SQL for Data Science Capstone Project

开始时间: 08/01/2020 持续时间: Unknown

所在平台: Coursera

课程类别: 其他类别

大学或机构: CourseraNew

   

课程主页: https://www.coursera.org/learn/sql-data-science-capstone

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课程详情

Data science is a dynamic and growing career field that demands knowledge and skills-based in SQL to be successful. This course is designed to provide you with a solid foundation in applying SQL skills to analyze data and solve real business problems. Whether you have successfully completed the other courses in the Learn SQL Basics for Data Science Specialization or are taking just this course, this project is your chance to apply the knowledge and skills you have acquired to practice important SQL querying and solve problems with data. You will participate in your own personal or professional journey to create a portfolio-worthy piece from start to finish. You will choose a dataset and develop a project proposal. You will explore your data and perform some initial statistics you have learned through this specialization. You will uncover analytics for qualitative data and consider new metrics that make sense from the patterns that surface in your analysis. You will put all of your work together in the form of a presentation where you will tell the story of your findings. Along the way, you will receive feedback through the peer-review process. This community of fellow learners will provide additional input to help you refine your approach to data analysis with SQL and present your findings to clients and management.

用于数据科学的SQL顶点项目:数据科学是一个动态且不断发展的职业领域,需要基于SQL的知识和技能才能成功。本课程旨在为您提供扎实的基础,以应用SQL技能来分析数据和解决实际的业务问题。 无论您是否已成功完成“学习SQL数据科学基础知识”专业中的其他课程,还是仅参加本课程,此项目都是您利用您所学到的知识和技能来练习重要的SQL查询和解决数据问题的机会。您将参与自己的个人或专业之旅,从头到尾制作一份有价值的作品。您将选择一个数据集并制定项目建议。您将探索您的数据并执行通过该专业知识所学到的一些初始统计信息。您将发现有关定性数据的分析,并考虑从分析中浮现出的模式有意义的新指标。您将以演示文稿的形式将所有工作放在一起,在其中讲述您的发现的故事。在此过程中,您将通过同行评审过程收到反馈。这个由学习者共同组成的社区将提供其他投入,以帮助您完善使用SQL进行数据分析的方法,并将发现的结果呈现给客户和管理层。

课程大纲

Getting Started and Milestone 1: Project Proposal and Data Selection/Preparation
Milestone 2: Descriptive Stats & Understanding Your Data
Milestone 3: Beyond Descriptive Stats (Dive Deeper/Go Broader)
Milestone 4: Presenting Your Findings (Storytelling)

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