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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-science-101-python-plus-excel/
课程评论：没有评论
课程名称：数据科学基础：Python与Excel结合 课程概述： 在工作专业人士中，Excel因其广泛的功能和易用性，长期以来一直是不可或缺的工具。它在商业、教育、金融和研究等各个领域中，扮演着重要角色。随着近些年Python编程语言的崛起，其需求在过去一年中增长了27.6%，且趋势仍在持续。Python自问世以来，就在网页开发、数据分析和基础设施管理等领域中发挥着先驱作用。 对于许多重复性工作，Python可以极大地提升效率。例如，当需要为10,000名员工在某网站上创建账户时，手动操作显然既耗时又繁琐。数据录入工作者通常需要将各种数据从表格（如Excel或Google Sheet）提取并输入到数据库中，这一过程容易产生疲惫感与效率低下。 为此，该课程提供了一种解决方案，通过Python编程语言来自动化这些繁复的任务。学习者只需花费一小时编写代码，便可实现工作自动化，从而简化生活，提升效率。 课程内容包括： 1. Excel基础知识 2. Excel函数 3. Excel可视化 4. Excel案例研究（财务报表） 5. Python的numpy和pandas库 6. Python实现Excel函数 7. Python的matplotlib和pandas可视化 证据表明，Excel和Python在特定应用中各有其用处。Excel是一个优秀的入门级工具，适合快速分析数据。然而，在处理大数据集及复杂分析与自动化时，Python所提供的工具、技术和处理能力是Excel所无法比拟的。Python更为强大、快速，适用于更深入的数据分析，并且拥有更为广泛和协作的支持系统。 因此，掌握Python已成为有志于数据分析、数据科学以及科学领域工作的必备技能，学习这个课程的时机正是现在。
For many years, and for good reason, Excel has been a staple for working professionals. It is essential in all facets of business, education, finance, and research due to its extensive capabilities and simplicity of use.Over the past few years, python programming language has become more popular. According to one study, the demand for Python expertise has grown by 27.6 % over the past year and shows no indications of slowing down. Python has been a pioneer in web development, data analysis, and infrastructure management since it was first developed as a tool to construct scripts that "automate the boring stuff."Why python is important for automation?Consider being required to create accounts on a website for 10,000 employees. What do you think? Performing this operation manually and frequently will eventually drive you crazy. It will also take too long, which is not a good idea.Try to consider what it's like for data entry workers. They take the data from tables (like those in Excel or Google Sheets) and insert it elsewhere.They read various magazines and websites, get the data there, and then enter it into the database. Additionally, they must perform the calculations for the entries.In general, this job's performance determines how much money is made. Greater entry volume, more pay (of course, everyone wants a higher salary in their job).However, don't you find doing the same thing over and over boring?The question is now, "How can I accomplish it quickly?"How to automate my work?Spend an hour coding and automating these kinds of chores to make your life simpler rather than performing these kinds of things by hand. By just writing fewer lines of Python code, you can automate your strenuous activity.The course covers following topics:1. Excel basics2. Excel Functions3. Excel Visualizations4. Excel Case study (Financial Statements)5. Python numpy and pandas6. Python Implementations of Excel functions7. Python matplotlib and pandas visualizationsThe evidence suggests that both Excel and Python have their place with certain applications. Excel is a great entry-level tool and is a quick-and-easy way to analyze a dataset.But for the modern era, with large datasets and more complex analytics and automation, Python provides the tools, techniques and processing power that Excel, in many instances, lacks. After all, Python is more powerful, faster, capable of better data analysis and it benefits from a more inclusive, collaborative support system.Python is a must-have skill for aspiring data analysts, data scientist and anyone in the field of science, and now is the time to learn.
