic approaches
- The Quantum Fourier Transform and its uses
- Grover's algorithm for efficient database search
Quantum AI and Machine Learning
- Quantum machine learning methodologies
- Architectures of quantum neural networks
- Potential industry applications of Quantum AI
Challenges and Future of Quantum AI
- Current technical hurdles in the field
- Ethical frameworks and societal impact
- Emerging trends and research directions
Lab Project
- Simulating quantum algorithms using Qiskit or comparable frameworks
- Building a basic quantum machine learning model
- Collaborative group project to propose an innovative Quantum AI application
Requirements
- A solid grasp of linear algebra and basic quantum mechanics concepts.
- Proficiency in Python programming.
Target Audience
- AI professionals
- AI researchers