Exploratory Data Analysis with MATLAB

所在平台: CourseraArchive

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大学或机构: CourseraNew

课程主页: https://www.coursera.org/archive/exploratory-data-analysis-matlab

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课程大纲

Introduction to the Data Science Workflow
Importing Data
Visualizing and Filtering Data
Performing Calculations
Documenting Your Work

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课程详情

In this course, you will learn to think like a data scientist and ask questions of your data. You will use interactive features in MATLAB to extract subsets of data and to compute statistics on groups of related data. You will learn to use MATLAB to automatically generate code so you can learn syntax as you explore. You will also use interactive documents, called live scripts, to capture the steps of your analysis, communicate the results, and provide interactive controls allowing others to experiment by selecting groups of data. These skills are valuable for those who have domain knowledge and some exposure to computational tools, but no programming background is required. To be successful in this course, you should have some knowledge of basic statistics (e.g., histograms, averages, standard deviation, curve fitting, interpolation). By the end of this course, you will be able to load data into MATLAB, prepare it for analysis, visualize it, perform basic computations, and communicate your results to others. In your last assignment, you will combine these skills to assess damages following a severe weather event and communicate a polished recommendation based on your analysis of the data. You will be able to visualize the location of these events on a geographic map and create sliding controls allowing you to quickly visualize how a phenomenon changes over time.

使用MATLAB进行探索性数据分析:在本课程中,您将学会像数据科学家一样思考,并提出有关数据的问题。您将在MATLAB中使用交互式功能来提取数据子集并计算相关数据组的统计信息。您将学习使用MATLAB自动生成代码,以便在探索时学习语法。您还将使用称为实时脚本的交互式文档来捕获分析步骤,交流结果并提供交互式控件,允许其他人通过选择数据组进行实验。 这些技能对于那些具有领域知识并且对计算工具有所了解的人来说非常有价值,但是不需要编程背景。要在本课程中取得成功,您应该具有一些基本的统计知识(例如直方图,平均值,标准差,曲线拟合,插值)。 在本课程结束时,您将能够将数据加载到MATLAB中,为进行分析做准备,对其进行可视化,执行基本计算,并将结果传达给其他人。在上一次作业中,您将结合这些技能来评估严重天气事件后的损失,并根据对数据的分析传达出详尽的建议。您将能够在地理地图上可视化这些事件的位置,并创建滑动控件,使您可以快速可视化现象随时间的变化。

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