Please visit WesMaps for a list of current offerings
Fall 2014
Can Machines Think? (Logic and Computation) (COMP 131)
Instructor: James Lipton
WesMaps Listing: COMP 131
Description: This course will address the question of machine reasoning and its scope through the perspective of computation and logic. We will start by studying the elements of mathematical logic, and will learn how to code in the ML programming language so we can approach the issues of automated deduction from both a technical and philosophical perspective. The course will also include extensive readings on consciousness and on the capabilities and limits of computation. Students will be required to write several detailed essays on the issues discussed in class and in the readings.
Digging the Digital Era: A Data Science Primer (QAC 211)
Instructors: Emmanuel Kaparakis and Pavel Oleinikov
WesMaps Listing: QAC 211
Description: The course introduces students to the practice of what has come to be known as data science. Using a multidisciplinary approach and data from a variety of sources that cover any aspect of everyday life–from credit card transactions to social media interactions and web searches–data scientists try to analyze and predict events, and behavior. The first part of the course defines the area and introduces basic concepts, tools and emerging applications. We describe how “big data” analysis affects both business practices and public policy, and discuss applications in different areas/disciplines. We also discuss the ethical, legal, and privacy dimensions of “big data” analysis. In part two of the course, we work on data acquisition and management and introduce appropriate programming and data management tools. In part three, we concentrate on basic analytical and visualization techniques as we explore and understand the emerging patterns. Using a learning-by-doing approach in a computing laboratory, students will learn how to write computer programs in R to access, organize, and analyze data through a series of small projects designed to illustrate the application of the techniques we develop for a variety of data sets and situations. Students will also engage in a semester-long project where they will access and use data from social media (Twitter) to address their own research questions.
Proseminar: Network Analysis (QAC 239/CIS 239)
Instructor: David Beveridge
WesMaps Listing: QAC 239
Description: Seminar leaders from physics, political science, psychology, and chemistry, as well as outside speakers, will introduce participants to network analysis and explore its applications across different topics and disciplines. The purpose of the course is to enable participants to use network analysis in their work and facilitated collaborations across disciplinary lines. In addition to the regular class meetings, we will schedule hands-on workshops for participants to become familiar with appropriate software and further develop their computing skills.
The Acceleration of Europe: Mobility and Communication, 1000-1700 (CHUM 267/HIST 392)
Instructors: Gary Shaw
WesMaps Listing: CHUM 267,
Description: This is a research course exploring the thesis that during the Middle Ages Europeans began to move faster, to move more often, and by doing so transformed the nature of social life, cultural life, and the character of selves and minds in the world. The course will explore the material aspects of this such as the nature and development of roads and bridges, ships and canals, inns and hospitality that sustained and encouraged advancing travel. Thematic importance will be given to the place of horses and horseriding in these developments. The course is about the history of communication and the idea that a particular sort of traveler was created through later medieval travel and became the means of cultural and psychological acceleration. The social and cognitive networks established through travel, including the exchange of letters and messages linked the local to the national. Merchants, pilgrims, soldiers, judge, students, preachers, and bureaucrats became the means of spreading news, changing views, and speeding up the world. This course will expose students to methods and skills in the digital humanities such as network analysis, Geographic Information systems, and database analysis.
Working with Python (QAC 155)
Instructor: William S. Boyd, Jr.
WesMaps Listing: QAC 155
Description: The course introduces students to programming, data management and analysis with Python. Through a series of hands on lab exercises students learn to work with a variety of data using a high-level programming language and associated libraries to effectively manage and analyze their data. The emphasis is on data exploration and visualization and includes work with unstructured data generated by social media interactions. While there are no prerequisites, a basic familiarity with computing tools, understanding of descriptive statistics and a willingness to make mistakes and learn from them is expected.
Working with Mathematica (QAC 153)
Instructor: William S. Boyd, Jr.
WesMaps Listing: QAC 153
Description: The course introduces students to Mathematica’s computing environment and all the basic features of the software. Starting with basic operations and computations students will be introduced to graphics and visualization, mathematical computations, and will learn through a series of hands-on lab exercises to use the Mathematica programming language for modeling and data analysis. While there are no prerequisites, a basic familiarity with computing tools, understanding of descriptive statistics along with a basic calculus background and a willingness to make mistakes and learn from them is expected.
Working with Stata (QAC 158)
Instructor: Emmanuel Kaparakis
WesMaps Listing: QAC 158
Description: The course introduces students to programming, data management and analysis with Stata. Through a series of hands on lab exercises students learn to work with a variety of data formats and use Stata’s programming capabilities to effectively manage and analyze their data, with an emphasis on data exploration and visualization. While there are no prerequisites, a basic familiarity with computing tools, understanding of descriptive statistics and a willingness to make mistakes and learn from them is expected.
Introduction to GIS (E&ES 322)
Instructor: Kim Diver
WesMaps Listing: E&ES 322
Description: Geographical information systems (GIS) are powerful tools for organizing, analyzing, and displaying spatial data. GIS has applications in a wide variety of fields including the natural sciences, public policy, business, and the humanities, literally any field that uses spatially distributed information. In this course we will explore the fundamentals of GIS with an emphasis on practical application of GIS to problems from a range of disciplines. The course will cover the basic theory of GIS, data collection and input, data management, spatial analysis, visualization, and map preparation. Course work will include lecture, discussion, and hands-on activities.
GIS Service Learning Laboratory (E&ES 324)
Instructor: Kim Diver
WesMaps Listing: E&ES 324
Description: This course supplements E&ES322 by providing students the opportunity to apply GIS concepts and skills to solve local problems in environmental sciences. Small groups of students will work closely with community groups to design a GIS, collect and analyze data, and draft a professional-quality report to the community.
Statistics: An Activity-Based Approach (PSYC 200)
Instructors: Andrea Patalano, Michael Greenstein
WesMaps Listing: PSYC 200
Description: This course will introduce the concepts and methods used in the analysis of quantitative data in the behavioral and life sciences. The approach will emphasize activity-based learning. Lectures will be used for the initial presentation and wrap-up of topics, but most class time will be devoted to activities in which students perform analyses. The topics covered will include descriptive statistics, sampling distributions, estimation, hypothesis testing, analysis of variance, and regression.
Spring 2015
Working with Excel and VBA (QAC 151)
Instructor: Pavel Oleinikov
WesMaps Listing: QAC 151
Description: Many of us know Excel for its spreadsheets: a quick and easy way to store some information, share it, and maybe make some charts. The goal of this course is to show you the more advanced features of Excel. We will write code in Visual Basic for Applications, learn how to import data from external databases and web-based resources, create custom menus to interact with a user, and examine how Excel can be used in business decision-making.
Working with Python (QAC 155)
Instructor: William S. Boyd, Jr.
WesMaps Listing: QAC 155
Description: The course introduces students to programming, data management, and analysis with Python. Through a series of hands-on lab exercises, students learn to work with a variety of data using a high-level programming language and associated libraries to effectively manage and analyze their data. The emphasis is on data exploration and visualization and includes work with unstructured data generated by social media interactions. While there are no prerequisites, a basic familiarity with computing tools, an understanding of descriptive statistics, and a willingness to make mistakes and learn from them is expected.
Introduction to Network Analysis (QAC 241/CIS 241)
Instructor: Pavel Oleinikov
WesMaps Listing: QAC 241
Description: This is an interdisciplinary hands-on course examining the application of network analysis in various fields. It will introduce students to the formalism of networks, software for network analysis, and applications from a range of disciplines (history, sociology, public health, business, political science). We will review the main concepts in network analysis, learn how to use the software (e.g. network analysis and GIS libraries in R), and will work through practice problems involving data from several sources (Twitter, Facebook, airlines, medical innovation, historical data). Upon completion of the course, students will be able to conduct independent research in their fields using network analysis tools.
Modeling and Data Analysis: From Molecules to Markets (PHYS 221/QAC 221)
Instructor: Francis Starr
WesMaps Listing: PHYS 221
Description: The development of models to describe physical or social phenomena has a long history in several disciplines, including physics, chemistry, economics, and sociology. With the emergence of ubiquitous computing resources, model building is becoming increasingly important across all disciplines. This course will examine how to apply modeling and computational thinking skills to a range of problems. Using examples drawn from physics, biology, economics, and social networks, we will discuss how to create models for complex systems that are both descriptive and predictive. The course will include significant computational work. No previous programming experience is required, but a willingness to learn simple programming methods is essential.
Science in the Making: Thinking Historically about Science (HIST 176/SISP 276)
Instructor: Paul Erickson
WesMaps Listing: HIST 176
Description: This course introduces students to a range of perspectives–drawn from history, sociology, anthropology, geography, media studies, and literary studies, among others–on how to write about the history of science. Throughout, the emphasis is on understanding the relationship between the histories of science we can tell and the materials that our histories draw upon, from publications and archival documents to oral histories, material culture, and film. In addition to reading academic literature, students will gain practical experience working with historical sources and conducting original research. Topics covered include scientific instruments and technology; the significance of the place where science is done (from laboratories to outer space); scientific “popularization”; science, visual culture, and cinema; gender, race, and science.
Medieval Europe (HIST 201/MDST 204)
Instructor: Gary Shaw
WesMaps Listing: HIST 201
Description: This introductory lecture course is the first of three that cover the history of Europe from the middle ages to the contemporary period. This course is a history of European politics, culture, and institutions from the end of the Roman Imperial era through 1520. Within a chronological framework we shall focus on the creation of kingdoms and government, the growth and crises of papal-dominated Christianity–its crusades and its philosophy–the rise and role of the knight, lady and aristocratic culture, masculinity and gender relations, the crises of the later Middle Ages, including the Black Death, heresy, mysticism, and war. These all contributed to the beginnings of the renaissance and the Reformation, events that ended the medieval period. We shall also at least glance at the borderlands of Europe, the edges of Islamic and Orthodox worlds.
The course will also provide students with basic introductory exposure to the ideas and methods of the Digital Humanities through course illustrations and discussions. This will probably include exercises in visualizing the past, exposure to Geographic Information Systems analysis, text-mining, and network analysis.
Economics of Big Data (ECON 282/QAC 282)
Instructor: Christiaan Hogendorn
WesMaps Listing: ECON 282
Description: “Big data” is a popular buzzword that describes techniques using very large datasets, often from nontraditional sources. Many technology firms essentially base their businesses on big data; Google, Facebook, and Amazon are all examples. Increasingly there are opportunities and pressures to employ these techniques in other areas of the economy and society such as government, healthcare, and education. This course examines (1) big data analysis techniques and how they relate to conventional economic statistics, (2) the effect of big data on the economy, society, and privacy, and (3) practical methods of big data analysis using the R statistics package.
Introduction to (Geo)Spatial Data Analysis and Visualization (QAC 231)
Instructor: Kim Diver
WesMaps Listing: QAC 231
Description: Geographic information systems (GIS) provide researchers, policy makers, and citizens with a powerful analytical framework for spatial pattern recognition, decision making, and data exploration. This course is designed to introduce social science and humanities students to spatial thinking through the collection, management, analysis, and visualization of geospatial data using both desktop and cloud-based platforms. Classes will consist of short lectures, hands-on training using different spatial analysis and geodesign technologies (e.g., ESRI ArcGIS, Google Fusion Tables, MapBox), group projects, critiques, and class discussions. Weekly readings and assignments will build skills and reinforce concepts introduced in class. The course will culminate in the development of a group project. Guest lectures by faculty across campus will allow students to comprehend the breadth of applicability geospatial thinking in today’s research arena. The course is part of Wesleyan’s Digital and Computational Knowledge Initiative and is aimed at students with limited or no prior GIS experience.
Digital Humanities: Intellectual Encounters in the 21st Century (CHUM 346/COL 346)
Instructor: Ethan Kleinberg
WesMaps Listing: CHUM 346
Description: Tweeting, Tumblr, blogs, and social media are changing the way that intellectuals produce, disseminate, discuss, and archive their work. This course will explore new modes of intellectual production and dissemination in theory and practice to explore and evaluate the ways that these forms are changing intellectual production (if indeed they are). The course combines two distinct components: attendance at the Center for the Humanities weekly Monday Night Lecture series faculty and weekly discussion meetings. The lectures will serve as content to be discussed, disseminated and archived using such forms as Twitter, Tumblr, and class blogs. Then we as a class will evaluate these artifacts in terms of efficacy, depth, and appropriateness to the subject under consideration. Students will learn strategies for informed live tweeting, editorial oversight of academic discussion forums, academic blogging, and other new media.
Working with R (QAC 156)
Instructor: Emmanuel Kaparakis
WesMaps Listing: QAC 156
Description: The course introduces students to programming, data management, and analysis with R. Through a series of hands-on lab exercises, students learn to work with a variety of data formats and use R’s programming language and associated packages to effectively manage and analyze their data, with an emphasis on data exploration and visualization. While there are no prerequisites, a basic familiarity with computing tools, an understanding of descriptive statistics, and a willingness to make mistakes and learn from them, is expected.
Working with SAS (QAC 157)
Instructor: Emmanuel Kaparakis
WesMaps Listing: QAC 157
Description: The course introduces students to programming, data management, and analysis with SAS. Through a series of hands-on lab exercises, students learn to work with a variety of data formats and use SAS’s programming capabilities to effectively manage and analyze their data, with an emphasis on data exploration and visualization. While there are no prerequisites, a basic familiarity with computing tools, an understanding of descriptive statistics, and a willingness to make mistakes and learn from them, is expected.