Course Outline

Introduction to Quantum Mechanics

  • Basic principles of quantum mechanics
  • Quantum states and qubits
  • Superposition and entanglement

Quantum Computing Basics

  • Quantum circuits and quantum gates
  • Quantum measurement and qubit manipulation
  • Introduction to quantum algorithms

Quantum Algorithms

  • Overview of quantum algorithms
  • Quantum Fourier transform and its applications
  • Grover's algorithm for database search

Quantum AI and Machine Learning

  • Quantum machine learning algorithms
  • Quantum neural networks
  • Potential applications of Quantum AI

Challenges and Future of Quantum AI

  • Technical challenges in Quantum AI
  • Ethical considerations and societal impact
  • Future trends and research directions in Quantum AI

Lab Project

  • Simulating quantum algorithms using Qiskit or similar quantum computing frameworks
  • Developing a basic quantum machine learning model
  • Collaborating on a group project to propose an innovative application of Quantum AI

Summary and Next Steps

Requirements

  • Basic understanding of linear algebra and quantum mechanics
  • Familiarity with Python programming

Audience

  • AI professionals
  • AI researchers
 14 Hours

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