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https://ga.rice.edu/programs-study/courses/dsci/
DSCI 302 - INTRODUCTION TO DATA SCIENCE TOOLS AND MODELS. Short Title: DATA SCIENCE TOOLS AND MODELS Department: Data Science Grade Mode: Standard Letter Course Type: Lecture Credit Hours: 3 Restrictions: Enrollment is limited to students with a minor in Data Science. Enrollment is limited to Undergraduate, Undergraduate Professional or Visiting Undergraduate level students.
DSCI is a not-for-profit, industry body on data protection in India, setup by NASSCOM. It makes cyberspace safe, secure and trusted by establishing best practices, standards and initiatives in cyber security and privacy.
https://web-app.usc.edu/soc/syllabus/20211/32403.pdf
O ce Hours: TBD Lecture: Monday, Wednesday, 2:00 pm {3:50 pm, ONLINE Webpages: Piazza Class Pagefor everything except grades andUSC Blackboard Class Pagefor grades andGitHubfor code submission { All HWs, handouts, solutions will be posted in PDF format Prerequisite: DSCI 250 and MATH 208. Other Requirements: Computer programming skills.
https://informationscience.unt.edu/ms-data-science-degree-structure
BCIS 5600 - Visual Information Technologies. CSCE 5300 - Introduction to Big Data and Data Science. DSCI 5240 - Data Mining. DSCI 5330 - Enterprise Applications of Business Intelligence. DSCI 5340 - Predictive Analytics and Business Forecasting. DSCI 5360 - Data Visualization for Analytics. INFO 5307 - Knowledge Management Tools and Technologies.
http://catalog.wvu.edu/undergraduate/eberlycollegeofartsandsciences/data_science/
DSCI 480. Capstone in Data Science. 3 Hours. PR: DSCI 410 and DSCI 450 with a minimum grade of C- in each. Integration and application of the skills and methods acquired through the program to a real data set through group project (development of a data science pipeline).
https://bulletins.iu.edu/iub/sice/2020-2021/graduate/degree-programs/master-of-data-science-online/index.shtml
Students are required to complete 30 credit hours of graduate-level coursework for this degree. Students are required to complete two core courses (6 credit hours), two courses to form a specialization (6 credit hours), and a capstone project (3 credit hours).
https://datascience.usc.edu/courses/
Foundations, techniques, and algorithms for building knowledge graphs and doing so at scale. Topics include information extraction, data alignment, entity linking, and the Semantic Web. Recommended preparation: DSCI 553 and experience programming in Python. Prerequisite: DSCI 551 or CSCI 585, and DSCI 552 or CSCI 567.
https://www.randolphcollege.edu/computer-science/curriculum/
Credit hours:1. Prerequisite: CSCI 251. DSCI 2232. Introduction to Data Science. Data science is an interdisciplinary field incorporating statistical techniques with algorithms to collect and to process large data sets, in order to extract meaning and make decisions. Students will explore the collection and filtering of data, machine learning ...
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