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自然科学

科学分析学

MSc in Analytics

芝加哥大学

学院名称

暂无

专业编号

标准考试成绩要求
  • TOEFL104  

专业排名

科学分析学专业排名暂无排名 ,US News 2018

招生人数

全球范围内招收学生暂无,秋季 2018

学年学费

$52,200 

奖学政策

暂无

学年学制

暂无

所在校区

暂无

录取要求

The required proficiency standards include a score of 104 on the TOEFL, with four subscores of 26 each, or seven overall on the IELTS, with subscores of seven each.


申请材料清单

立即申请

TRANSCRIPTS
One transcript from each university attended must be uploaded within the application. If we do not receive one unofficial transcript from each University attended, your application will be considered incomplete and we will not review it. We accept unofficial transcripts for application evaluation, which can be uploaded as a PDF as part of your online application. Please do not mail transcripts as part of your admission application. If you are offered admission, one official transcript for each university attended will be required at least one month prior to matriculation.
An unofficial transcript for undergraduate coursework is required even if you hold an advanced degree(s). Course by course evaluations (see section on International Transcripts below) are not considered unofficial transcripts.

ENGLISH PROFICIENCY
If your native language is not English, we require an official TOEFL or IELTS test score submitted by the testing body by the application deadline. Our TOEFL and College Board code is 1832. The required proficiency standards include a score of 104 on the TOEFL, with four subscores of 26 each, or seven overall on the IELTS, with subscores of seven each. Note that students are required to take the Academic Reading/Writing test within IELTS, not the General Training Reading/Writing test. If your score is lower than the required proficiency standard in the total score or subscores, we recommend you retake the test.
The English language requirement may be waived if the applicant is a native of or studied in full-time status for at least one academic year within the last five years in the U.S., the United Kingdom, Ireland, Australia, New Zealand or English-medium universities in Canada or South Africa. We do not grant English language requirement waivers, unless you fall into the group of people described. More details are listed here.
Please note, it may take three to four weeks for your official test scores to be uploaded to our application system. In order to avoid late score submissions, we highly recommend you take the test no later than one month prior to the application deadline listed above. If we do not receive your score by the application deadline, we will not review your application.

LETTERS OF RECOMMENDATION
Three letters of recommendation from individuals who can assess your academic or professional qualifications are due by the application deadline. Letters from family members or peer-level colleagues are not acceptable.

CANDIDATE STATEMENT
Applicants are required to demonstrate the motivation, academic potential, and ability to undertake work at the University of Chicago by writing a candidate statement (typed, double-spaced, not to exceed four pages) highlighting their qualifications and describing their interest.

INTERNATIONAL TRANSCRIPTS
If you attended an international university or college, we require a Course by Course Evaluation by a NACES Evaluator for each international institution to be submitted by the application deadline. A course-by-course evaluation will translate courses, degree, and grades to U.S. equivalency. Please visit naces.org/members for more details. Evaluation reports should be mailed to:

The University of Chicago Graham School
Attention - Graduate Admissions
1427 East 60th Street
Second Floor
Chicago, Illinois 60637
The agency you choose may also submit your evaluation report electronically to analytics@uchicago.edu.
In order for this to be received by the application deadline listed above, we recommend you submit your transcript to be reviewed by a NACES evaluator no later than one month prior to the application deadline.

RESUME OR CV
You will submit an up-to-date resume or CV as part of your complete application.

Application Fee
The application system will prompt you to pay the $75 application fee once you have completed the appropriate sections of the online application.

截止申请时间:

2-Apr

专业介绍

The University of Chicago Graham School Master of Science in Analytics attracts students from all over the world to our downtown Chicago campus. These students use the MScA program as a springboard to dive into the analytics field, discover new ways to use analytics to explore complex questions, and shape themselves into leaders in the analytics community.

Building from a core in applied statistics, the Master of Science in Analytics provides students with advanced analytical training, developing the ability to draw insights from big data. The curriculum offers a thorough exploration of state-of-the-art data-gathering tools, methods, and analytics.


Coursework focuses on:

Acquiring advanced proficiency in applying state-of-the-art database development and software skills to support a variety of analytics applications

Learning data collection and preparation methodologies including identifying relevant data sources and preparing data for analytics

Gaining an in-depth understanding of established and state-of-the-art modeling and data analysis techniques

Designing and implementing applied research by using analytics tools relevant to strategic business issues, while working with real data sets provided by our industry partners in the Capstone project

Building effective leadership and communication skills which includes developing impactful practical solutions and understanding the marriage between business and analytics strategy

推荐课程

  • Statistical Analysis 31007

  • Data Mining Principles 31008

  • Machine Learning & Predictive Analytics 31009

  • Leadership Skills 31003

  • Programming for Analytics 37010

  • Linear Algebra &Matrix Analysis 32010

  • Big Data Platforms 31013

  • Data Engineering Platforms for Analytics 31012

  • Bayesian Methods32014

  • Research Design for Business Applications31001

  • Marketing Analytics32003

  • Linear and Non-Linear Models31010

  • Time Series Analysis & Forecasting31006

  • Advanced Python for Streaming Analytics32016

  • Real Time Analytics32005

  • Advanced Machine Learning32017

  • Linear and Non-Linear Models31010

  •   Optimization & Simulation Methods32013

  • Health Analytics32009

  • Digital Marketing Analysis in Theory and Practice32015

  • Machine Learning & Predictive Analytics31009

  • Time Series Analysis & Forecasting31006

  • Data Mining Principles31008

  • Data Visualization Techniques32007

  • Financial Analytics32001

  • Leadership Skills31003

  • Natural Language Processing and Cognitive Computing32018

  • Research Design for Business Applications31001

  • Big Data Platforms32018

  • Statistical Analysis31007

  • Optimization and Simulation Methods for Analytics32013

  • Risk Analytics32004

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