Quantum Computing and Quantum Machine Learning - Part 2

Introduction to Quantum Principles, Quantum Gates and Quantum Programming
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Quantum Computing and Quantum Machine Learning - Part 2
856
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2 hours
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Mar 2021
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$29.99
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Why take this course?


Unlock the Mysteries of Quantum Computing and Quantum Machine Learning with Expert Instructor Rushabh Doshici! 🚀

Course Title:

Quantum Computing and Quantum Machine Learning - Part 2

Course Headline:

Introduction to Quantum Principles, Quantum Gates, and Quantum Programming


Course Description:

🌟 Please ensure you have completed the Part 1 course which sets the foundational tone for this part 2 series.

Quantum Computing and Quantum Machine Learning are revolutionizing the tech industry, and with our comprehensive online course, you can be at the forefront of this transformation. This course is tailored for professionals in Machine Learning, Artificial Intelligence, Physicists, Researchers, Cloud Computing Professionals, Python Programmers, DevOps, Security, and Data Science. Dive into the new era of computing and master the principles that will shape the future.

Why This Course?

  • In-Depth Coverage: All pre-requisites are covered thoroughly to ensure a solid understanding before moving on to more advanced topics.
  • Stepwise Progression: The course is launched in segments, starting from the basics and progressing step by step.
  • No Prior Knowledge Required: This course is designed for individuals with an interest in quantum computing and machine learning, regardless of their current expertise level.

Course Highlights:

  • Part 1 Foundations: The first part of the series will lay down the essential foundations for studying quantum computation, focusing on quantum mechanics and some mathematical basics.
  • Programming with Qiskit: From Part 2 onward, programming begins in earnest using IBM's Qiskit library. Concepts of quantum computing and quantum machine learning will be revealed as you progress.
  • Quantum Computing Series: The series will be released in multiple parts, each building upon the last, with concepts clearly separated for ease of learning.

What You Will Learn:

  • Quantum Mechanics Fundamentals: Gain a solid understanding of the principles that govern quantum systems.
  • Quantum Programming: Start programming quantum computers using the Qiskit framework.
  • Quantum Gates: Explore the quantum gates and their role in manipulating qubits.
  • Physics of Quantum Systems: Discover the physics behind quantum computing.
  • Quantum Machine Learning Concepts: Learn how quantum principles can be applied to machine learning tasks to solve complex problems more efficiently.

Pre-Requisites:

  • Python Proficiency: A good grasp of Python is essential as it's the primary language for quantum programming.
  • 10th Grade Math/Physics: Basic knowledge of high school math and physics will be helpful to comprehend the quantum concepts better.

Join Us on This Quantum Adventure! 💫 This course is designed to build a solid foundation for those interested in exploring the vast potential of Quantum Computing and Quantum Machine Learning. Whether you're a student, a professional, or simply an enthusiast, this course will guide you through the complexities of quantum computing and introduce you to the world of quantum programming using Qiskit.

Don't miss out on this opportunity to be part of the future of computing! 🌐💫


Enroll Now and Transform Your Career with Quantum Computing and Machine Learning! 🚀🔬

Course Gallery

Quantum Computing and Quantum Machine Learning - Part 2 – Screenshot 1
Screenshot 1Quantum Computing and Quantum Machine Learning - Part 2
Quantum Computing and Quantum Machine Learning - Part 2 – Screenshot 2
Screenshot 2Quantum Computing and Quantum Machine Learning - Part 2
Quantum Computing and Quantum Machine Learning - Part 2 – Screenshot 3
Screenshot 3Quantum Computing and Quantum Machine Learning - Part 2
Quantum Computing and Quantum Machine Learning - Part 2 – Screenshot 4
Screenshot 4Quantum Computing and Quantum Machine Learning - Part 2

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3730802
udemy ID
27/12/2020
course created date
17/01/2021
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