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卡内基梅隆大学计算数据科学硕士专业 让你成为挖掘数据的开发者!

  身处在大数据时代之下,各行各业都依靠数据来进行商业运作,从而对计算数据科学人才的需求量与日俱增,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数据科学专业,其中最出色的就是卡内基梅隆大学,下面,小编就带大家深入了解卡内基梅隆大学计算数据科学硕士专业,希望对大家有所帮助:

  Master of Computational Data Science

  该项目(成立于2004年,作为超大型信息系统的MSIT)培养专业硕士学生在超大型信息系统的设计、工程和部署的各个方面。在课程中,你将深入研究数据库、分布式算法和存储、机器学习、语言技术、软件工程、人机交互和设计等主题。通过核心课程和选修课,您将对大型信息系统有一个统一的认识,而我们的实习和顶点项目要求确保您拥有在职业生涯中获得成功所需的知识和经验。

  课程设置:

  Common Core

  The following four (4) core courses are to be completed by all students during their first two semesters:

  15-619 Cloud Computing

  10-601 Machine Learning

  05-839 Interactive Data Science

  11-631 Data Science Seminar

  Systems Concentration

  15-605 Operating Systems Implementation

  15-618 Parallel Computer Architecture & Programming

  15-640 Distributed Systems

  15-641 Computer Networks

  15-645 Database Systems

  15-712 Advanced and Distributed Operating Systems

  15-719 Advanced Cloud Computing

  15-721 Advanced Databases

  15-746 Advanced Storage Systems

  15-821 Mobile and Pervasive Computing

  36-702 Statistical Machine Learning

  36-705 Intermediate Statistics

  36-725 Convex Optimization

  Analytics Concentration

  10-608 Conversational Machine Learning

  10-701 Introduction to Machine Learning (PhD)

  10-703 Deep Reinforcement Learning & Control

  10-708 Probabilistic Graphical Models

  10-715 Advanced Intro to Machine Learning

  10-725 Convex Optimization

  10-805 Machine Learning with Big Data Sets

  11-641 Machine Learning for Text Mining

  11-661 Language and Statistics

  11-727 Computational Semantics for NLP

  11-741 Machine Learning for Text Mining

  11-747 Neural Networks for NLP

  11-755 Machine Learning for Signal Processing

  11-761 Language and Statistics

  11-763 Structured Prediction

  11-777 Advanced Multimedia Machine Learning

  11-785 Intro to Deep Learning

  Choose one course in Software Systems:

  11-642 Search Engines

  11-747 Neural Networks for NLP

  11-775 Large-Scale Multimedia Analysis

  11-777 Advanced Multimedia Machine Learning

  11-791 Design & Engineering of Intelligent Information Systems

  11-792 Intelligent Systems Project

  11-797 Question Answering

  Choose one course with a focus on Big Data:

  10-605 Machine Learning with Big Data Sets

  10-805 Machine Learning with Big Data Sets

  11-775 Large-Scale Multimedia Analysis

  Human-Centered Data Science (HCDS) Concentration

  Choose one course in Behavioral Research Methods:

  05-816 Applied Research Methods

  94-834 Applied Econometrics I & II

  Choose two courses in HCI Methods:

  05-821 Social Web

  05-823 E-Learning Design Principles and Methods

  05-833 Applied Gadgets, Sensors & Activity Recognition

  05-836 Usable Privacy and Security

  05-840 Tools for On-Line Learning

  05-872 Rapid Prototyping of Computer Systems

  05-891 Designing Human Centered Systems

  05-899 Crowd Programming

  05-899 Learning Analytics & Educational Data Science

  05-899 Special Topics in HCI: Sensemaking

  05-899 Design of Large-Scale Peer Learning Systems

  05-899 Learning With Peers at Massive Scale

  05-899 Mobile Health

  入学要求:

  GPA 3.0或更高。

  GRE成绩:必须少于5年。

  申请材料:

  简历,请提交你目前的简历,概述你的教育,研究经历,工作经历,出版,奖学金,所获奖项和荣誉,社会成员。

  目的陈述,准备一或两页的文章,描述你的主要兴趣领域的研究,你的相关经验,和你在卡内基梅隆大学攻读研究生学位的目标

  三封推荐信。

  你就读的每所大学的正式成绩单,无论你是否在那里获得了学位。

  语言要求:

  新托福考试成绩至少为100分。

  综上所述,以上讲的就是关于卡内基梅隆大学计算数据科学硕士专业的相关问题介绍,希望能给各位赴美留学的学子们指点迷津。近年来,赴美留学一直是广大学生最热门的话题,同时,很多学生对于签证的办理、院校的选择、就业的前景、学习的费用等诸多问题困扰不断,别担心,IDP留学专家可以为你排忧解难,同时,更多关于赴美留学的相关资讯在等着你,绝对让你“浏览”忘返。在此,衷心祝愿各位学子们能够顺利奔赴自己心目中理想的学校并且学业有成!


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卡内基梅隆大学计算数据科学硕士专业 卡内基梅隆大学 美国留学热门专业
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