近日,MIT Sloan商学院高调宣布将开设商业分析硕士(Master of Science in Business Analytics)。不得不说,大数据的火热逐渐引起了学术界的高度重视。
大数据目前主要有3个研究的方向:机器学习(Machine Learning),数据科学(Data Science),商业分析(Business Analytics)。3个研究方向同时又对应着美国各个名校的不同专业方向。机器学习(Machine Learning),是计算机科学下的热门研究方向,注重通过各种算法和计算机语言来处理成百亿的数据,机器学习也是大数据技术的核心。对申请者的计算机编程和算法背景要求极高,所以这个方向的申请者最好有扎实的计算机背景,本科所学专业最好是计算机相关的理工科专业。
数据科学(Data Science),更像是计算机和应用数学的交叉学科,更偏后者,注重数理统计,数学建模等在数据挖掘处理方面的应用。可想而知,如果对这个方向感兴趣,那么申请需要具备扎实的数理分析能力,需要在统计,数学,建模,计算机编程以及相关软件应用方面有过硬的数学或者科研背景。
商业分析(Business Analytics),说白了就是大数据理念在商业领域的实际应用,如何通过更精准的数据分析得出更客观的决策建议进而优化商业运作流程,并且提高资源利用效率。在成本控制精算化的时代,商业分析已经成为众多商业机构最为重视的核心部门之一。从最经典的啤酒和纸尿裤的故事,到网购平台上的Recommendation Items,无一不渗透着数据分析的理念。商业分析这个专业,一般开设在商学院,一方面要求申请者要对数学分析有一定的功底,另外,最好有一些商科或者经济方面的认知。
根据官网内容,该项目同时接受GRE或GMAT成绩进行申请,同时需提交PS、小论文、成绩单、简历、3封推荐信。此项目的学费为7万5美金。
【参考原文】
MIT Sloan today announced the launch of a new, specialized Master of Business Analytics (M.B.An.) program designed to prepare students for careers in business analytics.
The school, together with the MIT Operations Research Center, introduces the M.B.An. in response to demand from current students and employers for a rigorous degree program focused on applying the tools of modern data science to solve problems in business and society. MIT now offers an analytics degree at the undergraduate, graduate, and doctoral levels.
“In the era of big data, the demand for skilled practitioners who understand how to mine and analyze the vast amount of digital data that’s being created is a well-known challenge,” says MIT Sloan Dean David Schmittlein. “In recognition of this need for innovation and excellence in analytics, our mission is to build a world-class master’s program in data science that leverages the intellectual resources of MIT, is based on cutting-edge research, and, as a result, attracts the very best applicants.”
A wide range of industries, including marketing, finance, health care, logistics, insurance, e-commerce, manufacturing, and government services already use analytics in their business processes and more will continue to do so in the next decade. According to a report from McKinsey Global Institute, the U.S. willexperience a shortage of 190,000 data scientists and 1.5 million managers and analysts capable of harvesting actionable insights from big data by 2018. A case in point: Job postings related to analytics at MIT Sloan’s Career Development Office have increased 78 percent over the past three years.
“The new degree is a timely addition to our portfolio of programs and builds on MIT Sloan’s excellence in management, finance, and business analytics,” says Jake Cohen, senior associate dean for MIT Sloan undergraduate and master’s programs. “The depth of the program creates a compelling value proposition—both for prospective students and for the companies and organizations that hire them.”
The success of any degree program is driven by its “intellectual content and the career opportunities it creates” for its participants, says MIT Sloan Professor Dimitris Bertsimas, the co-director of the MIT Operations Research Center. “The professional opportunities for our graduates will be extensive. Companies from IBM to Dell to Amazon to Google are collectively investing billions of dollars in data collection to build models that help them make better, more informed decisions. This is a transformational moment in business and management science.”
The inaugural class is slated to enter MIT Sloan in fall 2016. By 2020, the class will reach a steady state of sixty students.
The full-time, yearlong program is divided into three semesters: fall, spring, and a summer capstone. During the 10-week capstone, students work in small teams onsite at a U.S. or international company on a real data science problem. Each group completes a written report and gives a final oral presentation to the company and MIT Sloan and MIT Operations Research Center faculty.
“The capstone reflects the school’s commitment to action learning,” says MIT Sloan Professor John Hauser. “It gives students an opportunity to get out in the field—with a lot of faculty mentoring and support—and apply the very deep technical knowledge they’ve learned in the classroom to solve a real world challenge. We want them to dive into data: to handle it, to organize it, and to interpret what it means.”
Interested students should have strong mathematical, computer science, and statistical backgrounds. The program is tailored for recent college graduates who plan to pursue a career in the data science industry, as well as those seeking a career change, especially engineers, mathematicians, physicists, computer programmers, and other high-tech professionals.
To be considered for the program, candidates must submit a personal statement and optional essay, a transcript, resume, recent GMAT or GRE scores, and three letters of recommendation. Tuition for the program is $75,000.
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