Difference between r1.61 and the current
[http://www.oii.ox.ac.uk/research/projects/?id=98 Accessing and Using Big Data to Advance Social Science Knowledge] . . . . A project initiated at the University of Oxford with a title, "Accessing and Using Big Data to Advance '''Social Science Knowledge'''"
한국 ¶
국민대학교 :: 빅데이터경영 MBA 과정
- 빅데이터 인프라 기술,
- 데이터 과학 및 분석기술
- 법, 정책
- 보건의료
- 생명, 환경
- 미래산업경제
- 사회복지
- 방송, 문화, 스포츠
- 인력양성
한양대학교 ::
Related program ¶
Academic Programs ¶
- Master of Information Systems Management (MISM), Carnegie Mellon
- Business Intelligence and Data Analytics (BIDA), Carnegie Mellon
- Institute for Data Sciences, Columbia University
DUAL MS IN JOURNALISM AND COMPUTER SCIENCEAdmitted students will enroll for a total of five semesters — approximately three in The Fu Foundation School of Engineering and Applied Science and two in the Journalism School. In addition to taking classes already offered at the Journalism and Engineering schools, students will attend a seminar and workshop designed specifically for the dual degree program. The seminar will teach students about the impact of digital techniques on journalism; the emerging role of citizens in the news process; the influence of social media; and the changing business models that will support newsgathering. In the workshop, students will use a hands-on approach to delve deeply into information design, focusing on how to build a site, section or application from concept to development, ensuring the editorial goals are kept uppermost in mind. For more information, please visit the program website.
The AP-Google Journalism Technology Scholarship has been announced. For more information, please visit their website.- http://www.journalism.columbia.edu/page/276-dual-degree-journalism-computer-science/279
CORE REQUIREMENT COMS W4111 Introduction to Databases COMS W4115 Programming Language and Translators COMS W4156 Advanced Software Engineering COMS W4170 User Interface Design CSOR W4231 Analysis of Algorithms COMS W4701 Artificial Intelligence REQUIRED TRACK COURSE (3) COMS W4112 Database Systems Implementation CSEE W4119 Computer Networks COMS W4160 Computer Graphics COMS W4162 Advanced Computer Graphics COMS W4172 3D User Interfaces and Augmented Reality COMS W4180 Network Security COMS W4705 Natural Language Processing COMS W4706 Spoken Language Processing COMS W4731 Computer Vision COMS W4771 Machine Learning COMS W4772 Advanced Machine Learning COMS W4999 Computing and the Humanities COMS W4995 Topics in CS (if focus is appropriate, needs approval from track advisor) ELECTIVE TRACK COURSES (2) COMS E6113 Topics in Database Systems COMS E6125 Web-Enhanced Information Management COMS E6175 Interaction Design COMS E6176 User Interfaces for Mobile and Wearable Computing COMS E6733 3D Photography COMS E6734 Computational Photography COMS E6735 Visual Databases COMS E6901 Projects in CS ELEN E6850 Visual Information Systems COMS E6998 Topics in CS with appropriate focus
Core seminars for all IGERT Students. (Beginning 2014) Approaches and Issues in Big Social Data Approaches and Issues in Social Data Analytics Analytics distribution, one course in a core approach to analytics: statistical / machine learning or visual analytics. Data Mining (STAT/IST) Machine Learning (CSE) Visual Analytics: Leveraging Geosocial Data (GEOG) Ethics and Scientific Responsibility distribution requirement Privacy in Statistical Databases (STAT/CSE) Data Privacy, Learning, and Games (CSE) Big Social Data and the Law (PLSC/CLJ) The Information Environment (IST) Social Data Analytics electives with substantial non-social science content (Social Science students) Network Science (PHYS) Vision-Based Tracking (CSE) Computational Regularity on Interdisciplinary, Large Data Sets (CSE) Pattern Recognition (CSE) Information Retrieval and Organization (IST) Web Analytics (IST) Spatial Analysis (GEOG) Most graduate courses in Statistics Social Data Analytics electives with substantial social science content (Non-Social Science students) Modeling Interdependent Data (CAS) Political Event Data and Forecasting (PLSC) Social Network Analysis (SOC) Causal Inference (PLSC) Democratic Representation: Big Data Approaches (PLSC) Multilevel Modeling (SOC) Spatial Demography (SOC) Intensive Longitudinal Data (HDFS) Geospatial Science in Anthropology (ANTH)