|
所在平台: Coursera |
课程主页: https://www.coursera.org/learn/data-preparation
课程评论：没有评论
课程名称：准备数据以便探索 课程概述：这是谷歌数据分析证书的第三门课程。该课程旨在帮助学员掌握申请入门级数据分析师职位所需的技能。在继续巩固前两门课程所学知识的基础上，学员将接触到新的主题，提升实际数据分析技能。课程中将教授如何使用电子表格和SQL工具提取并利用适合自身目标的数据，以及如何组织和保护数据。现任谷歌数据分析师将指导学员，提供实际操作方法，帮助完成常见数据分析任务。 完成该证书项目的学员将有能力申请入门级数据分析师职位，无需任何先前经验。 课程目标： - 了解分析师如何决定收集哪些数据用于分析。 - 学习结构化和非结构化数据、数据类型及数据格式。 - 探索如何识别数据中的不同偏见，以确保数据的可信度。 - 了解分析师如何利用电子表格和SQL进行数据库和数据集的分析。 - 检视开放数据及数据伦理与数据隐私之间的重要关系。 - 掌握如何访问数据库，提取、过滤和排序其中的数据。 - 学习组织数据和保持安全的最佳实践。 课程大纲： 1. 数据类型与结构： - 探讨我们日常生活中生成的数据，分析师如何决定收集和分析的数据类型，学习结构化和非结构化数据及其数据格式。 2. 数据责任： - 学习分析师如何识别数据中的偏见，确保数据的可信性，并探讨开放数据与数据伦理、数据隐私之间的重要关系。 3. 数据库基础： - 了解如何访问数据库，并提取、过滤和排序其中的数据，以及元数据的作用和分析师的使用方法。 4. 组织与保护数据： - 学习数据的最佳组织和安全保护实践，掌握分析师如何使用文件命名规范来保持工作有序。 5. 参与数据社区： - 探索如何管理个人的在线形象，了解与其他数据分析专业人士网络交流的好处。 该课程为想要进入数据分析领域的学员提供了全面的基础知识和必要技能。
Name: Data types and structures
Description:We all generate lots of data in our daily lives. In this part of the course, you’ll take a look at how we generate data and how analysts decide what data to collect for analysis. You’ll also learn about structured and unstructured data, data types, and data formats as you start thinking about how to prepare your data for exploration.
Name:Data responsibility
Description:When data analysts work with data, they always check that the data is unbiased and credible. In this part of the course, you’ll learn how to identify different types of bias in data and how to ensure credibility in your own data. You’ll also explore open data and the relationship between and importance of data ethics and data privacy.
Name:Database essentials
Description:When you’re analyzing data, you’ll access much of the data from a database; it’s where data lives. In this part of the course, you’ll learn all about databases, including how to access them, and how to extract, filter, and sort the data they contain. You’ll also check out metadata to discover the different types and understand how analysts use them.
Name:Organize and protect data
Description:Good organizational skills are a necessary skill for most types of work, and data analytics is no different. In this part of the course, you’ll learn best practices for organizing data and keeping it secure. You’ll also learn how analysts use file naming conventions to help them keep their work organized.
Name:Engage in the data community
Description:Having a strong online presence can be a big help for job seekers of all kinds. In this part of the course, you’ll explore how to manage your online presence. You’ll also discover the benefits of networking with other data analytics professionals.
This is the third course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. As you continue to build on your understanding of the topics from the first two courses, you’ll also be introduced to new topics that will help you gain practical data analytics skills. You’ll learn how to use tools like spreadsheets and SQL to extract and make use of the right data for your objectives and how to organize and protect your data. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources. Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary. By the end of this course, you will: - Find out how analysts decide which data to collect for analysis. - Learn about structured and unstructured data, data types, and data formats. - Discover how to identify different types of bias in data to help ensure data credibility. - Explore how analysts use spreadsheets and SQL with databases and data sets. - Examine open data and the relationship between and importance of data ethics and data privacy. - Gain an understanding of how to access databases and extract, filter, and sort the data they contain. - Learn the best practices for organizing data and keeping it secure.
