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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
  • Phenomena of superposition and entanglement

Foundations of Quantum Computing

  • Structure of quantum circuits and gates
  • Processes of quantum measurement and qubit control
  • Primer on quantum algorithms

Quantum Algorithms

  • Broad overview of available quantum algorithms
  • The Quantum Fourier Transform and its utility
  • Utilizing Grover's algorithm for database searching

Quantum AI and Machine Learning

  • Exploration of quantum machine learning techniques
  • Architecture of quantum neural networks
  • Practical applications of Quantum AI

Challenges and the Future of Quantum AI

  • Current technical limitations in Quantum AI
  • Ethical frameworks and societal impacts
  • Emerging trends and future research trajectories in Quantum AI

Practical Lab Project

  • Simulating quantum algorithms using Qiskit or comparable quantum computing platforms
  • Designing a simple quantum machine learning model
  • Collaborative group work to propose a novel Quantum AI application

Requirements

  • Foundational knowledge of linear algebra and quantum mechanics
  • Proficiency in Python programming

Target Audience

  • AI professionals
  • AI researchers

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