Teaching Data Science

We describe an introductory data science course, entitled Introduction to Data Science, offered at the University of Illinois at Urbana-Champaign. The course introduced general programming concepts by using the Python programming language with an emphasis on data preparation, processing, and presentation. The course had no prerequisites, and students were not expected to have any programming experience. This introductory course was designed to cover a wide range of topics, from the nature of data, to storage, to visualization, to probability and statistical analysis, to cloud and high performance computing, without becoming overly focused on any one subject. We conclude this article with a discussion of lessons learned and our plans to develop new data science courses.Comment: 10 pages, 4 figures, International Conference on Computational Science (ICCS 2016

Computationally-intensive Econometrics using a Distributed Matrix-programming Language

This paper reviews the need for powerful facilities in econometrics, focusing on concrete problems which arise in financial economics and in macroeconomics. We argue that the profession is being held back by the lack of easy to use generic software which is able to exploit the availability of cheap clusters of distributed computers. Our response is to extend, in a number of directions, the well known matrix-programming interpreted language Ox developed by the first author. We note three possible levels of extensions: (i) Ox with parallelization explicit in the Ox code; (ii) Ox with a parallelized run-time library; (iii) Ox with a parallelized interpreter. This paper studies and implements the first case, emphasizing the need for deterministic computing in science. We give examples in the context of financial economics and time-series modelling.Distributed computing; Econometrics; High-performance computing; Matrix-programming language

General Education Requirements: Fontbonne Catalog, 2018-2019

This catalog reflects an institution that is devoted to upholding its new, self-identified value of the common good. The addition of the Mission Core classes and restructuring of the GERs that took place in 2015 fundamentally changed how the program worked. A system that relies on Mission core being the “heart” of the GER program with “Pillars” of knowledge supporting the “structure” of Fontbonne is an important change. The institution is now focused on bringing its own version of a liberal arts education to its students rather than a more standardized one, coming close to finalizing the vision started in the 1970s.https://griffinshare.fontbonne.edu/gen-ed/1004/thumbnail.jp

An educational project for master’s program in computing

The curriculum of a specific master’s program is discussed in thematic and methodological aspect. The general plan, the target group and the educational parameters of the program are represented. The features of the curriculum as thematic areas, learning activities and schedule are discussed. Some statistical data concerning the program implementation are also provided

Computing and Information Science (CIS)

Cornell University Courses of Study Vol. 97 2005/200