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Quantum Machine Learning: Harnessing Quantum Computing for AI Course

Original price was: INR ₹10,998.00.Current price is: INR ₹5,499.00.

Course Overview

This 8-week intensive course is tailored for advanced undergraduates, graduate students, and professionals eager to explore the intersection of quantum computing and AI. Through comprehensive tutorials, participants will learn how to simulate quantum circuits, develop quantum algorithms, and apply these techniques to AI tasks. The course offers a unique opportunity to dive into this cutting-edge technology, preparing participants to contribute to the future of quantum machine learning.

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Quantum Machine Learning: Harnessing Quantum Computing for AI
Quantum Computing, Machine Learning, Quantum Algorithms

Course Overview

This 8-week intensive course is tailored for advanced undergraduates, graduate students, and professionals eager to explore the intersection of quantum computing and AI. Through comprehensive tutorials, participants will learn how to simulate quantum circuits, develop quantum algorithms, and apply these techniques to AI tasks. The course offers a unique opportunity to dive into this cutting-edge technology, preparing participants to contribute to the future of quantum machine learning.

Course Goals

The primary aim of this course is to provide participants with a deep understanding of quantum computing fundamentals and their applications in machine learning. The course is designed to bridge the gap between quantum technologies and AI, empowering participants to develop and implement quantum machine learning algorithms that outperform classical solutions in both speed and efficiency.

Program Objectives

  • Understand Quantum Computing and AI: Build a strong foundation in quantum mechanics principles and their application to solving complex computational problems.
  • Develop Quantum Algorithms: Learn to create quantum machine learning algorithms, including quantum neural networks and quantum support vector machines.
  • Project Implementation: Plan and execute a quantum machine learning project, from inception to testing and optimization, on quantum computing platforms.
  • Industry Readiness: Prepare for emerging roles in the quantum technology sector by gaining insights into current technologies, potential applications, and industry needs.

Program Structure

  • Module 1: Introduction to Quantum Computing and Machine Learning
    • Section 1: Foundations of Quantum Computing
      • Principles of Quantum Mechanics
      • Quantum Bits and Quantum Gates
      • Quantum Circuits
    • Section 2: Basics of Machine Learning
      • Overview of Machine Learning
      • Algorithms and Models in Classical Machine Learning
      • Data Handling and Preprocessing
    • Section 3: Integration of Quantum Computing with Machine Learning
      • Potential of Quantum Computing in AI
      • Case Studies: Quantum Speedups in Algorithmic Tasks
  • Module 2: Quantum Algorithms for Machine Learning
    • Section 1: Quantum Algorithms Basics
      • Grover’s Algorithm
      • Shor’s Algorithm
      • Quantum Fourier Transform
    • Section 2: Quantum Machine Learning Algorithms
      • Quantum Principal Component Analysis
      • Quantum Support Vector Machines
      • Quantum Neural Networks
  • Module 3: Implementing Quantum ML Models
    • Section 1: Quantum Programming Languages
      • Qiskit
      • Microsoft Q#
      • Forest by Rigetti
    • Section 2: Simulation and Real Quantum Computers
      • Using IBM Quantum Experience
      • Cloud-based Quantum Computing
    • Section 3: Project Development
      • Project Planning and Design
      • Implementation of a Quantum ML Model
      • Testing and Optimization on Quantum Devices

Eligibility

  • This course is suitable for advanced undergraduates and graduate students in Computer Science, IT, and Electronics, as well as professionals in IT services, consulting, and analytics services looking to explore new technologies. A basic understanding of quantum computing and machine learning concepts is recommended.

Learning Outcomes

  • Gain a robust understanding of quantum machine learning and its applications in AI.
  • Develop practical skills in implementing machine learning algorithms on quantum devices.
  • Acquire hands-on experience through simulations of quantum circuits and real-world projects.
  • Explore the integration of quantum computing with machine learning to solve complex problems.
  • Be prepared to contribute to the rapidly growing field of quantum machine learning in academia or industry.

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Certification

  • Upon successful completion of the workshop, participants will be awarded a Certificate of Completion, validating their skills and knowledge in advanced AI ethics and regulatory frameworks. This certification can be added to your LinkedIn profile or shared with employers to demonstrate your commitment to ethical AI practices.

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