Looking to know a bit more about my academic experience? Look here.
This post contains a list of some of the relevant coursework I’ve taken while earning my bachelor’s at the University of Illinois. While this is not a complete list, I have unofficial and offical transcripts available upon request. This is simply to give potential employers or collaborators a brief introduction to some of the experience I have. Courses are broken up by subject area by alphabetical order, and university course descriptions are included when provided.
Computer Science
CS 107 Data Science Discovery: Data Science Discovery is the intersection of statistics, computation, and real-world relevance. As a project-driven course, students perform hands-on-analysis of real-world datasets to analyze and discover the impact of the data. Throughout each experience, students reflect on the social issues surrounding data analysis such as privacy and design.
Geography
GEOG 379 Introduction to GIS systems: Investigates the fundamentals of geographic information science as well as the basic skills in the execution of that theoretical knowledge with industry standard software packages. Student will learn the basics of projections and coordinate systems, how geographic information is stored and manipulated, and the theory and practice behind the production of thematic maps.
Information Sciences
IS 457 Introduction to Data Science: This course introduces students to data science approaches that have emerged from recent advances in programming and computing technology. They will learn to collect and use data from a variety of sources, including the web, in a modern statistical inference and visualization paradigm. The course will be based in the programming language R, but will also use HTML, regular expressions, basic Unix tools, XML, and SQL. Supervised and unsupervised statistical learning techniques made possible by recent advances in computing power will also be covered.
Mathematics
MATH 241 Calculus III: Third course in calculus and analytic geometry including vector analysis: Euclidean space, partial differentiation, multiple integrals, line integrals and surface integrals, the integral theorems of vector calculus.
Political Science
PS 230 Introduction to Political Research: Surveys the principles that guide empirical research in political science; emphasizes definition of research problems, principles and practices of measurement, use of data as evidence, and data analysis.
PS 292 Undergraduate Research Practicum: With Professor Scott Althaus. Worked 10 hours a week at the Cline Center for Advanced Social Research contributing to the Rule of Law and Coup d’État Projects. Undertook an independent study with the Data Analytics and Management team on data management and analysis in a research firm setting. Culminated with a term paper utilizing Cline Center data on the effects of interstate war on coup success. Course description by Jonathan Bonaguro
PS 490 Individual Study: With Professor Scott Althaus. Worked 10 hours a week at the Cline Center for Advanced Social Research contributing to the expansion of the Coup d’État Project. Undertook an independent study with the Data Analytics and Management team on data management and analysis in a research firm setting. Culminated with a term paper utilizing Cline Center data on the effects of IMF loan programs on regime stability. Course description by Jonathan Bonaguro
PS 495 Senior Honors Seminar: Provides an advanced overview of methodological issues in political science especially identification of research questions and design of research strategies in political science appropriate for a senior thesis. Requires completion of a substantial research proposal. Culminated in prospectus entitled “Making Friends and Influencing People: The Effects of Social Media on Political Knowledge Misperceptions”.
Statistics
STAT 200 Statistical Analysis: Survey of statistical concepts, data analysis, designed and observational studies and statistical models. Statistical computing using a statistical package such as R or a spreadsheet. Topics to be covered include data summary and visualization, study design, elementary probability, categorical data, comparative experiments, multiple linear regression, analysis of variance, statistical inferences and model diagnostics. May be taken as a first statistics course for quantitatively oriented students, or as a second course to follow a basic concepts course.
STAT 400 Statistics and Probability I: Introduction to mathematical statistics that develops probability as needed; includes the calculus of probability, random variables, expectation, distribution functions, central limit theorem, point estimation, confidence intervals, and hypothesis testing.