数据分析

数据分析课程介绍管理和分析大规模数据的方法。您将学习数据挖掘、大数据应用以及数据产品开发,成为一名数据科学家。

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Introduction to Data Science
IBM
Introduction to Data Science
专项课程
Data Science
Johns Hopkins University
Data Science
专项课程
Excel Skills for Business
Macquarie University
Excel Skills for Business
专项课程
Data Science: Foundations using R
Johns Hopkins University
Data Science: Foundations using R
专项课程
商业分析
University of Pennsylvania
商业分析
专项课程
Applied Data Science with Python
University of Michigan
Applied Data Science with Python
专项课程
从 Excel 到 MySQL:商业分析技术
Duke University
从 Excel 到 MySQL:商业分析技术
专项课程
Data Analysis and Presentation Skills: the PwC Approach
PwC
Data Analysis and Presentation Skills: the PwC Approach
专项课程
Search Engine Optimization (SEO)
University of California, Davis
Search Engine Optimization (SEO)
专项课程
AI Foundations for Everyone
IBM
AI Foundations for Everyone
专项课程
Learn SQL Basics for Data Science
University of California, Davis
Learn SQL Basics for Data Science
专项课程
Data Visualization with Tableau
University of California, Davis
Data Visualization with Tableau
专项课程
Statistics with R
Duke University
Statistics with R
专项课程
数据结构与算法
University of California San Diego
数据结构与算法
专项课程
Geographic Information Systems  (GIS)
University of California, Davis
Geographic Information Systems (GIS)
专项课程
Genomic Data Science
Johns Hopkins University
Genomic Data Science
专项课程
Advanced Data Science with IBM
IBM
Advanced Data Science with IBM
专项课程
Accelerated Computer Science Fundamentals
University of Illinois at Urbana-Champaign
Accelerated Computer Science Fundamentals
专项课程
Statistics with Python
University of Michigan
Statistics with Python
专项课程

    关于 数据分析 的常见问题

  • Data analysis is the process of applying statistical analysis and logical techniques to extract information from data. When carried out carefully and systematically, the results of data analysis can be an invaluable complement to qualitative research in producing actionable insights for decision-making.

    If that sounds a lot like data science, you’re right! It’s a closely related field, but there are important differences. Data scientists typically come from computer science and programming backgrounds and rely on coding skills to build algorithms and analytic models to automate the processing of data at scale. Data analysts typically have backgrounds in mathematics and statistics, and frequently apply these analytic techniques to answer specific business problems - for example, a financial analyst at an investment bank.