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所在平台: Coursera专项课程 |
课程主页: https://www.coursera.org/specializations/total-data-quality
课程评论：没有评论
课程名称：全面数据质量 概述：本专业旨在深入探讨全面数据质量框架，帮助学习者了解在数据分析之前需要进行的数据质量评估。课程的目标是让学习者在所有项目中将数据质量评估作为关键环节进行整合，特别针对数据科学家和定量分析师，弥补他们在数据收集和数据质量评估初步步骤中的培训不足。整个课程将强调科学调查的基础步骤，包括数据生成或收集、理解数据来源、评估数据质量，以及在进行任何统计分析或应用数据科学技术之前最大程度地提升数据质量。 学习内容：学习者将在此课程中通过专家访谈、互动讲座、软件概念的现场演示和案例研究获得全面的数据质量框架的知识与技能。此外，课程还包括实际评估，以巩固概念与强化关键思想。 证书：完成课程后，学习者将获得可分享的证书。课程为100%在线，可随时开始并根据个人日程灵活学习。 适合人群：本课程适合初学者，无需任何先前经验。预计课程完成时间为3个月，建议每周学习3小时。 可用语言：英语，提供英文字幕。 课程链接： - [全面数据质量框架](https://www.coursera.org/learn/the-total-data-quality-framework) - [测量全面数据质量](https://www.coursera.org/learn/measuring-total-data-quality) - [优化全面数据质量的设计策略](https://www.coursera.org/learn/design-strategies-for-maximizing-total-data-quality)
Course Link: https://www.coursera.org/learn/the-total-data-quality-framework
Name:The Total Data Quality Framework
Description:Offered by University of Michigan. By the end of this first course in the Total Data Quality specialization, learners will be able to: 1. ... Enroll for free.
Course Link: https://www.coursera.org/learn/measuring-total-data-quality
Name:Measuring Total Data Quality
Description:Offered by University of Michigan. By the end of this second course in the Total Data Quality Specialization, learners will be able to: 1. ... Enroll for free.
Course Link: https://www.coursera.org/learn/design-strategies-for-maximizing-total-data-quality
Name:Design Strategies for Maximizing Total Data Quality
Description:Offered by University of Michigan. By the end of this third course in the Total Data Quality Specialization, learners will be able to: 1. ... Enroll for free.
About this Specialization
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This specialization aims to explore the Total Data Quality framework in depth and provide learners with more information about the detailed evaluation of total data quality that needs to happen prior to data analysis. The goal is for learners to incorporate evaluations of data quality into their process as a critical component for all projects. We sincerely hope to disseminate knowledge about total data quality to all learners, such as data scientists and quantitative analysts, who have not had sufficient training in the initial steps of the data science process that focus on data collection and evaluation of data quality. We feel that extensive knowledge of data science techniques and statistical analysis procedures will not help a quantitative research study if the data collected/gathered are not of sufficiently high quality.
This specialization will focus on the essential first steps in any type of scientific investigation using data: either generating or gathering data, understanding where the data come from, evaluating the quality of the data, and taking steps to maximize the quality of the data prior to performing any kind of statistical analysis or applying data science techniques to answer research questions. Given this focus, there will be little material on the analysis of data, which is covered in myriad existing Coursera specializations. The primary focus of this specialization will be on understanding and maximizing data quality prior to analysis.
Applied Learning Project
Learners will gain valuable and applicable knowledge and skills about the Total Data Quality framework from interviews with leading experts in this area, engaging lectures, live demonstrations of concepts using software and case studies, and will complete practical assessments to solidify concepts and reinforce essential ideas.
Shareable Certificate
Shareable Certificate
Earn a Certificate upon completion
100% online courses
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
Beginner Level
No prior experience required.
Hours to complete
Approximately 3 months to complete
Suggested pace of 3 hours/week
Available languages
English
Subtitles: English
Shareable Certificate
Shareable Certificate
Earn a Certificate upon completion
100% online courses
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
Beginner Level
No prior experience required.
Hours to complete
Approximately 3 months to complete
Suggested pace of 3 hours/week
Available languages
English
Subtitles: English
