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所在平台: Udemy |
课程主页: https://www.udemy.com/course/qc101-introduction-to-quantum-computing-quantum-physics-for-beginners/
课程评论：没有评论
课程名称：QC101 量子计算与量子机器学习简介 课程概述：欢迎参加这一在Udemy上热销的量子计算课程！量子计算是软件行业的下一个浪潮。量子计算机的处理速度是现代经典计算机的指数级别。许多被认为计算机无法解决的问题，如生物系统中的蛋白质折叠模拟和破解RSA加密，现在都可以通过量子计算机来实现。一个64位的量子计算机每一步计算可以处理36000亿亿字节的信息，而一般家用计算机每步只处理8字节！谷歌、英特尔、IBM和微软等公司正在数十亿美元的投资，在构建量子计算机的道路上。如果你现在掌握量子计算，将为从这一技术革命中获益做好准备。 本课程从基础开始教授量子计算相关知识，您只需具备12年级的高中数学和物理基础。重要提示：您需要对物理和数学感兴趣，以便充分理解这门课程。课程主要通过数学和量子物理分析量子电路的行为。课程中会解释超出高中科学的所有知识，但请注意，量子物理是一个非常复杂的学科，您可能需要多次回放视频以理解内容。 课程内容还包括量子机器学习，它被认为是量子计算的“杀手级应用”。量子机器学习算法可以显著加快训练速度，从而获得更准确的预测。虽然理解量子算法需要掌握复杂的数学知识，但使用量子机器学习相对简单。Qiskit将机器学习算法封装成一个类似于流行的Scikit-Learn机器学习工具包的API，因此您几乎可以像使用传统机器学习一样轻松使用量子机器学习。 课程大纲： - 数学基础回顾，包括线性代数、概率论、布尔代数和复数。 - 通过偏振光的行为来解释量子物理。 - 学习量子密码学，介绍BB84量子协议以实现安全密钥共享。 - 理解量子程序的基本构建块——量子门，通过深入研究量子叠加和量子纠缠来理解量子门的工作原理。 - 使用Microsoft Q#和IBM Qiskit构建量子电路，并为Python编程语言提供简要入门。 - 从简单电路开始，逐步实现Qiskit中的BB84量子密码学协议。 - 介绍经典机器学习和神经网络的基础，最终在真实世界数据上训练量子支持向量机，并利用其进行预测。 建议学员在学习过程中打开转录面板，以帮助理解概念。如果需要加快学习速度，可以根据传稿文本跳过不需要重复的内容。 立即注册，加入量子革命！
Welcome to the bestselling quantum computing course on Udemy!Quantum Computing is the next wave of the software industry. Quantum computers are exponentially faster than classical computers of today. Problems that were considered too difficult for computers to solve, such as simulation of protein folding in biological systems, and cracking RSA encryption, are now possible through quantum computers.How fast are Quantum Computers? A 64-bit quantum computer can process 36 billion billion bytes of information in each step of computation. Compare that to the 8 bytes that your home computer can process in each step of computation!Companies like Google, Intel, IBM, and Microsoft are investing billions in their quest to build quantum computers. If you master quantum computing now, you will be ready to profit from this technology revolution.This course teaches quantum computing from the ground up. The only background you need is 12th grade level high-school Math and Physics. IMPORTANT: You must enjoy Physics and Math to get the most out of this course. This course is primarily about analyzing the behavior of quantum circuits using Math and Quantum Physics. While everything you need to know beyond 12th grade high school science is explained here, you must be aware that Quantum Physics is an extremely difficult subject. You might frequently need to stop the video and replay the lesson to understand it. QUANTUM MACHINE LEARNINGIt appears that the killer-app for quantum computing will be machine learning and artificial intelligence.Quantum machine learning algorithms provide a significant speed-up in training. This speed-up can result in more accurate predictions.While understanding quantum algorithms requires mastery of complex math, using quantum machine learning is relatively simple. Qiskit encapsulates machine learning algorithms inside an API that mimics the popular Scikit-Learn machine-learning toolkit. So you can use quantum machine learning almost as easily as you would traditional ML!Quantum machine learning can be applied in the back-end to train models, and those trained models can be used in consumer gadgets. This means that quantum machine learning might enhance your everyday life even if quantum computers remain expensive!COURSE OUTLINEWe begin by learning about basic math. You might have forgotten the math you learned in high-school. I will review linear algebra, probability, Boolean algebra, and complex numbers.Quantum physics is usually considered unapproachable because it deals with the behavior of extremely tiny particles. But in this course, I will explain quantum physics through the behavior of polarized light. Light is an everyday phenomenon and you will be able to understand it easily.Next we learn about quantum cryptography. Quantum cryptography is provably unbreakable. I will explain the BB84 quantum protocol for secure key sharing.Then we will learn about the building-blocks of quantum programs which are quantum gates.To understand how quantum gates work, we will study quantum superposition and quantum entanglement in depth.We will apply what we have learned by constructing quantum circuits using Microsoft Q# (QSharp) and IBM Qiskit. For those of you who don't know the Python programming language, I will provide a crisp introduction of what you need to know.We will begin with simple circuits and then progress to a full implementation of the BB84 quantum cryptography protocol in Qiskit.The killer-app for quantum computing is quantum machine learning.To understand quantum machine learning, we must first learn how classical machine learning works. I provide a crisp introduction to classical machine learning and neural networks (deep learning).Finally, we will train a Quantum Support Vector Machine on real-world data and use it to make predictions.For a better learning experience, open the transcript panel. You will see a small "transcript" button at the bottom-right of the video player on Udemy's website. If you click this button, the transcript of the narration will be displayed. The transcripts for all the videos have been hand-edited for accuracy. Opening the transcript panel will help you understand the concepts better. If you missed an important concept, then you can click on text in the transcript panel to return directly to the part you want to repeat. Conversely, if you already understand the concept being presented, you can click on text in the transcript panel to skip ahead in the video.Pacing: This course is designed to be slow with a lot of repetition. Quantum physics is easier for beginners to understand when concepts are repeated. If you want to learn at a faster pace, then open the transcripts panel (as explained in the previous paragraph above) and click the transcript-text to skip ahead to the next concept.Enroll today and join the quantum revolution!
