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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-project-fundamentals/
课程评论：没有评论
课程名称：数据项目基础知识：成功的技能与技巧 课程概述：本课程旨在强调使您成为全面数据专业人士的关键技能。您将学习数据项目各个逻辑阶段所涉及的技术、挑战和方法。课程内容包括数据概况分析、数据映射与转换、开发、数据建模、数据解决方案设计、软件设计、单元测试和故障排除。课程将遵循项目的自然生命周期，通过讲座、屏幕录制、测验和练习来进行展示。课程将使用实际零售数据，结合Python和Jupyter Notebooks来演示技术。虽然使用了Jupyter Notebooks，但课程的重点并不在于某些技术如何深入实现，而在于理解这些技术以及它们在整个过程中为何至关重要。因此，尽管动手实践部分会增强课程体验，但不是先决条件，您也可以通过其他软件来进行相关操作。最终，本课程旨在弥补专注于特定编程、数据分析技能或数据建模技能课程之间的空白。它可以帮助您更好地理解并批判性地质疑当前的数据环境。我相信本课程提供了不同的视角，让您在全力投入数据相关任务之前，可以先进行深思。对数据项目的更全面的理解将使您成为更优秀、更全面的数据专业人士。祝您学习愉快！
This course aims to highlight the key skills that will make you stand out as a rounded Data Professional. You will cover the techniques, challenges and approaches undertaken in each of the logical stages of a data project. You will cover Data Profiling; Data Mapping and Transformation; Development; Data Modelling; Data Solution Design; Software Design; Unit Testing and Troubleshooting. The course aims to follow the natural life-cycle of a project.These topics will be demonstrated by a mixture of lectures, screencasts, quizzes and exercises. Practical retail data will bring it all to life with Python and Jupyter Notebooks used to illustrate the techniques. Although Jupyter notebooks are used, a running them in the course is that it is not important how certain techniques are done, but that these techniques are understood and why they form a key part of the process. So although the hands-on sections will definitely enhance the course experience they are not a prerequisite, and could also be tackled using alternative software.Ultimately this course aims to fill the gaps between courses focused on specific programming, data analysis skills or data modelling skills. It should allow you to appreciate but also critically question your current data environment. I believe this course offers something different and will make you stand back and think before heading full-steam into a data-related task. This more complete understanding of Data Projects will make you a better, more rounded Data Professional. Enjoy!
