关于此 专项课程
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尝试观看 ASU MCS 学位 学位的课程视频、阅读课程以及完成自主学习作业

100% 在线课程

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灵活的计划

设置并保持灵活的截止日期。

中级

完成时间大约为3 个月

建议 8 小时/周

英语(English)

字幕:英语(English)

开始攻读学位

尝试观看 ASU MCS 学位 学位的课程视频、阅读课程以及完成自主学习作业

100% 在线课程

立即开始,按照自己的计划学习。

灵活的计划

设置并保持灵活的截止日期。

中级

完成时间大约为3 个月

建议 8 小时/周

英语(English)

字幕:英语(English)

专项课程 的运作方式

加入课程

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实践项目

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获得证书

在结束每门课程并完成实践项目之后,您会获得一个证书,您可以向您的潜在雇主展示该证书并在您的职业社交网络中分享。

how it works

此专项课程包含 4 门课程

课程1

Introduction to Data Exploration and Visualization

3.2
13 个评分
6 个审阅

This course answers the questions, What is data visualization and What is the power of visualization? It also introduces core concepts such as dataset elements, data warehouses and exploratory querying, and combinations of visual variables for graphic usefulness, as well as the types of statistical graphs, —tools that are essential to exploratory data analysis.

...
课程2

Multivariate and Geographical Data Analysis

Covering the tools and techniques of both multivariate and geographical analysis, this course provides hands-on experience visualizing data that represents multiple variables. This course will use statistical techniques and software to develop and analyze geographical knowledge.

...
课程3

Temporal and Hierarchical Data Analysis

—Data repositories in which cases are related to subcases are identified as hierarchical. This course covers the representation schemes of hierarchies and algorithms that enable analysis of hierarchical data, as well as provides opportunities to apply several methods of analysis.

...
课程4

Additional Tools Used for Data Visualization

This course will expose learners to additional tools that can be used to perform Data Visualization. In particular, the courses focuses on Tableau, a state-of-the-art visualization package. In this course, the visualization concepts from previous courses are reinforced and the Tableau software is introduced through replication of the visualizations built in previous courses.

...

讲师

Avatar

Ross Maciejewsk

Associate Professor at Arizona State University in the School of Computing, Informatics & Decision Systems Engineering and Director of the Center for Accelerating Operational Efficiency
School of Computing, Informatics & Decision Systems Engineering
Avatar

K. Selcuk Candan

Professor of Computer Science and Engineering
Director of ASU’s Center for Assured and Scalable Data Engineering (CASCADE)
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Huan Liu

Professor: Computer Science and Engineering
School of Computing, Informatics, and Decision Systems Engineering (CASCADE)

领先获取学位

此 专项课程 隶属于 亚利桑那州立大学 提供的 100% 在线 Master of Computer Science。立即开始学习开放课程或专项课程,观看 iMBA 教师的课程并完成自主学习作业。 完成每门课程后,您将获得一个证书,您可以添加到 LinkedIn 和简历中。 如果申请并被录取参加全部课程,您的课程将计入您的学位学习进程。

关于 亚利桑那州立大学

Arizona State University has developed a new model for the American Research University, creating an institution that is committed to excellence, access and impact. ASU measures itself by those it includes, not by those it excludes. ASU pursues research that contributes to the public good, and ASU assumes major responsibility for the economic, social and cultural vitality of the communities that surround it....

常见问题

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  • 此课程完全在线学习,无需到教室现场上课。您可以通过网络或移动设备随时随地访问课程视频、阅读材料和作业。

  • Time to completion can vary based on your schedule and experience level, most individual courses, in which this Specialization has 4, will take about a month to complete if you devote 2-5 hours per week.

  • Basic statistics and computer science knowledge including computer organization and architecture, discrete mathematics, data structures, and algorithms

    Knowledge of high-level programming languages (e.g., C++, Java) and scripting language (e.g., Python), Jupyter Notebooks

  • No, courses may be taken in any order.

  • All courses in this Specialization form the lecture and skill practice component of a corresponding course in ASU’s online Master of Computer Science Degree. You can apply to the degree program either before or after you begin the Specialization.

  • Learners completing this specialization will be able to:

    Develop exploratory data analysis and visualization tools using Python and Jupyter notebooks

    Apply design principles for a variety of statistical graphics and visualizations including scatterplots, line charts, histograms, and choropleth maps

    Combine exploratory queries, graphics, and interaction to develop functional tools for exploratory data analysis and visualization

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