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Data Analytics Fall 2021
Description:

Dates: August 20, 2021 - December 31, 2021
Concepts: Big Data, Analytics
Topics in Knowledge Graphs 2021
Description:
Prepare students for research in knowledge graphs. Teach students how to: Read and find relevant research papers, Present research ideas, Synthesize material, Identify gaps in existing research, Critically review (as one might do for a publication venue) Develop a literature corpus for use in research.
This course will discuss emerging trends in research on semantic technologies, focusing on knowledge representation, management, and modeling, including applications of knowledge graphs and ontologies. This is a seminar course, not a lecture course. Students will give many presentations and lead discussions throughout the course that will help them to understand, conduct, and evaluate academic research while we discuss the emerging trends in semantic technologies. This course is intended to give students a foundation that will allow them to participate in leading edge semantics research and also provide students with an opportunity to produce a research survey. The research survey may serve as a foundation for a related work chapter of a thesis and can also serve as a way to fulfill the research qualifying examination requirement in the CS program. Participants will read relevant papers and learn how to critically review ontology and knowledge graph papers, as well as ontologies and knowledge graphs themselves. They will also use the review to propose a research topic in knowledge graphs that can serve as the basis for their dissertation research, or as an investigation within a project they are currently working on.

Dates: August 26, 2021 - December 13, 2021
Concepts: ,
Data Science 2021
Description:
To instruct future scientists how to sustainably generate/ collect and use data for their research as well as for others: data science. To instruct future technologists how to understand and support essential data and information needs of a wide variety of producers and consumers For both to know tools, and requirements to properly handle data and information Will learn and be evaluated on the full life-cycle of data and relevant methods, technologies and best practices.

Data science is advancing the inductive conduct of science and is driven by the greater volumes, complexity and heterogeneity of data being made available over the Internet. Data science combines aspects of data management, library science, computer science, and physical science using supporting cyberinfrastructure and information technology. It is changing the way all of these disciplines do both their individual and collaborative work. Key methodologies in application areas based on real research experience are taught to build a skill-set. To instruct future scientists how to sustainably generate/ collect and use data for their research as well as for others: data science. To instruct future technologists how to understand and support essential data and information needs of a wide variety of producers and consumers For both to know tools, and requirements to properly handle data and information Will learn and be evaluated on the full life-cycle of data and relevant methods, technologies and best practices.

To instruct future scientists how to sustainably generate/ collect and use data for their research as well as for others: data science. To instruct future technologists how to understand and support essential data and information needs of a wide variety of producers and consumers For both to know tools, and requirements to properly handle data and information Will learn and be evaluated on the full life-cycle of data and relevant methods, technologies and best practices.


Dates: September 1, 2021 - December 20, 2021
Concepts: