麻省理工学院统计和数据硕士网课介绍

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2020-11-30

　　麻省理工学院统计和数据硕士申请要求有哪些呢?是很多留学朋友十分关心的问题，今天就让我们带着这个问题来听听小编对此的相关介绍吧，希望对大家的留学有所帮助。

　　About the Program

　　Demand for professionals skilled in data, analytics, and machine learning is exploding. A recent report by IBM and Burning Glass states that there will be 364K new job openings in data-driven professions by 2020 in the US. Data scientists bring value to organizations across industries because they are able to solve complex challenges with data and drive important decision-making processes. 39% of the most rigorous data science positions require a degree higher than a bachelor’s.

　　This MicroMasters® program in Statistics and Data Science was developed by MITx and the MIT Institute for Data, Systems, and Society (IDSS). It is a multidisciplinary approach comprised of four online courses and a virtually proctored exam that will provide you with the foundational knowledge essential to understanding the methods and tools used in data science, and hands-on training in data analysis and machine learning. You will dive into the fundamentals of probability and statistics, as well as learn, implement, and experiment with data analysis techniques and machine learning algorithms. This program will prepare you to become an informed and effective practitioner of data science who adds value to an organization. The credential can be applied, for admitted students, towards a PhD in Social and Engineering Systems (SES) through the MIT Institute for Data, Systems, and Society (IDSS) or may accelerate your path towards a Master’s degree at other universities around the world.

　　Anyone can enroll in this MicroMasters program. It is designed for learners who want to acquire sophisticated and rigorous training in data science without leaving their day job but without compromising quality. There is no application process, but college-level calculus and comfort with mathematical reasoning and Python programming are highly recommended if you want to excel.

　　All the courses of this program are taught by MIT faculty and administered by Institute for Data, Systems, and Society (IDSS), at a similar pace and level of rigor as an on-campus course at MIT. This program brings MIT’s rigorous, high-quality curricula and hands-on learning approach to learners around the world—at scale.

　　对精通数据、分析和机器学习的专业人士的需求正在激增。IBM和Burning Glass最近的一份报告指出，到2020年，美国数据驱动行业将有364K个新职位空缺。数据科学家为跨行业的组织带来价值，因为他们能够用数据解决复杂的挑战，并推动重要的决策过程。39%的最严格的数据科学职位要求高于学士学位。

　　该MicroMasters®统计与数据科学课程由麻省理工学院和麻省理工学院数据、系统与社会研究所(IDSS)开发。它是一个多学科的方法，由四门在线课程和一个虚拟监考组成，将为您提供理解数据科学中使用的方法和工具所必需的基础知识，以及数据分析和机器学习方面的实际操作培训。您将深入学习概率论和统计学的基础知识，并学习、实现和实验数据分析技术和机器学习算法。这项计划将使你成为一个有见识和有效的数据科学的实践者谁增加价值的组织。对于被录取的学生，可以通过麻省理工学院数据、系统和社会研究所(IDSS)申请社会和工程系统(SES)博士学位，也可以加快你在世界其他大学获得硕士学位的步伐。

　　任何人都可以参加这个计划。它是专为那些希望在不脱离日常工作的情况下，在不影响质量的情况下，获得复杂而严格的数据科学培训的学习者而设计的。没有申请流程，但是如果你想出类拔萃的话，强烈推荐使用大学级别的微积分以及数学推理和Python编程。

　　该课程的所有课程均由麻省理工学院的教员讲授，并由数据、系统和社会研究所(IDSS)管理，其速度和严格程度与麻省理工学院的校内课程相似。该课程将麻省理工学院严谨、高质量的课程和实践性学习方法大规模地带到世界各地的学习者面前。

　　PhD Program in Social & Engineering Systems社会和工程系统(SES)博士学位

　　https://idss.mit.edu/academics/ses_doc/

　　Applications are due by 11:59PM EST on December 15

　　GRE scores will not be required or accepted for September 2021 applications.

　　Whether your most recent experience has been an undergraduate or master’s program, or in industry, if you can demonstrate (a) academic excellence in a relevant area (engineering or applied mathematics, or social science) from a strong program, (b) motivation to solve concrete and complex societal problems with technological aspects, and (c) an interest in fundamental research on complex systems, we encourage you to apply.

　　We are expecting to see applicants with two different types of undergraduate preparation:

　　Students with a background in engineering or applied mathematics

　　These applicants should be interested in learning about the social sciences and translating their skills to a particular domain, or interested in incorporating the social or economic aspects of their research problem into their work.

　　Students with a background in social science – particularly those with a background in quantitative analysis.

　　These applicants should be interested in learning advanced quantitative methods, and in applying their skills to domains of interest, while also taking into account engineering aspects.

　　Is a master's degree expected? Required?

　　A master’s degree is neither expected nor required. Many SES doctoral students are admitted directly from an undergraduate program.A master’s degree may be useful for providing applicants with a significant research experience if their undergraduate program (or their professional experience, if any) hasn’t included a substantial exposure to research. It may also be useful to applicants whose undergraduate preparation did not include some of the prerequisites for high-level graduate work in this area.

　　Work experience is neither expected nor required. Work experience can be useful at focusing career and research objectives, and providing relevant context in an application domain. We expect most SES students will be motivated by solving the complex problems that occur at a systems-scale, at the interface of human activity and technology: problems that incur unnecessary human and economic costs; problems that require a multidisciplinary skill-set to address. That motivation and perspective — however a student arrives at it — is invaluable, and we expect most applicants to have some sort of track record of seeking out opportunities to work with these types of systems, whether that’s through coursework, internships, research, or work experience.

　　The admissions committee is looking for evidence of an applicant’s potential to thrive as a researcher. The goal is to find junior researchers who can focus on a problem intensively and exhaustively over a period of years; who benefit from instruction, guidance, and critique; and who, over the course of their preparation, can progress to a level where their work is furthering the state of knowledge.

　　computer programming

　　ability to communicate technical material

　　for social science backgrounds: preliminary experience in engineering and/or quantitative methods is desirable

　　for engineering backgrounds: preliminary experience in social science is desirable

　　申请截止时间为美国东部时间12月15日晚上11:59

　　2021年9月的申请不要求或不接受GRE分数。

　　无论你最近的经历是本科或硕士课程，还是在工业领域，如果你能证明(a)在相关领域(工程或应用数学，或社会科学)从一个强大的项目中获得卓越的学术成就，(b)有能力解决技术方面的具体和复杂的社会问题，以及(c)对复杂系统的基础研究感兴趣，我们鼓励您申请。

　　我们希望看到有两种不同类型的本科准备的申请人：

　　具有工程或应用数学背景的学生

　　这些申请人应该有兴趣学习社会科学并将其技能转化到特定领域，或者有兴趣将其研究问题的社会或经济方面纳入其工作。

　　有社会科学背景的学生，尤其是有定量分析背景的学生。

　　这些申请人应该有兴趣学习先进的定量方法，并将其技能应用到感兴趣的领域，同时也考虑到工程方面。

　　硕士学位既不期望也不要求。许多SES博士生直接从本科项目录取。如果他们的本科项目(或专业经验，如果有的话)没有大量的研究经验，硕士学位可能有助于为申请人提供重要的研究经验。它也可能有助于申请者的本科准备不包括一些先决条件的高水平研究生工作在这一领域。既不要求也不期望有工作经验。工作经验有助于关注职业和研究目标，并在应用领域提供相关背景。我们预计，大多数SES学生将通过解决在系统规模上、在人类活动和技术界面上出现的复杂问题来获得动力：产生不必要的人力和经济成本的问题;需要多学科技能集来解决的问题。这种动机和观点——无论学生如何获得——都是无价的，我们希望大多数申请者在寻找与此类系统合作的机会方面都有一定的记录，无论是通过课程、实习、研究还是工作经验。招生委员会正在寻找证据，证明申请人有潜力成为一名研究人员。其目标是寻找能够在一段时间内集中精力、精疲力竭地研究一个问题的初级研究人员;从指导、指导和评论中受益的研究人员;以及在他们的准备过程中，能够进步到工作促进知识状态的水平的研究人员。

　　计算机程序设计

　　沟通技术资料的能力

　　社会科学背景：有工程和/或定量方法的初步经验者优先

　　工程背景：有社会科学方面的初步经验者优先

　　The current application fee is $75.00 USD.