关于此 专项课程

14,444 次近期查看
Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions. The Data Analysis and Interpretation Specialization takes you from data novice to data expert in just four project-based courses. You will apply basic data science tools, including data management and visualization, modeling, and machine learning using your choice of either SAS or Python, including pandas and Scikit-learn. Throughout the Specialization, you will analyze a research question of your choice and summarize your insights. In the Capstone Project, you will use real data to address an important issue in society, and report your findings in a professional-quality report. You will have the opportunity to work with our industry partners, DRIVENDATA and The Connection. Help DRIVENDATA solve some of the world's biggest social challenges by joining one of their competitions, or help The Connection better understand recidivism risk for people on parole in substance use treatment. Regular feedback from peers will provide you a chance to reshape your question. This Specialization is designed to help you whether you are considering a career in data, work in a context where supervisors are looking to you for data insights, or you just have some burning questions you want to explore. No prior experience is required. By the end you will have mastered statistical methods to conduct original research to inform complex decisions.
学生职业成果
50%
完成此 专项课程 后开始了新的职业。
17%
加薪或升职。

可分享的证书

完成后获得证书

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。

初级

完成时间大约为7 个月

建议 4 小时/周

英语(English)

字幕:英语(English), 韩语, 德语(German)
学生职业成果
50%
完成此 专项课程 后开始了新的职业。
17%
加薪或升职。

可分享的证书

完成后获得证书

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。

初级

完成时间大约为7 个月

建议 4 小时/周

英语(English)

字幕:英语(English), 韩语, 德语(German)

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

课程 1

数据管理与可视化

4.4
725 个评分
200 条评论
课程2

课程 2

数据分析工具

4.5
352 个评分
77 条评论
课程3

课程 3

回归建模实践

4.4
242 个评分
48 条评论
课程4

课程 4

使用机器学习进行数据分析

4.2
237 个评分
51 条评论

提供方

卫斯连大学 徽标

卫斯连大学

其中一位行业合作伙伴的徽标其中一位行业合作伙伴的徽标

审阅

来自数据分析和解释的热门评论

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。

  • No, Specializations are a premium product, and learners must pay or apply for financial aid to join them. You can access individual course content for free by searching for the course title in the catalog and choosing the This Course Only option when enrolling. You will not earn a Certificate in the free version of the course, or be able to access the Capstone Project.

  • 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. The Capstone Project will be offered four times per year on a recurring schedule.

  • 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 access and manage data using either the Python or SAS programming language, explore patterns and associations among variables, and use machine learning methods to develop predictive algorithms. Additionally, you will have a portfolio of hands-on project work that demonstrates your ability to apply all of these methods to real-world situations.

  • You may choose to use either Python or SAS to complete the assignments. Both of these software packages are being made freely available.

  • This Specialization is appropriate for anyone interested in learning more about data analysis, including those new to the field. Some knowledge of basic programming and familiarity with linear algebra concepts may be helpful, but no specific background is required.

还有其他问题吗?请访问 学生帮助中心