2023年佐治亚理工大学新增的分析学硕士专业 让你成为数字时代的分析师!
近些年，随着大数据时代的到来，各行各业都需要一些懂得数据挖掘、分析并运用到商业决策中的专业人才，从而分析师的需求量与日俱增，可国内目前鲜少有大学开设此专业，而美国很多大学都相继开设了分析专业，这不2023年佐治亚理工大学就新增了分析学硕士专业，下面，就随小编来看看吧，希望对大家有所帮助：
Master of Science in Analytics
分析学理学硕士是一个跨学科的分析和数据科学项目，通过结合谢勒商学院、计算学院和工程学院的世界级专业知识，充分利用佐治亚理工学院在统计、运筹学、计算和商业方面的优势。通过整合这些国家排名项目的优势，毕业生将学习以独特和跨学科的方式整合技能，从而对分析问题产生深刻的见解。
课程设置：
Base Curriculum - All Tracks
MGT 6203 Data Analytics in Business (3 credits)
CSE 6242 Data and Visual Analytics (3 credits)
One operations research course (3 credits)
Two statistics courses (6 credits)
MS Analytics Track Options
Analytical Tools Track
CSE 6040 Computing for Data Analysis (can be replaced by an elective if you have sufficient background)
ISyE 6501 Introduction to Analytics Modeling (can be replaced by an elective if you have sufficient background)
MGT 8803 Introduction to Business for Analytics (can be replaced by an elective if you have sufficient background
CSE 6242 Data and Visual Analytics
MGT 6203 Data Analytics in Business
Five (5) statistics/operations research electives, including at least one in each area
CSE/ISyE/MGT 6748 Applied Analytics Practicum (could include approved applied analytics internship)
Additional Resources - All Tracks
Academic and professional advising
Job placement support
Professional development funding to attend conferences, training, etc.
Georgia Tech's state-of-the-art high-performance computing infrastructure for massive-scale analytics
Free cloud computing resources
Free and discounted analytics, engineering, and productivity software
Free and discounted certification training
Communication training
Interview skills training and practice
Creativity, leadership, teamwork, and ethics training
Access to the MS Analytics Seminar Series
Business Analytics Track
CSE 6040 Computing for Data Analysis (can be replaced by an elective if you have sufficient background)
ISyE 6501 Introduction to Analytics Modeling (can be replaced by an elective if you have sufficient background)
MGT 8803 Introduction to Business for Analytics (can be replaced by an elective if you have sufficient background
CSE 6242 Data and Visual Analytics
At least three (3) business analytics courses beyond the introductory core, including MGT 6203 Data Analytics in Business
Two statistics electives and one operations research elective
CSE/ISyE/MGT 6748 Applied Analytics Practicum (could include approved applied analytics internship)
Additional Resources - All Tracks
Academic and professional advising
Job placement support
Professional development funding to attend conferences, training, etc.
Georgia Tech's state-of-the-art high-performance computing infrastructure for massive-scale analytics
Free cloud computing resources
Free and discounted analytics, engineering, and productivity software
Free and discounted certification training
Communication training
Interview skills training and practice
Creativity, leadership, teamwork, and ethics training
Access to the MS Analytics Seminar Series
Computational Data Analytics
CSE 6040 Computing for Data Analysis (can be replaced by an elective if you have sufficient background)
ISyE 6501 Introduction to Analytics Modeling (can be replaced by an elective if you have sufficient background)
MGT 8803 Introduction to Business for Analytics (can be replaced by an elective if you have sufficient background)
MGT 6203 Data Analytics in Business
At least three (3) computing courses beyond the introductory core, including CSE 6242 Data and Visual Analytics (can also include CSE/ISyE Computational Data Analysis (Machine Learning), which must be taken as a computing elective or as a statistics elective)
Two statistics courses (can include CSE/ISyE 6740 Computational Data Analysis (Machine Learning)) and one operations research course
CSE/ISyE/MGT 6748 Applied Analytics Practicum (can include approved applied analytics internship)
Additional Resources - All Tracks
Academic and professional advising
Job placement support
Professional development funding to attend conferences, training, etc.
Georgia Tech's state-of-the-art high-performance computing infrastructure for massive-scale analytics
Free cloud computing resources
Free and discounted analytics, engineering, and productivity software
Free and discounted certification training
Communication training
Interview skills training and practice
Creativity, leadership, teamwork, and ethics training
Access to the MS Analytics Seminar Series
申请要求：
寻找对分析/数据科学有强烈兴趣的优秀学生，并具有高水平的能力，这些能力已经在过去的适当的课程和/或工作经验以及标准化测试中得到证明。所有申请者预计将有基本的数学背景(至少有一个大学水平的课程或同等知识微积分,概率和统计,和一些线性代数)和计算(至少有一个大学水平的课程或相关知识在计算机程序设计中使用高级语言如C、c++、Java、Python、FORTRAN、等)，以及四年制学士学位或同等学历。
语言要求：
托福成绩(最低100分)或雅思成绩(最低7.5分)
职业前景：
该项目的目标之一将是培养和安置能够立即和长期影响商业、工业和政府的毕业生。除了在课程期间与领先的分析组织接触，学生还将获得资助参加一个主要的分析会议，在乔治亚理工大学的大数据行业论坛上获得有价值的曝光，并在求职过程中得到专业人士的支持。
课程还将促进内部联系。为了在每个小组中建立一个强大的专业网络，学生将一起学习几门课程，发展跨学科的工作关系，并建立可以在整个职业生涯中依赖的联系。
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