关于此 专项课程
100% 在线课程

100% 在线课程

立即开始,按照自己的计划学习。
灵活的计划

灵活的计划

设置并保持灵活的截止日期。
初级

初级

完成时间(小时)

完成时间大约为8 个月

建议 4 小时/周
可选语言

英语(English)

字幕:英语(English), 阿拉伯语(Arabic), 中文(简体), 韩语, 俄语(Russian)...

您将获得的技能

Binary ClassificationData AnalysisTableau SoftwareSQL
100% 在线课程

100% 在线课程

立即开始,按照自己的计划学习。
灵活的计划

灵活的计划

设置并保持灵活的截止日期。
初级

初级

完成时间(小时)

完成时间大约为8 个月

建议 4 小时/周
可选语言

英语(English)

字幕:英语(English), 阿拉伯语(Arabic), 中文(简体), 韩语, 俄语(Russian)...

专项课程 的运作方式

加入课程

Coursera 专项课程是帮助您掌握一门技能的一系列课程。若要开始学习,请直接注册专项课程,或预览专项课程并选择您要首先开始学习的课程。当您订阅专项课程的部分课程时,您将自动订阅整个专项课程。您可以只完成一门课程,您可以随时暂停学习或结束订阅。访问您的学生面板,跟踪您的课程注册情况和进度。

实践项目

每个专项课程都包括实践项目。您需要成功完成这个(些)项目才能完成专项课程并获得证书。如果专项课程中包括单独的实践项目课程,则需要在开始之前完成其他所有课程。

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 5 门课程

课程1

Business Metrics for Data-Driven Companies

4.5
4,732 个评分
961 个审阅
In this course, you will learn best practices for how to use data analytics to make any company more competitive and more profitable. You will be able to recognize the most critical business metrics and distinguish them from mere data. You’ll get a clear picture of the vital but different roles business analysts, business data analysts, and data scientists each play in various types of companies. And you’ll know exactly what skills are required to be hired for, and succeed at, these high-demand jobs. Finally, you will be able to use a checklist provided in the course to score any company on how effectively it is embracing big data culture. Digital companies like Amazon, Uber and Airbnb are transforming entire industries through their creative use of big data. You’ll understand why these companies are so disruptive and how they use data-analytics techniques to out-compete traditional companies....
课程2

Mastering Data Analysis in Excel

4.2
2,695 个评分
608 个审阅
Important: The focus of this course is on math - specifically, data-analysis concepts and methods - not on Excel for its own sake. We use Excel to do our calculations, and all math formulas are given as Excel Spreadsheets, but we do not attempt to cover Excel Macros, Visual Basic, Pivot Tables, or other intermediate-to-advanced Excel functionality. This course will prepare you to design and implement realistic predictive models based on data. In the Final Project (module 6) you will assume the role of a business data analyst for a bank, and develop two different predictive models to determine which applicants for credit cards should be accepted and which rejected. Your first model will focus on minimizing default risk, and your second on maximizing bank profits. The two models should demonstrate to you in a practical, hands-on way the idea that your choice of business metric drives your choice of an optimal model. The second big idea this course seeks to demonstrate is that your data-analysis results cannot and should not aim to eliminate all uncertainty. Your role as a data-analyst is to reduce uncertainty for decision-makers by a financially valuable increment, while quantifying how much uncertainty remains. You will learn to calculate and apply to real-world examples the most important uncertainty measures used in business, including classification error rates, entropy of information, and confidence intervals for linear regression. All the data you need is provided within the course, all assignments are designed to be done in MS Excel, and you will learn enough Excel to complete all assignments. The course will give you enough practice with Excel to become fluent in its most commonly used business functions, and you’ll be ready to learn any other Excel functionality you might need in the future (module 1). The course does not cover Visual Basic or Pivot Tables and you will not need them to complete the assignments. All advanced concepts are demonstrated in individual Excel spreadsheet templates that you can use to answer relevant questions. You will emerge with substantial vocabulary and practical knowledge of how to apply business data analysis methods based on binary classification (module 2), information theory and entropy measures (module 3), and linear regression (module 4 and 5), all using no software tools more complex than Excel....
课程3

Data Visualization and Communication with Tableau

4.7
1,759 个评分
380 个审阅
One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. Even the most sophisticated statistical analyses are not useful to a business if they do not lead to actionable advice, or if the answers to those business questions are not conveyed in a way that non-technical people can understand. In this course you will learn how to become a master at communicating business-relevant implications of data analyses. By the end, you will know how to structure your data analysis projects to ensure the fruits of your hard labor yield results for your stakeholders. You will also know how to streamline your analyses and highlight their implications efficiently using visualizations in Tableau, the most popular visualization program in the business world. Using other Tableau features, you will be able to make effective visualizations that harness the human brain’s innate perceptual and cognitive tendencies to convey conclusions directly and clearly. Finally, you will be practiced in designing and persuasively presenting business “data stories” that use these visualizations, capitalizing on business-tested methods and design principles....
课程4

Managing Big Data with MySQL

4.7
2,111 个评分
475 个审阅
This course is an introduction to how to use relational databases in business analysis. You will learn how relational databases work, and how to use entity-relationship diagrams to display the structure of the data held within them. This knowledge will help you understand how data needs to be collected in business contexts, and help you identify features you want to consider if you are involved in implementing new data collection efforts. You will also learn how to execute the most useful query and table aggregation statements for business analysts, and practice using them with real databases. No more waiting 48 hours for someone else in the company to provide data to you – you will be able to get the data by yourself! By the end of this course, you will have a clear understanding of how relational databases work, and have a portfolio of queries you can show potential employers. Businesses are collecting increasing amounts of information with the hope that data will yield novel insights into how to improve businesses. Analysts that understand how to access this data – this means you! – will have a strong competitive advantage in this data-smitten business world....

讲师

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Daniel Egger

Executive in Residence and Director, Center for Quantitative Modeling
Pratt School of Engineering, Duke University
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Jana Schaich Borg

Assistant Research Professor
Social Science Research Institute

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关于 Duke University

Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world....

常见问题

  • 可以!点击您感兴趣的课程卡开始注册即可。注册并完成课程后,您可以获得可共享的证书,或者您也可以旁听该课程免费查看课程资料。如果您订阅的课程是某专项课程的一部分,系统会自动为您订阅完整的专项课程。访问您的学生面板,跟踪您的进度。

  • 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。

  • 此专项课程不提供大学学分,但部分大学可能会选择接受专项课程证书作为学分。查看您的合作院校了解详情。

  • Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in 6-7 months.

  • Each course in the Specialization is offered on a regular schedule, with sessions starting about once per month. If you don't complete a course on the first try, you can easily transfer to the next session, and your completed work and grades will carry over.

  • No prior experience with analytics or programming is required. This Specialization is intended for anyone with an interest in data analysis and its applications in business decision-making.

  • We recommend taking the courses in the order presented, as each subsequent course will build on material from previous courses.

  • Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • You will be able to frame practical business questions that can be answered with data, visualize analytical insights in an informative and compelling fashion, and translate and persuasively communicate insights into actionable recommendations for decision-makers.

  • You will need access to Microsoft Excel 2007 (or a more recent version of Microsoft Excel). We will be using the free Solver plugin for optimization problems, and this functionality is not available in alternative online tools such as Google Sheets. The Specialization will also make use of freely-downloadable software packages such as Tableau.

  • Yes! We will teach you all the analytical and software tools you need to succeed not only in this class, but also as a business analyst.

  • Yes. Our goal is to give you tools to help you navigate business data analyses of all kinds, even if you have never worked with that type of data before or do not have experience with the associated type of business.

  • Yes. In fact, chances are high that you have never seen the majority of the content in this class. Applying quantitative skills to business contexts requires software, skills, and domain knowledge you are not likely to have been exposed to in graduate school.

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