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所在平台: Udemy |
课程主页: https://www.udemy.com/course/ipython-and-jupyter-notebook-in-practice-3-in-1/
课程评论：没有评论
课程名称：IPython和Jupyter Notebook实战：三合一 课程概述：Python是数据科学和数值计算的领先开源平台之一，IPython和Jupyter Notebook提供了高效的Python接口，用于数据分析和交互式可视化，成为这一平台的理想入口。本综合性的三合一课程是一个实用的、以实例为驱动的教程，旨在显著提高您在交互式Python会话中的生产力，并教您如何有效地利用IPython进行交互计算、数据分析和数据可视化。 课程主要内容包括：在第一部分，您将学习IPython的基本知识，包括Python语言、IPython和Jupyter Notebook的介绍。您将通过真实案例学习如何分析和可视化数据，创建图形用户界面进行图像处理，以及使用NumPy、Numba、Cython和ipyparallel进行科学模拟的快速数值计算。第二部分将探讨Jupyter Notebook的编程技巧，包括代码质量和可重现性、代码优化、通过即时编译实现高性能计算、并行计算和图形处理器编程。第三部分涵盖了数据科学中的统计方法与应用数学，包括数据科学、统计学、机器学习、信号与图像处理、动态系统以及纯和应用数学。 课程的最终目标是使您熟练掌握数据科学与数学建模中的标准方法，以便将这些先进的方法应用于各种实际案例，来说明应用数学、科学建模和机器学习的相关主题。 讲师介绍：本课程的作者Cyrille Rossant，博士，现为伦敦大学学院的神经科学研究者和软件工程师。他毕业于巴黎高等师范学校，主攻数学和计算机科学，并曾在普林斯顿大学和法国高等研究院工作。在数据科学和软件工程项目中，他积累了数值计算、并行计算和高性能数据可视化的经验，并著有《学习IPython进行交互式计算和数据可视化》第二版。 总之，本课程将通过三个完整的子课程，为您提供全面的培训，助您掌握IPython和Jupyter Notebook在数据科学中的应用。
Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and constitute an ideal gateway to the platform. This comprehensive 3-in-1 course is a practical, hands-on, example-driven tutorial to considerably improve your productivity during interactive Python sessions, and shows you how to effectively use IPython for interactive computing, data analysis, and data visualization. You will learn all aspects of of IPython, from the highly powerful interactive Python console to the numerical and visualization features that are commonly associated with IPython. You will also learn high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to write better and faster code. This training program includes 3 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Learning IPython for Interactive Computing and Data Visualization, begins with an introduction to Python language, IPython, and Jupyter Notebook. You will then learn how to analyze and visualize data on real-world examples, how to create graphical user interfaces for image processing in Notebook, and how to perform fast numerical computations for scientific simulations with NumPy, Numba, Cython, and ipyparallel.The second course, Interactive Computing with Jupyter Notebook, covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming.The third course, Statistical Methods and Applied Mathematics in Data Science, tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics. You will be well versed with the standard methods in data science and mathematical modeling.By the end of this course, you will be able to apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning.Meet Your Expert(s):We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:Cyrille Rossant, PhD, is a neuroscience researcher and software engineer at University College, London. He is a graduate of École Normale Supérieure, Paris, where he studied mathematics and computer science. He has also worked at Princeton University and Collège de France. While working on data science and software engineering projects, he gained experience in numerical computing, parallel computing, and high-performance data visualization. He is the author of Learning IPython for Interactive Computing and Data Visualization, Second Edition, Packt Publishing.
