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所在平台: Udemy |
课程主页: https://www.udemy.com/course/how-to-be-a-data-analyst-essence-of-data-analysis/
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课程名称：如何成为数据分析师：数据分析的本质 课程概述：数据分析师是一位擅长清理、变更和处理原始数据的专家，旨在提取可操作的、相关的信息，以帮助企业做出更明智的决策。数据分析是一个清理、转化和建模数据的过程，用于发现对商业决策有用的信息。根据Glassdoor的劳动统计，数据分析师的年平均薪资约为80,000美元。由于对高技能数据分析师的需求增加，薪资也相应上升。 该课程试图以一种即使没有数学背景的人也能理解的方式解释数据分析和分析，同时展示可以进行生产级数据分析的工具。成为数据分析师需要掌握数据分析的专业知识。本在线课程涵盖了数据分析中的重要主题，以及公司如何利用这些流行工具和技术在组织内做出关键决策。 课程内容包括：数据需求收集、数据收集、数据清理、数据分析、数据解读和数据可视化。此外，还涵盖了常见的统计分析方法，如均值、标准差、回归分析和假设检验。 完成此在线数据分析课程后，你应该能够： - 深入了解数据分析的最佳实践，包括数据需求收集、数据收集、数据分析、数据解读和数据可视化。 - 精通数据分析技术，如文本分析、统计分析、诊断分析、预测分析和规范性分析。 - 详细了解数据分析工具和技术、常见的统计分析方法、数据可视化的基本图表类型、可能阻碍企业发展的数据分析神话，以及使用大数据分析的公司及其数据分析的运用方式。
A Data analyst is someone who is an expert in cleaning, changing, and processing raw data in order to extract actionable, relevant information that helps businesses make more informed decisionsData analysis is a process of cleaning, transforming and modelling data to discover useful information for business decision-making.According to Glassdoor labor statistics, the average salary for data analyst is around 80,000 dollars per yearGiven the demand for highly skilled data analysts, there has been a corresponding increase in salaries too.In this course, I tried to explain data analysis and analytics in a way someone without a background in maths will understand as well as showing you the tools in which you can perform production level data analysis For you to be a Data Analyst you need to be an expert in Data AnalysisThis well-curated online course covers important topics in Data Analysis, as well how companies are making use of these popular tools and techniques to make key decisions in their organisation. Topics covered here include: Data Requirement Gathering, Data Collection, Data Cleaning, Data Analysis, Data Interpretation and Data VisualisationAlso covered are common statistical analysis methods such as Mean, Standard deviation, Regression, Hypothesis testingAfter taking this Data Analysis online course, you should be able to:Know in depth Data analysis best practises which include Data Requirement Gathering, Data collection, Data Analysis, Data Interpretation, Data VisualisationMaster Data Analysis techniques like Text Analysis, Statistical Analysis, Diagnostic Analysis, Predictive Analysis and Prescriptive AnalysisKnow in details Data Analysis Tools and Techniques, Common Statistical Analysis Methods, Essential Chart Types for Data Visualisation, Data Analysis Myths That Can Hamper Your Business, Companies That Use Big Data Analytics and How Companies Make Use Of Data Analysis
