a final, two-quarter group capstone
•DATA 556:统计与概率简介 •HCDE
511:信息可视化与数据可视化科学实验室:DATA 501
•数据557:应用统计与实验设计 •DATA 514:数据科学的数据管理 •DATA
558:数据科学家的统计机器学习 •DATA 515:数据科学的软件设计 •DATA
516:可扩展的数据系统和算法 •DATA 512:以人为本的数据科学 •数据590: C
apstone 1 – 项目准备 •数据591:Capstone II – 项目实施Students generally
progress through this sequence of required courses as a cohort. Master
of Science in Data Science courses are not open for single-course
enrollment, and no seats are available to non-matriculated students.A
Team-Based Learning ApproachMany of the courses will emphasize
team-based data analysis and engineering work and will involve working
in small groups to complete one or more guided practicum projects per
quarter. The final course is a capstone project where students get to
solve a real-world data analysis challenge facing a local
prerequisite coursework must be completed before you apply. MOOC or
other ungraded coursework cannot be used to fulfill this requirement.If
you took math or programming at a Washington state community college,
please see UW’s course equivalency guide.Mathematics: At a minimum, you
should have completed a three-class calculus sequence and a linear
algebra course, equivalent to UW’s MATH 124/125/126 and MATH
308.Computer Programming: At a minimum, you should have completed a
two-course introductory sequence in programming, equivalent to UW’s CSE
142/143, or be able to demonstrate equivalent proficiency.Alternatively,
you may demonstrate programming skills through practical experience,
such as through work, Kaggle competitions or other projects. If you
believe you have satisfied the programming requirement this way, please
provide a link in your application to a GitHub repository demonstrating
your coding experience or a recommendation from a technical colleague
describing your coding contributions to a work
1 (250 words maximum)What do you hope to accomplish in the short- and
long-term future? How will a Master of Science in Data Science help you
get there? Why is the UW Master of Science in Data Science program the
best fit for you?Essay 2 (500 words maximum)The UW Master of Science in
Data Science program places a premium on creativity and strong
communication skills. In addition to excellent quantitative abilities,
good data scientists must be able to visualize and narrate their
findings in a way that makes them meaningful to a non-technical
•破解蛋形之谜 (科学)
•35年美国人死亡 (FiveThirtyEight)
•2016年如何成为地球上最热门的一年(纽约时报)Essay 3 (250 words
maximum)The UW Master of Science in Data Science program aims to produce
leaders in data science. Provide an example of your leadership and
describe what you learned about yourself in the process.Optional Essay
(250 words maximum)Provide additional information that you would like to
bring to the attention of the admissions committee. This may include
gaps in employment history, academic performance issues, choice of
recommenders, socioeconomic disadvantages or any other relevant
information. If you are a reapplicant, explain how your candidacy has
strengthened since your last application.RecommendationsTwo
recommendations are required; three are preferred. Consider asking
current or recent employers, colleagues or teachers. Make sure they can
speak in detail about your programming, mathematical and communication
skills and your ability to learn new things or bring together different
approaches.You’ll need the email addresses of your references for the
Graduate School application. They’ll each be sent an email directing
them to a secure website where they’ll submit their

英属哥伦比亚大学:Sauder School of Business
of ManagementThe 9-month Master of Management (MM) at UBC Sauder’s
Robert H. Lee Graduate School gives students who have recently graduated
with non-business Bachelor’s degrees (from mathematics to music) the
business skills they need to gain a competitive edge in the job market.
Students can begin the program directly after their university
graduation, or with up to two years of post-graduation work
for UBC Master of Management :#2 Master of Management in North America
(Financial Times Global Master of Management Ranking 2017) :Rankings
for UBC Sauder School of Business :#16 in North America for Business
Research Excellence (QS Top 250 Business Schools Report 2017) #1 in
Best Universities to Study Business in Canada (Maclean’s University
Rankings 2018)Rankings for UBC #1 in Canada for Business and Economics
(Times Higher Education World University Rankings 2017-2018) #34
University in the World (Times Higher Education World University
Rankings 2017-2018)录取要求:We assess your managerial and leadership
potential领导力, maturity 成熟度, ambition and drive 目标和动力, through
your Essay Questions, resume, professional references and
>>我能被UBC商学院录取吗,在线咨询1、成绩单:a B+ average, or
recognized equivalent from an accredited
institutiom(非商科学生背景)  2、有竞争力的成绩:Applicants should
have B+ or 76% or 3.3GPA.  3、Two references:2封推荐信  4、No
full-time work experience to a maximum of two years full-time work
experience gained after graduation from your Bachelor’s
degre(不强制要求工作经验)  5、语言要求:GMAT:550 GMAT with at least
a 50th percentile in each test section or 150 GRE score on verbal and
quantitative section;TOEFL: 100,IELTS Academic:
7.0;  6、需要面试:an interview either in person or by Skype or
phone。2018年入读学生的情况:Class size: 39 Male | Female: 44% | 56%
Average age: 23 Percentage of International Students: 51%学位2:Master
of Business AnalyticsIn just nine months, the UBC MBAN gives candidates
with quantitative backgrounds sought-after analytical skills within a
broader business context. Our graduates will be able to apply advanced
analytical tools and methods to address management challenges in today’s
business world. Candidates will complete 33 credits, taking courses in
data handling, data analytics and decision analytics. Candidates may
also apply to an optional 6-credit Analytics Consulting Internship where
successful applicants will have the opportunity to gain real world
experience and hands-on business skills with leading
UBC MBAN selection process is rigorous.? Candidates are carefully
selected against competitive requirements to ensure that you learn from
peers who have demonstrated vision前瞻性, leadership 领导力 and
experience相关经验.? Applications are accepted on a rolling basis, and
are reviewed holistically.?1、背景要求:成绩要求with a B+
average,即为Applicants should have B+ or 76% or
3.3GPA,建议的先修课:it is strongly recommended that applicants have
some exposure to university-level courses in topics like statistics
统计学, calculus 微积分, and linear algebra 线性代数(or other courses in
mathematics and statistics或者其他数学和统计相关的课程). Experience in
computer programming计算机程序设计, data analytics 数据分析 or
mathematical modeling 数学建模is also an asset.
>>我的本科背景课程符合要求吗,在线咨询  2、语言要求:基础要求,550
GMAT with at least a 50th?percentile in each test section、或者是 155
GRE score on both the verbal and quantitative
sections,具有竞争力的分数为650 GMAT OR 320+ GRE score on combined
verbal and quantitative sections. TOEFL: 100、IELTS Academic:
7.0  3、no minimum work experience
requirement:没有工作经验要求  4、Two references:2封推荐信学位3:MSc
in Business AdministrationAimed at students interested in research, the
UBC MSc in Business Administration is a challenging and rigorous program
designed to prepare you for a?PhD program and a subsequent career in
academia. We will only be admitting a small number of students who are
qualified for and interested in a research oriented master’s degree
program in each of the specialized
MSc program offers study in three areas of specialization:
有3个具体的研究方向:Finance :金融  The research interests of our
Finance Division cover most major topics and methodologies in financial
economics.Management Information Systems:信息系统管理  The research
interests of our MIS Division include a wide range of topics in the
study of design, evaluation, implementation, deployment, management,
control and use of information technologies in
organizations.Transportation and Logistics :物流管理  The research
interests of our Transportation and Logistics faculty include aviation
research, transport economics, game theory applications, logistics and
supply chain management, operations management and

About the Course
In this course you will get an introduction to the main tools and ideas
in the data scientist’s toolbox. The course gives an overview of the
data, questions, and tools that data analysts and data scientists work
with. There are two components to this course. The first is a conceptual
introduction to the ideas behind turning data into actionable knowledge.
The second is a practical introduction to the tools that will be used in
the program like version control, markdown, git, GitHub, R, and RStudio.

Course Syllabus
Upon completion of this course you will be able to identify and classify
data science problems. You will also have created your Github account,
created your first repository, and pushed your first markdown file to
your account.
Recommended Background
No prior backround required. Previous experience in programming is
Course Format
This course consists of weekly video lectures, weekly quizzes, and a
final peer-assessed project.
How do the courses in the Data Science Specialization depend on each
We have created a handy course dependency chart to help you see how the
nine courses in the specialization depend on each other.

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