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所在平台: Udemy |
课程主页: https://www.udemy.com/course/learndata/
课程评论：没有评论
Coursera 课程《数据与数据分析入门指南》（SF Data School 提供）旨在为初学者提供一个全面且实用的数据领域导论。该课程填补了许多初学者在开始学习数据分析时所缺失的“分析情境”空白，并附赠免费的《数据基础手册》，作为视频内容的书面补充。 课程内容始于数据世界的引入，强调了在接触任何数据工具之前，理解数据背后的背景和语境至关重要。随后，课程将深入探讨数据分析（Data Analytics）、数据科学（Data Science）和数据工程（Data Engineering）之间的区别，以及各角色如何创造价值。此外，学员还将了解专业人士常用的数据工具，包括它们的流行度、适用场景以及协作使用方式。 接着，课程将讲解数据生命周期中的技术流程，帮助学员理解数据管道（Data Pipeline）的概念，并建立关于数据如何从收集到分析的数据迁移过程的词汇和读写能力。 最后，课程提供了一个成为数据分析实践者的学习路线图，包括完成本课程后的推荐步骤以及最相关职业发展路径。该课程承诺在约90分钟内，帮助学员从零开始，建立起对数据世界的真正理解，这是基于作者十余年经验构建的视角。该课程是初学者开始数据之旅的理想起点。
The inspiration for building this course is right in the title - it's the Analytics Context We Wish We Had, When We First Started.This course now includes free access to our Data Fundamentals Handbook, which compliments all the video content in this course in written form.This course starts with an introduction to the world of data. Context is critical, and it most definitely applies to learning how to work with data. Before even touching a data tool, amongst many other things, we believe it's vital that one fully understands the context surrounding data.From there you'll delve deep in to the differences between Data Analytics, Data Science, and Data Engineering, and how each of these roles provide value in their own way. In addition, you'll gather a deep understanding of the tools used by professionals - which are the most popular, when one would be preferred over another, and how they can be used in collaboration.Next, you'll learn about the technical processes that encompass the lineage of data. This section will enable you to internalize the concept of a Data Pipeline, and start building-up a lexicon and literacy for how data moves from collection to analysis.Finally, you'll see a step-by-step learning roadmap to become a practitioner of Data Analytics. In this section you'll gain access to recommended steps to take after this course, and career paths that are most relevant.One of the biggest challenges in getting started with data is finding the right place to start, we believe this is it. You are 90 minutes away from truly understanding the world of data - a perspective we've built over a decade of experience.
