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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/analyze-data-cdsp
课程评论：没有评论
课程名称：数据分析 课程概述：本课程旨在为希望学习如何分析数据以获取洞察的商务专业人士提供指导。学员将学习使用统计分析方法探索数据的潜在分布，利用直方图、散点图和地图等可视化工具进行数据分析，并对数据进行预处理，以生成适合训练的数据集。此课程的典型学员一般拥有数年的计算机技术经验，并具备一定的计算机编程能力。 课程大纲： 1. 部分一：检查数据 描述：在之前的课程中，学员进行了数据的提取、转换和加载（ETL），以确保数据为下一阶段的数据科学过程：分析做好准备。本部分将探讨如何通过各种技术分析数据，以获取有用的洞察，并更好地了解数据需要如何进一步处理以准备进行机器学习。 2. 部分二：探索数据的潜在分布 描述：数据分析的一个关键因素是确定各个特征值的分布情况。这将使学员更深入地理解数据的表示方式，以及数据为什么需要发生变化。 3. 部分三：使用可视化分析数据 描述：在这一模块中，学员将从可视化的角度观察数据，以揭示仅靠原始数字无法提供的见解。 4. 部分四：数据预处理 描述：数据分析的努力很可能会促使学员进一步转化数据，尤其是在为机器学习做准备时。本部分将指导学员如何进行数据的进一步处理。 5. 部分五：应用所学知识 描述：学员将进行一个项目，将课程中学到的知识应用于实际场景中。 通过这一课程，学员将掌握数据分析的基本技能，提高其在商务领域的决策能力。
Part: 1
Title:Examine Data
Description:In the previous course in this specialization, you conducted extract, transform, and load (ETL) to ensure your data was ready for the next phase of the data science process: analysis. In some cases, an analysis of the data may be the actual final goal of the project, or it may be an important intermediary step on the road to machine learning. In either case, analyzing your data using various techniques will help you obtain useful insights into that data and what it represents. It'll also give you a better understanding of how the data needs to undergo more processing to prepare it for machine learning. You'll begin your analysis efforts by exploring the nature of your dataset and the relationships it contains.
Part: 2
Title:Explore the Underlying Distribution of Data
Description:One of the key factors in data analysis is determining how values are spread out within each of the different features. This will give you a deeper understanding of how the data is represented and how it might need to change.
Part: 3
Title:Use Visualizations to Analyze Data
Description:In this module, you'll look at your data from a visual perspective in order to reveal insights that raw numbers alone may not provide.
Part: 4
Title:Preprocess Data
Description:Your analysis efforts will most likely prompt you to transform your data further, especially in preparation for machine learning. In this topic, you'll do just that.
Part: 5
Title:Apply What You've Learned
Description:You'll work on a project in which you'll apply your knowledge of the material in this course to a practical scenario.
This course is designed for business professionals that want to learn how to analyze data to gain insight, use statistical analysis methods to explore the underlying distribution of data, use visualizations such as histograms, scatter plots, and maps to analyze data and preprocess data to produce a dataset ready for training. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming.
