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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-science-with-jupyter-2-in-1/
课程评论：没有评论
课程名称：数据科学与Jupyter：2合1 课程概述：Jupyter作为一个开源网络应用程序，已成为代码展示和研究文献分享的流行工具。它允许您创建和分享包含实时代码、方程、可视化和叙述文本的文档。Jupyter的应用包括数据清洗与转化、数值模拟、统计建模、数据可视化、机器学习等。本课程适合已经具备Python或R编程经验及基本Jupyter理解的学习者，全面教授如何使用Jupyter进行日常数据科学任务。课程内容结合概念与实用案例，逻辑性强，便于理解与实施。 本课程包含两个完整的部分。第一部分“数据科学中的Jupyter”从Jupyter概念及其安装开始，随后学习各种数据科学任务，如数据分析、数据可视化和数据挖掘。还将介绍如何将Python 3、R和Julia与Jupyter结合使用。接着进行统计建模，并理解多种机器学习概念及其在Jupyter中的实现。第二部分“深入Jupyter”将带您了解控制台、客户端及笔记本服务器的核心模块及标准功能。通过探索Python语言，您将能够启动配置管理、文件系统监控及数据加密备份等项目。学习如何在Jupyter笔记本中创建仪表板，以报告项目相关的信息及各个Jupyter组件的状态。 通过本培训项目，您将能够高效地利用Jupyter的强大功能进行各类数据科学任务。 讲师介绍：课程由经验丰富的讲师教授，包括： - Dan Toomey，拥有20年以上应用开发经验，曾在多个行业担任过不同职位。他专注于东马萨诸塞地区的公司合同服务，并于Packt Publishing出版过《R for Data Science》和《Learning Jupyter》等书籍。 - Jesse Bacon，居住并工作于北弗吉尼亚地区的业余程序员，拥有10年以上的技术专业服务经验，对Jupyter的兴趣始于学术阶段。
Jupyter has emerged as a popular tool for code exposition and the sharing of research artefacts. It is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Some of its uses includes data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and more. To perform a variety of data science tasks with Jupyter, you'll need some prior programming experience in either Python or R and a basic understanding of Jupyter. This comprehensive 2-in-1 course teaches you how to perform your day-to-day data science tasks with Jupyter. It's a perfect blend of concepts and practical examples which makes it easy to understand and implement. It follows a logical flow where you will be able to build on your understanding of the different Jupyter features with every section. This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible. The first course, Jupyter for Data Science,starts off with an introduction to Jupyter concepts and installation of Jupyter Notebook. You will then learn to perform various data science tasks such as data analysis, data visualization, and data mining with Jupyter. You will also learn how Python 3, R, and Julia can be integrated with Jupyter for various data science tasks. Next, you will perform statistical modelling with Jupyter. You will understand various machine learning concepts and their implementation in Jupyter. The second course, Jupyter In Depth, will walk you through the core modules and standard capabilities of the console, client, and notebook server. By exploring the Python language, you will be able to get starter projects for configurations management, file system monitoring, and encrypted backup solutions for safeguarding their data. You will learn to build dashboards in a Jupyter notebook to report back information about the project and the status of various Jupyter components. By the end of this training program, you'll comfortably leverage the power of Jupyter to perform various data science tasks efficiently. Meet Your Expert(s): We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth: ● Dan Toomey has been developing applications for over 20 years. He has worked in a variety of industries and companies of all sizes, in roles from sole contributor to VP/CTO level. For the last 10 years or so, he has been contracting companies in the eastern Massachusetts area under Dan Toomey Software Corp. Dan has also written R for Data Science and Learning Jupyter with Packt Publishing. ● Jesse Bacon is a hobbyist programmer that lives and works in the northern Virginia area. His interest in Jupyter started academically while working through books available from Packt Publishing. Jesse has over 10 years of technical professional services experience and has worked primarily in logging and event management.
