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2015年的最后一天，跟大家分享一下我所了解到的一些BA&DS的项目信息，通过CD认识了不少好朋友，希望新的一年大家多多拿AD啦~~
顺序：
GWU DS, UCSD BA, WUSTL CA, UR BA, SMU BA, PURDUE BAIM （乱排的）
George Washington University MS in Data Sciences
GWU今年家新开了MSDS，但是官网上信息很不全，所以打电话骚扰了小米。
1) 这个项目是什么时候开的，有多少人enroll？
小米：MSDS项目是2015 Fall新开的项目，在Columbian College of Arts & Sciences学院下。由于第一年录取发的比较晚，最后大概有20个人 enroll 2015 Fall class. 2016 Fall 招生人数没有确定，初步预计人数会增加，但不会增加太多。
2) 这个项目提供奖学金吗？人数多少？需要单独申请么？
小米：MSDS项目提供为少数学生提供 merit-based奖学金，去年20个enroll的学生中有2人获得了奖学金。每人的奖学金在10k左右。不需要单独申请，在申请页面选择申请奖学金选项即可。申不申将不会影响录取。
3) MSDS项目接受GRE/GMAT么？
小米：目前MSDS的申请者不需要提供GRE或者GMAT成绩，但是非常推荐quantitative background不强的同学上传他们的GRE或者GMAT成绩作为参考。
4）MSDS项目费用多少？项目要多长时间？
小米：MSDS项目需要至少修满30个学分，每个学分1500刀+。建议大家一学期修9个学分左右，summer修3个学分，一般的同学可以在1.5年左右完成整个program。需要注意的是，国际生可能会被要求先修语言课，这样的话，一般要在两年左右完成program。
5) MSDS项目是stem么？
小米：是STEM，学校可以帮助学生办理cpt和opt。
6)接受春季入学么？
小米：接受春季入学，但是春季入学的同学得到奖学金的几率更小。
下面附上GWU家的课程信息，感觉选课还是很自由的。
Curriculum
Our curriculum features a combination of courses that address:
Methods: Data management and data analytics; develop deep expertise in the programing languages essential for Data Science, including Python, JavaScript and R
Applications: Elective courses in data science applied to a specific knowledge domain, such as astrophysics, political science and geography (GIS)
Skills: Teamwork, project management and communication skills
Technology: Hands-on exposure to data analysis and visualization software tools and languages; gain experience applying data science principles to real world applications
The Master of Science in Data Science requires 10 three-credit courses, with the following components:
three data analytics core courses
two data analytics elective courses
at least two domain/application
one Capstone Core Course
two additional courses in data analytics or domain/applications
The Certificate in Data Science requires four data science courses, at least two of which are core courses.
Data Analytics Core Courses (3 courses)
The three core courses below provide foundational knowledge in data science and should be taken during year one:
DATS 6101 Introduction to Data Science
DATS 6102 Data Warehousing and Analytics
DATS 6103 Introduction to Data Mining
Data Analytics Courses
Intermediate (choose at least 2 courses)
DATS 6201 Numerical Linear Algebra and Optimization
DATS 6202 Machine Learning I (Initially, cross list with PHYS 6620)
MATH 6522 Introduction to Numerical Analysis
STAT 6201 Mathematical Statistics I
STAT 6207 Methods of Statistical Computing
STAT 6210 Data Analysis
STAT 6214 Applied Linear Models
STAT 6216 Applied Multivariate Analysis II
STAT 6242 Regression Graphics/Nonparametric Regression
Advanced (choose 2 or fewer courses)
DATS 6203 Machine Learning II
STAT 6202 Mathematical Statistics II
STAT 6223 Bayesian Statistics, Theory and Applications
STAT 6289 Topics in Statistics
Domain/Application Area Elective Courses (choose at least 2 courses)
DATS 6401 Visualization of Complex Data
DATS 6402 High Performance Computing and Parallel Computing
DATS 6450 Topics in Data Science
ECON 8375 Econometrics I
ECON 8376 Econometrics II
ECON 8377 Econometrics III
ECON 8378 Economic Forecasting
GEOG 6304 Geographical Information Systems I
GEOG 6307 Digital Image Processing
PSC 8132 Network Analysis
PSC 8185 Topics in Empirical and Formal Political Analysis
Capstone Core Course (1 course)
DATA 6501 Data Science Capstone
This is a three-credit course in which students apply what they have learned in data science courses to address data-related complex problems in the real-world. Through various projects assigned by the faculty, students will have the opportunity to reinforce their knowledge in data science while enhancing real-world skills such as communication, teamwork and analytics.
University of California, San Diego MS Business Analytics
最近在研究BA/DS的学校所以扒出了几个新项目。。。USCD家算一个！阳光啊！沙滩啊！而且SD的墨西哥食物真的很好吃啊！！！！好了废话不说，说说项目。通过电话和邮件跟小米确认了不少信息，跟大家分享一下。
1）项目预计招收多少人？
小米：目前没有确定，会根据申请人数的多少来决定项目大小。
2）项目有先修课要求么？
小米直接给我发的官网信息：
It is expected that most successful applicants will have either (i) an undergraduate degree in a quantitative discipline such as mathematics, economics, statistics, physics, engineering, or computer science, or (ii) five or more years of work experience in the public or private sector. Students with a non-quantitative undergraduate degree and less than five years of work experience will be considered on an exceptional basis if (1) their work experience is in the area of business analytics or marketing research or (2) they have developed a strong quantitative background through additional coursework or relevant work experience. The program will only admit students who have a solid foundation in quantitative methods, particularly knowledge of probability and statistics and the use of statistical applications such as R, SAS, STATA, and Matlab. Additionally, each student must demonstrate evidence of programming proficiency from prior college coursework, professional experience, a certificate from a continuing education program, or a Coursera course on R-programming.
总体看来背景要求还是挺高的。
3）项目多长？预计什么时间开学？
小米：项目4个quarters，50个unit，预计12个月可以完成。开学时间未定，以往来看9月底开学。
4）项目是stem么？
小米：是STEM。(但是BA群的小伙伴质疑了这一点，一个还没开始的新项目拿下stem知得商榷)
5）项目费用多少？有没有奖学金？给奖比例？
小米：$52,900学费，保险（optional）3414$, 生活费估算2w上下。提供 merit-based fellowships，国际学生可以申请，无需额外申请。给奖比例大概10-30%。
6）就业服务如何？
小米：有capstone project会与企业合作。
私下看了一下SD的MBA还就业统计，感觉不太乐观。
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吐槽：总体来说项目很新，很多东西还无从参考，之前听别人讨论过他家的课程设置。相比其他BA项目课程设置偏文，但是录取对quantitative background要求又很高。。感觉项目定位并不是很准。
Washington Unversity in St.Louis MS in Customer Analytics
1）项目预计招收多少人？
AO: 今年的人数应该会跟去年持平，
2）项目有先修课要求么？
AO：希望申请人学过Stats&Calc 2
（从录取的同学们的背景来看，MSCA对于理科背景卡的并不是很严格，什么专业都有，包括广告经济mkt什么的，相反的更看重申请人的综合背景，大部分录取者都有工作经验或者是美本，已知的2个应届陆本的背景非常出色）
3）项目多长？预计什么时间开学？
AO: 从2016Fall 开始，MSCA将会变成3个学期修完，具体时间是2016年7月中下旬-2017年十二月中旬，中间会有summer留给大家实习。当然学费也水涨船高，估计17个月的学费在75k左右。
4）项目是stem么？
AO：是STEM
6）就业服务如何？
AO：career center会帮助大家找实习，还会有许多企业来到校园招聘。
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WUSTL在CD上也算高冷女神了，毕竟综排商排都很高。。跟在读的学长学姐聊了以后发现变成3个学期还是非常有必要的，他们现在2个学期39学分已经要handle不了了，而且多个summer可以实习会对找工作有利很多，只是学费。。。。:-(MSCA变成3个学期以后，每个学期可以选19.5学分，所以也就意味着大家可以多选点课，选修课还不错从public policy 到Data Mining都有，偏文偏理可以自己控制。目前知道涉及到的软件有R,JAVA,SAS,SPSS.
WUSTL最大的槽点就是地理位置了，中部大农村，不知道对找工作会不会有很大影响，不过从Olin 各个专业的就业数据来看，还是可以的。
update:
昨天刚跟第一届毕业的，也就是2015年12月毕业的学姐聊了一下，第一届毕业的除了一个人以外基本上都找到了工作，学姐是在st louis当地找的，也有很多同学去了西海岸。
学姐说：“课程设置这两年都有变动，整体还是非常data，我看了一眼这两年比我当时更科学了，有一些big data非常需要的课程也加上去了。”
这个项目最后一个学期有industry project，client一般都是些很不错的公司，如果项目完成得好的话，客户公司会直接问愿不愿意来他们公司，学姐还有他的同学都是这样的，但是因为他们已经找好了工作，所以没有接受。
关于安全问题，学校附近都是很安全的，只要不去delmar以北就还好。
University of Rochester MS Business Analytics
罗村在CD上应该算是非常火的学校了吧，各种争论也很多，包括地理位置中国人数什么的。罗村的MSBA在罗村所有项目里应该算是比较良心的。
1）招生人数
小米：去年13人，今年会扩招到30人左右。
2）学费
小米：63k for 11 months. (听在读的同学说，罗村的17months track不单收学费，这点还是很良心的）
3）地理位置问题
开车到NY大约要5,6小时。
4）就业
MSBA这个专业应该是罗村所有专业里就业率最高的，第一届13个人的就业应该是接近百分百的。
5）是否STEM
是
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罗村的地理位置，学费，还有中国人多，是大家争议的热点。但是BA这个项目能感觉到学校做的很用心，而且课程设置也相当不错，免费延长到17个月更是有利于大家实习找工作。罗村30多的宗排，也拿得出手。对MSBA这个项目还是比较看好的。但是罗村一年中3-4个月都在下雪，怕冷的同学慎选。
Southern Methodist University MS Business Analytics
SMU的MSBA是我本人特别喜欢的一个项目，他家的director是26年的Accenture 大partner，也算是职场女强人了。
今年准备招60人，国际生控制在一半左右。
今年BA特别火，SMU的director说他家今年申请人第一轮多了一倍，卡人会很严格。第一轮申请人大概在六十个，录了16个左右，wl了18个左右。
SMU的BA就业特别好，去年31个国际生只有1个没有在毕业之前找到全职工作，average salary 70k，不过听中国校友说，薪水大概在50-60k，不知是否有税前税后区别。
教授也很给力，有UT的PHD，还有之前MIT的教授，也有wharton毕业的。大牛教授Dillian自己创业，在boston有公司，年薪500k。
这个项目的Director Hettie是在Accenture干了26年的partner，被SMU挖过来了。非常profesional的一个人，人脉也特别广。非常敬业，邮件秒回。
课程加上summer camp大概10个月，费用在50k左右。(项目稍微有点短。。)
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从录取情况来看，SMU家今年录的绝大多数都是71族，并且非常看重海外背景和programming，因为项目短，director不希望大家来了以后还要用一段时间适应语言。
SMU一个硬伤就是排名，宗排有点低，QS700+，但是对于死了心留美的同学，SMU所在的dallas应该算是美国最好的job hub之一了。SMU地霸的性质，比较适合愿意在texas当地工作的同学。顺便说，texas没有州个人所得税。SMU的课程相当intensive，要去的同学需要做好准备
课程设置
| | Course Number | Course | Instructor | Description | | E | BP Elective - ITOM 6226 | Operations Analytics | Bhaskaran, Sree | Organizations invest the bulk of their human and financial resources in their operations functions. As a result, more efficient operations typically result in better performance. In this course, students will study analytical models and techniques that can be used to improve operational and firm performance. Decision making under uncertainty will be addressed using static stochastic optimization, two-stage optimization with recourse, and sequential decision making. Optimization models will be used to tackle problems in inventory management, revenue management, supply chain management, project management and new product development. Students will also learn how strategic decisions can be aided by data-driven, analytical models. Some core aspects of business strategy, including external analysis, competitor analysis, and opportunity analysis are covered. The goal is to understand the role that analytics and analytical models can play in improving an organization’s operational processes | | E | BP Elective - ITOM 6208 | Managing Big Data | Smith, Bryan | This course covers methods for capturing, organizing and managing databases that are both big and complex. The use of data warehouses to support online analytical processes (OLAP) will be examined, as well as non-traditional databases, such as federated and distributed database systems, grid systems and emerging technologies such as HADOOP and MapReduce. | | E | BP Elective - ITOM 6214 | Business Process Analytics | Puelz, Amy | This course covers more advanced topics and applications of the analytical techniques surveyed in the introductory decision modeling class (linear programming, nonlinear programming, integer programming and simulation, among others). Areas of application may include operations, technology, finance and marketing. More advanced methods such as dynamic optimization, game theory, multi-criteria decision making, and stochastic optimization will be covered. The course requires basic comfort with spreadsheets, including fixed and relative cell copying, functions and formatting. | | E | BP Elective - ITOM 6220 | Revenue Management | Semple, John | Revenue Management involves methods for increasing revenue by offering different fares/prices as perishable capacity is consumed. Examples of RM can be found in the airline, hotel, railroad, rental car, and retail fashion businesses among others. This class offers a variety of topics including price optimization (with and without capacity constraints), Littlewood’s two-class model (and extensions), the n-class single resource RM problem, nested controls, bid pricing controls, heuristic approaches, network capacity control (multi-resource problems), overbooking models, markdown optimization, and more. Students learn how to implement RM models using dynamic programming and linear programming in spreadsheets. | | E | BP Elective - ITOM 6222 | Predictive Analytics and Forecasting | Tan, Tom | From forecasting aggregate-level sales to predicting whether a customer will choose a particular product, analytic techniques are used by businesses to make rigorous, data-driven predictions. This course explores analytic models such as deterministic time-trend, exponential smoothing, Holt-Winters, auto-regressive exogenons, and Box-Jenkins, among others. Students learn to distinguish between trend and seasonality and to utilize both for making forecasts in such areas as sales and operational planning. This course also covers how to use industry and government metrics and how to present results to management. | | E | BP Elective - ITOM 6225 | Project Management | Bhaskaran, Sree | Managing projects in a cost effective and timely manner is one of the most challenging tasks in any organization. Competent project leadership requires understanding of how to allocate financial, material and time-based resources, and the ability to motivate and maintain focus of the project team. This course provides relevant project management skills by examining project decisions at three levels; (i) structuring and managing the task and leading the project team in an individual project, (ii) aggregate linkages across a portfolio of projects and management of programs, (iii) alliances across firms, project contracting and managing open innovation. It introduces tools and concepts that enable project managers to evaluate, manage and execute critical functions of any project while ensuring speed, efficiency and market impact. | | E | BP Elective - ITOM TBD | In Memory Analytics | Tabor, Hettie | This course examine the new in memory database systems used in Analytics. It includes configuration using SAP's HANA as well as discussions form other In Memory providers including IBM, Oracle and Teradata. | | E | CA Elective - MKTG 6204 Consumer Behavior | Consumer Behavior | Howard, Dan | This course examines in depth the consumer decision-making process and the factors that influence those decisions. The course covers "how" people make product related decisions and "why" they end up buying what they do. It will cover a range of consumer models including behavioral decision theory, psychology and utility theory | | E | CA Elective - MKTG 6205 Customer Ubsgights and Market Intelligence | Customer Insights and Market Intelligence | Sethuraman, Raj |
| | E | CA Elective - MKTG 6279 | Database Marketing using Multivariate Analysis | Sethuraman, Raj | Database marketing represents a fruitful marriage between the concept of marketing and advances in information technology. Database marketing is a systematic approach to the gathering, consolidation, and processing of marketing databases to learn more about customers and competitors, to select target markets, to compare customers’ value to the company, and to provide more specialized offerings. This course covers multivariate statistical techniques related to database marketing – including latent variables factor and principal component analysis, multidimensional scaling and perceptual mapping, cluster and discriminant analysis. | | E | CA Elective - MKTG 6284 | Retailing Analytics | Fox, Ed | The vast majority of consumer expenditures, which represent more than $5 trillion dollars and 68 percent of the United States gross domestic product, are made through retailers. Moreover, the average consumer product company spends as much on trade promotions (such as promoting its products to retailers) as it does on media advertising and consumer promotions combined. These facts highlight the importance of retailer behavior and trade promotions in consumer marketing. This course takes the retailer’s point of view, exploring strategic and tactical decision-making by assessing the impact of these decisions on both consumer shopping behavior and the retailer’s own operating costs. Students explore issues in sales promotion, pricing, product mix, and store location in order to gain an understanding of consumer response in these areas | | E | CA Elective -MKTG 6273 | Customer Value and Pricing Analytics | Dillon, William | Determining what is valued is perhaps the most important issue facing marketing managers. Recently, conjoint and choice models have become popular techniques to help marketing mangers understand what customers value in terms of the importance placed on specific product features and services. The objective of this course is to expose students to a variety of preference models used by brand managers and marketing analysts and to give students hands-on experience in using conjoint and choice modeling techniques | | C | ITOM 6212 | Data Visualization and Communications | Tabor, Hettie | In this course, students will be taught how to effectively communicate the results of the business analytics that they perform, in both written and oral presentation. The key questions for the analytic communications are: What is happening? Why is it happening? What should we do from here? | | C | ITOM 6215 | Database Design for Business Applications | Rogers, Stewart | This course covers fundamental issues in database creation and design. Students start with mapping data collection in organizations onto a database with the objective of storing data consistently over time. They then proceed to study methods for information extraction from databases. In terms of practical skills, students will learn how to import spreadsheet data into Microsoft Access and generate summary reports to answer business questions related to our data. Homework assignments and an implementation project in Microsoft Access will reinforce both the design issues and the practical skills covered in the course. | | C | ITOM 6217 | Data Mining | Basu, Amit | This course examines how companies can effectively leverage their information technology resources to gain better operational and competitive intelligence. Several technologies for enhancing organizational intelligence such as machine learning, neural networks, clustering and association-based reasoning are surveyed, and considerations that managers must make in applying these technologies to different types of decision and planning problems are discussed, using lectures, cases and hands-on exercises using appropriate software | | C | ITOM 6218 | Intro to Business Process Analytics | Schultze, Ulrike | Understanding and documenting the business processes and decisions that business analytics are expected to support is central to developing solutions that improve organizational performance. In this class, students will learn the conceptual frameworks, tools and skills needed to develop a blueprint for analytics. This entails successfully analyzing the high-level requirements for business analytics, prioritizing and outlining solutions, proposing business process improvements to generate the requisite data, and making the business case. | | C | ITOM 6219 | Web and Social Media Analytics | Mukherjee, Rajiv | This course focuses on methods to analyze the online activities of both organizations and consumers particularly on social media platforms. Key topics include how and why social networks form, how innovation diffuses in such networks, how unstructured user interaction data can be analyzed and what metrics can be used to measure platform performance. Analytic tools such as NodeXL, SAS (Text Miner, Sentiment Analyzer and Google Analytics, as well as experimental techniques are used to model, visualize and understand such network data. | | C | ITOM 6252 | Decision Models | Puelz, Amy | The purpose of this course is to help students understand how complex business problems can be analyzed, modeled and solved in an optimal manner. The course begins with a review of decision making under risk and uncertainty. Specific emphasis is then placed on the use and application of decision trees including the incorporation of utility theory. Then, this course moves on to the use and application of mathematical optimization models including linear programming, network models and integer programming. The final topic covered is simulation. Students will learn to develop spreadsheet models for making complex business decisions, as well as interpret the results of such models | | C | MAST 6251 | Applied Predictive Analytics I | Briesch, Rick | From forecasting aggregate-level sales to predicting whether a customer will choose a particular product, analytic techniques are used by businesses to make rigorous, data-driven predictions. This course explores analytic methods such as variable transformations, logistic regression, truncation and selection models, among others. Students learn to distinguish between trend and seasonality and to utilize both for making forecasts in such areas as sales and operational planning. | | C | MAST 6252 | Applied Predictive Analytics II | Braun, Michael | This course applies fundamental concepts of probability to data analysis and forecasting. The methodological focus is on both maximum likelihood and Bayesian approaches to statistical inference. Particular attention is placed on count, choice and timing models, with heterogeneous latent variables. Applications will be drawn from a wide range of business settings, such as new product forecasting, modeling customer retention and lifetime value, and market segmentation." | | C | MKTG 6258 | Business Metrics | Thomas, Jakki | This course is designed to provide an introduction to different metrics used across all businesses activities, e.g., marketing, operations, finance, etc. It includes an introduction to financial statement and Profit/Loss analysis and key business and economic concepts for the firm. | | C | MKTG 6274 | Business Research Methods | Armstrong, Marci | Business research is the formal process of gathering information needed by managers to make decisions. This course develops skills in the following areas so that students can competently implement decision-oriented business research projects in the real world: 1) translate a business decision into a research problem, 2) choose an appropriate research design, 3) collect data from secondary and primary data sources including survey research, experimental design and focus groups. 4) analyze data using spreadsheets or statistical packages, and 5) recommend decisions based on the analysis. | | C | MNGT 6101 | Managing Your Career | Tabor, Hettie | This course empowers MSBA students with the knowledge and tools to effectively manage their own careers. Topics include, but not limited to: exploring career opportunities within the Business Analytics space, building and leveraging a professional network and developing a personal marketing plan |
Purdue University MS Business Analytics & Information System
这个专业是purdue今年新开的，目前信息较少。
1）预计招生人数
AO: 30人左右
2)开课时间
六月份（应届生慎选）
3）项目费用，项目长度
BAIM的学费在商学院里可以算是非常厚道的，45k上下的费用，1年的长度。。难找啊!!
4)是否STEM
目前还不是，还在审批中，预计第一届学生毕业的时候之前也就是2017年6月份之前，能够拿到STEM
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听purdue在读的同学说，学院对这个新项目很用心，教授也都非常好，但是还没拿到stem这一点可能会对大家未来留美还是回国这一点有影响，所以想留美工作的同学慎选。
暂时就这么多了，未来如果了解到新的信息会继续更新在帖子里，对这几个项目，尤其是后五个有什么想法的同学可以留言大家一起交流，目前WUSTL,SMU,UR都有录取群，录了的同学可以私信我拉你进群。。。。
最后的最后，祝贺hzdy1994（杭州大爷1994）升任版主，苟富贵勿相忘。。。。
祝大家2016年AD拿到手软~~~
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发表于 2015-12-31 17:18:26
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发表于 2015-12-31 17:20:31
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