楼主主申BA，排除到最后只剩GWU 和 UCSD，多方了解一些细节，贴出作为CD信息补充。
1.GWU: From在读学长学姐，课程很好
课程质量：她自己没和其他学校比较，觉得自己专业还不错。老师上课认真，特别课后有问题找老师，都帮你解答的很好，尤其是自己专业老师。因为第一个学期的课除了两门是数学统计相关，其他都和编程相关。有些就是programming。有些同时需要其他软件的编程。没有编程基础，花的功夫比较多. 选课：大部分人选商学院的课，但是院里也很支持你去统计，cs，还有其他专业选课。 软件：杂七杂八。主要是python，sars，r。还有sars下面一些自己的附属，jmp pro，sars enterprise minor，ampl。sars，r多用在统计的课上。有一门课专门学jmp pro。有一门叫动态优化，用ampl。一边上课，一边学用法。 讲课水平：看你自己接受程度。因为内容比较难懂，从理论讲，有些不太能理解，就需要自己课后多花时间。自学比例，本来学cs计算机，课后花的时间少一些。如果没有编程背景，第一个学期课后花的时间可能比较多。 同学：MSBA以往只有4个左右中国学生，人比较少。 掌握程度：第一个学期python比例大。要求没那么高。即使没有基础，自己下面多花时间，跟着老师，还是可以。用它写code可以做数据分析。比如数据弄到python里，会调整格式，整理数据，做相关分析。 找工作：（一位想做互联网方向DATA SCIENTIST的学长）实习经历对找工作很重要。互联网主要就业方向应该还是在ny，西雅图，加州。如果打算留美国而且想进互联网公司，建议直接去湾区的大学，san jose state，SCU之类，不要在乎宗排。 环境：华盛顿没有纽约的嘈杂，干净现代，公共交通便利，气候和北京相似。一般不住在校园所以除了上课几乎都在家。
2.UCSD：设置课程教授挺用心的 我主要对SD的课程设置上有点疑惑，写邮件问了Nijs和August两位co-director of Rady MSBA program.为什么着重在R语言？以下是两位的回信，他们主要认为一年的项目应该打好学生的基础，注重技术的extensibility and amazing foundation.应追求质而非量。同时注重对统计和编程的商业“应用”。两位教授很负责，回邮件很快很详细耐心。
1）From professor Nijs Hi Jing,
Our focus is indeed on R, but SQL and SAS will also be covered. In particular, the elective on Behavioral Finance uses SAS extensively.
I believe that by using too many different tools you cannot become REALLY good at any of them. An advantage of R is that you will be able to use it after graduation, no matter if the organization you work for happens to (also) use other tools. With SAS or Stata, if the organization doesn't have a license you will not even be able to review the materials and code you worked on during the MSBA program.
I don't know the details of the GW program. In our view, knowledge of statistics and machine learning is not sufficient to be successful. You have to know how to USE statistics and machine learning to solve real world business problems.
The MSBA program at Rady is technically sophisticated but also very much applied and focused on real world problems. If that appeals to you Rady will be a good choice.
Best,
Vincent
1）From professor August “Could you please tell me why Rady don't want to cover more practical tools?” First of all, we do cover the tools and libraries we believe are most beneficial to one’s budding career. Second, what’s even more important is building the right foundation so you can easily learn and apply the right tools for the particular business problem you encounter. That’s why our focus is on tools that are extensible (this is extremely important to the development of one’s foundation). Third, if a program’s focus is purely on learning a laundry list of tools, then you will probably be less likely to get a job. If you want an analogy, when an undergraduate student majors in computer science as an undergraduate does he learn:
Ruby on Rails, Java Server Pages, Java Servlets, JBoss administration, C##, SQL Server, MySQL, Postgres, Oracle, NoSQL, Cold Fusion, Adobe FDF, Flash programming, PHP, VBA programming, Apache, Cocoon, Struts, Spark, Hadoop, Turbine, Xerces, XML, Tapestry, Perl, Tomcat, Geronimo, C++, Android programming, iOS Frameworks, …
and the list goes on to literally thousands of technologies. The answer is a resounding “NO” because the tools that need to be used are often quite specific to the problem that is being solved, which is often specific to the role that the person takes, which is often specific to the organization the person works for and the industry it lies within. The best outcome for a student is to have a program like ours teach them an amazing foundation so that (i) they understand the role of various tools and technologies as it relates to the business problems they will face, and (ii) they develop the ability to learn and harness any tool or technology from their experience in the program using extensible ones. Going back to the example above, do you know how one becomes an expert server-side java programmer? – by working in a position where they use enterprise java application servers and write server-side code for years for a software company that built and supported a real product… not by getting a CS degree. Do you know how one becomes an expert in R Studio, Shiny application development, dplyr, knitr, DT, ggplot2, CRAN, rmarkdown etc.? By writing and supporting an amazing business analytics software package for years (Radiant) as Professor Njis has done: http://vnijs.github.io/radiant/ From his experience with the data visualization libraries in the design of Radiant, Professor Nijs can easily harness *any* other visualization library out there (and there are dozens). That’s the benefit of developing extensible skills.
We’ve designed our program to ensure our graduates will be successful working on business analytics teams in companies. If I had to choose between hiring someone who built a product like Radiant, and someone who has “working knowledge” of SAS, Stata, R, S Plus, Excel, Minitab, Matlab, and SQL, I would take the former every single time.
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发表于 2016-4-4 11:43:20
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