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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-literacy-understanding-data-in-the-digital-age/
课程评论：没有评论
**数据素养：理解数字时代的数据** **课程概述** 欢迎学习 Miuul 的“数据素养”课程。本课程旨在赋能您掌握理解和有效处理数据的基本技能。在一个日益由数据驱动的世界中，阅读、分析和沟通数据的能力已成为每个人的必备技能。无论您是学生、职场人士，还是希望通过数据提升决策和解决问题能力的人，本课程都将是您的理想选择。 **课程内容** * **理解数据素养：** 掌握数据素养的含义及其在当今数据驱动世界中的关键作用。 * **核心概念：** 学习总体与样本、观测单位、变量类型和尺度类型等基础概念。 * **集中趋势和离散度测量：** 深入理解均值、中位数、众数和四分位数等概念，并通过极差、标准差、方差、偏度和峰度探索数据的变异性。 * **统计思维：** 通过数据描述、组织、简化、表示、分析和解释等模块，培养统计思维。 **为何选择本课程** * **MiuulBacked：** 本课程由 Miuul 创建，Miuul 是一家创新的教育科技公司，专注于为未来就业做好人才准备。Miuul 不仅提供教育，还为数据科学项目提供咨询服务，确保课程的现实意义和内容的及时性。 * **为初学者设计：** 无需任何统计学或数据处理的先修知识。 * **全面学习：** 涵盖数据素养的所有基础方面，助您为更高级的学习或专业任务做好准备。
Welcome to Miuul's "Data Literacy," a course designed to empower you with the fundamental skills needed to understand and work with data effectively. As we navigate a world increasingly driven by data, the ability to read, analyze, and communicate data is becoming an essential skill for everyone. This course is perfect for students, professionals, or anyone looking to enhance their decision-making and problem-solving abilities through data.What You'll LearnUnderstanding Data Literacy: Grasp what data literacy means and why it is critical in today's data-driven world.Core Concepts: Learn about population and sample, observation units, variable types, and scale types.Measures of Central Tendency and Dispersion: Dive deep into concepts like mean, median, mode, and quartiles, and explore variability through range, standard deviation, variance, skewness, and kurtosis.Statistical Thinking: Develop a statistical mindset with modules on data description, organization, reduction, representation, analysis, and interpretation.Why Choose This CourseBacked by Miuul: This course is created by Miuul, an innovative education and technology company with a focus on preparing individuals for the jobs of the future. Miuul not only educates but also provides consultancy services for data science projects, ensuring real-world relevance and updated curricula.Designed for Beginners: No prior experience with statistics or data handling is required.Comprehensive Learning: Covers all foundational aspects of data literacy to prepare you for more advanced studies or professional tasks.
