This course explores scientific and technical systems that permeate our lives. By way of facial recognition, IQ tests, vaccine protocols, hydroelectric dams, and other systems, we will focus on the all-too-human questions embedded in processes of scientific innovation and technological development. Together, we will address the following: What makes something a scientific fact? Who benefits and who is harmed by emerging platforms? How do social, political, and economic inequities shape technology and vice-versa? Can we engineer alternate futures?

Historical overview of the development of computer art and the significant events leading to the development of the field. Projects include hands-on experience with computer imaging for use in the creation of fine art. Prerequisite: completion of foundation courses or consent of instructor. *IT Minors may request a course override from the IT Program Office, 413-545-6242 or via our Contact Form.

This course explores, through demonstrations and technical assignments, the creative possiblities of digital image creation and manipulation using primarily Photoshop, and the printmaking technique of Photopolymer Gravure processes.

Principles and applications of computer animation using Autodesk Maya software in film, video, music, and technology. Introduction to 2D and 3D animation programs. Skills acquired in preparation for production in second semester.  Prerequisites: ART 271 and 297Q. Should be followed by Art 384 Computer Animation II 

The second of a two semester sequence.  Animation techniques using digital tools as applied to film, video, music and technology.  Animation software (Maya) and professional compositing programs are used.  Development and design of personal work is stressed.  Emphasis is on creativity and professionalism.

This course provides an introduction into construction-related Computer-Aided-Design (CAD) tools.  By using industry-standard software in exercises and projects, students gain the capability to model construction projects and create industry-standard architectural drawings. BCT and Architecture Majors Only. 

Biology of nerve cells and cellular interactions in nervous systems. Lectures integrate structural, functional, molecular, and developmental approaches. Topics include neuronal anatomy and physiology, neural induction and pattern formation, development of neuronal connections, membrane potentials and neuronal signals, synapses, sensory systems, control of movement, systems neuroscience and neural plasticity. With Biology 494LI, this course satisfies the Integrative Experience requirement for BS-Biol majors.

The world is rich in data and our ability to process, manipulate, analyze, and visualize that data is growing in power. This course discusses how to understand and solve real-world problems using modern programming techniques. Concepts and techniques covered include the representation of data, fundamentals of programming including data types, expressions, objects, methods, program design, program testing and debugging, state representation, accessing, processing, and manipulating data, generating visualizations of data, interpreting results, and introductory data analytics using data to make predictions that help solve important problems in the world around us. Use of a laptop computer is required. (Gen. Ed. R2)

Open to freshman and sophomore Computer Science, Informatics, Math, and Physics students.

Prerequisite: Completion of the R1 General Education Requirement (or a score of 20 or higher on the Math Placement Exam, Part A) or one of the following courses: Math 101 & 102, Math 104, 127, 128, 131 or 132.

STUDENTS NEEDING SPECIAL PERMISSION MUST REQUEST OVERRIDES VIA THE ON-LINE FORM:  https://www.cics.umass.edu/overrides.

It is recommended that non-CICS majors take CS 119.

This course introduces foundational abstract data types and algorithms. The main focus is on the use of data structures in designing and developing programs to solve problems in a variety of domains. Specific topics include lists, sets, dictionaries, graphs, stacks and queues, searching, and sorting. There will be weekly programming assignments, programming and written exercises in lab sections, regular quizzes, and a cumulative final exam. Use of a personal laptop in class is required.

Open to freshman and sophomore Informatics and Computer Science students.

Prerequisite: CICS 110 with a grade of C or better.

USE OF PERSONAL LAPTOP IN CLASS IS REQUIRED.  STUDENTS NEEDING SPECIAL PERMISSION MUST REQUEST OVERRIDES VIA THE ON-LINE FORM:  https://www.cics.umass.edu/overrides.

Note: This is course replaces INFO 190T and CS 186

This course will examine the different ways that communication and digital technologies are shaping notions of work and labor. We will engage with ongoing debates on topics such as the sharing economy (e.g. Uber/Lyft driving), microwork (e.g. Amazon Mechanical Turk), microcelebrity (e.g. YouTube stars and Instagram influencers), tech entrepreneurship both in Silicon Valley and other parts of the world, as well as the work that goes into making popular consumer technologies like the iPhone. By the end of the course, you should have a critical understanding of the economic and social forces underlying shifts in digital labor, communication, technology, and work. The coursework includes digital assignments, reading responses, and a research paper.

Formerly listed as COMM 497DL

This course explores the relationship between digital media, politics, and democracy, examining the social and technical history of online activist projects in different societies around the world.

Course addresses the main debates and perspectives on the economic and social transformation associated with the spread of new media technologies, from various forms of collaborative and social media, to mobile phones and wireless broadband delivery systems.  

Our digital, social and civic life is increasingly powered by data. What we read, watch and buy is shaped by customization algorithms that are built based on a trove of digital behavioral data (e.g., Facebook likes and YouTube viewing history). This class will provide a broad picture of how our internet behavior is being tracked and analyzed for user psychology and public opinion as well as the implication of data mining on privacy and civic engagement. The course includes workshops in technical skills for social media data mining and visualization.

This course examines law, economy, and the social aspects of advanced communications technologies; with special emphasis on how the Internet has challenged dominant ways of thinking about the media.  We will focus on key issues of privacy, ownership, access, international balance, and cultural accountability in the use of newer technologies.   

Develop an understanding of digital culture, what its primary goals are, and what metaphors are useful in describing it. There are three units: a survey of digital culture and learn how to understand digital artworks and electronic literature, second, unit focuses on virtual reality technology as it has been represented in fiction and used by artists, lastly. the topic of cyborgs, and the merging of the human and the machine.

Broad introduction to hardware and software aspects of microcomputers. Four application areas: word processing, spreadsheets, databases, and telecommunications (access to the Internet). Prerequisites: reasonable high school math skills. Typing ability an important asset. Not for Computer Science Majors.  *CMPSCI majors see IT Advisor about waiver

Basic skills needed to use the Internet.  Web browsers, search strategies, basic Web page design, client-side and server-side programming, and cryptography.  Malware and viruses, e-mail management and etiquette.  Web-site management through UNIX commands, ftp file transfers, telnet sessions. Relevant and timely social, technical, and political topics.  Not intended for Computer Science majors. Programming experience not required. Prerequisites: some hands-on experience with PCs or MACs or UNIX.

The use of data in computer systems.  Formats for representing text, sound, images, ets. as strings of bits.  Basic information theory, use and limitations of file compression.  PreRequisite: R1

Advanced programming techniques in the Java language and elementary techniques of software engineering: documentation, coding style, basic testing principles, and informal reasoning about correctness. The notion of an abstract data structure and various important data structures: stacks, queues, linked lists, tree-based structures, and hash tables. Use of object-oriented language constructs for encapsulation of data objects.

In this course we examine the important problems in Usability, Human Computer Interaction, User Interfaces, and Human Centered Computing.  We will examine elements of HCI history, understanding human capabilities, HCI design, several methods for prototyping user interfaces, and new applications and paradigms in human computer interaction.

Data Science is the study of how we can transform raw observations (data) into meaningful information. The products of Data Science, such as models, reports, graphs and charts convey information in a concise way so that informed decisions can be made and new hypotheses can be formulated at an increasing rate. Data Science involves three main areas of focus: computer science, statistics, and knowledge of the domain under study. In this course we provide an introduction into the concepts, tools and techniques to perform the following steps in the data science process:

1. data acquisition, preparation
2. data exploration
3. data modeling
4. data visualization

To register for this course, fill out the CICS online override form.

This course covers decision making under uncertainty, focusing on topics such as evolutionary psychology, human biases, probabilistic thinking, risk taking, artificial intelligence, AI biases and algorithmic oppression.  The skills learned in this class can aide students in decision making at both personal and societal levels. They can help students recognize cognitive and algorithmic biases and comprehend the social implications of these biases. Examples from everyday decisions, business/finance, economics/policy making, sports, and AI decision making are discussed. (Gen. Ed. SB, DU)

Liars' Economics will introduce students to skeptical and effective consumption and production of information in the era of big data.  Students will learn how to spot and avoid statistical pitfalls, irrational decisions, fake news, information out of context, and blind faith.  The course will draw from historical examples and current events and from contemporary debates in economics and political economy. Students will practice interpreting, visualizing, and writing about big data.

Formerly ECON 397LE

This course provides an economist?s introduction to the study of scientific, inventive and technological activities.  The overarching focus is on understanding the microeconomic foundations of the knowledge production function and the determinants of innovation and technical change. We will begin with a brief historical overview of institutions supporting science and innovation and an introduction to the economic analysis of knowledge and ideas.  Other topics include: incentive mechanisms such as prizes and intellectual property (patents), diffusion of ideas and technology, models of cumulative innovation, private and public funding for R&D, scientific and university-industry collaboration, diversity and career choices among STEAM workers, and innovation in emerging economies. The course will emphasize gaining real world knowledge about these issues and motivate economic concepts covered in a variety of ways, such as through publicly available datasets, news articles, group debates, case studies, and guest speakers.

This course is designed to teach students to utilize open educational and public domain resources to create, edit, and deliver content for learning and instruction.  This course will introduce students to various web-based technologies for learning and teaching.  

This class is an introduction for students who want to build basic digital proficiencies and a stronger technical foundation while also remaining attentive to broader social, ethical, and political issues. Students can expect to learn how to use and analyze a variety of digital tools, programs, and platforms, including but not limited to: HTML and website customizing, interactive storytelling, visualizing research objectives, Photoshop, GIF creation and analysis, and basic programming. This class is required for the Digital Humanities and New Media Specialization in English at UMass. It is designed for students with a humanities background, and students from the other Five Colleges are encouraged to enroll.

 The course has three complementary aims: 1) to allow you to develop a specialized interest or skill, 2) to prepare you to enter the professional realm of technical writing and information design, and 3) to enable and assist you in developing strategies for lifelong learning. 

In this course we will explore modes of writing in and for digital environments. Students will develop skills that are relevant for a variety of writing-intensive professions, including publishing, content strategy, technical writing, marketing, and non-profit advocacy work. Students can expect to gain hands-on experience with software or platforms commonly used for digital or print publishing (e.g., WordPress or Adobe InDesign/Illustrator). This workshop-style course meets in a computer classroom; regular attendance is required. This course counts toward the following specializations in English: PWTC, SPOW, NMDH.

Prerequisite (may be waived with instructor approval): completion of English 200 and two of the following period survey courses-English 201, 202, 221, 268 or 269.

Outcomes. You will learn 1) the python programming language, 2) how to design simple algorithms, and 3) how to apply data science to the humanities.

Application of financial models in the business environment. The use of computer-based spreadsheet and simulation packages in business analysis.

This course introduces fundamental concepts and methods of geographic information system.  Emphasis on developing skills using GIS to solve typical spatial problems in the geosciences and environmental sciences.

Focus on the birth of Western science in the rational cosmology of the ancient Greeks, on its transmission to medieval Europe, and its eventual overturning in the Scientific Revolution of the 16th and 17th centuries. (Gen.Ed. HS)

This course will examine the nexus of science, technology, and war in the 20th century United States and Europe. This course will cover topics such as the development and use of chemical and biological warfare; scientific, political, medical, and philosophical implications of nuclear technology; the Manhattan Project and Big Science; Nazi science; Soviet agriculture; Cold War technology and the Space Race; missile technology; and psychological research and the military. As a unifying theme we will consider the impact of technological determinism and the centrality of science and technology in wartime politics and practice. Readings will consist of primary and secondary sources as well as historical and contemporary films. Requirements will include writing several short papers as well as a longer historiographical essay.

This course examines the strategic use of technology in modern hospitality and tourism organizations including the utilization of Information and Communication Technologies (ICT) and social media as a marketing and management tool. The application and use of both business intelligence and hospitality business analytics is also explored.

This course introduces foundational abstract data types and algorithms. The main focus is on the use of data structures in designing and developing programs to solve problems in a variety of domains. Specific topics include lists, sets, maps, graphs, stacks, queues, searching, and sorting. (Gen Ed R2)

The terms "data science" and "big data" appear in the news media and in everyday conversations. Moreover, we are told that we live in the "age of information", where almost every business venture and scientific research initiative collect a massive amount of data which may contain valuable information. This course is an introduction to the concepts and skills involved with the collection, management, analysis, and presentation of large data sets and the data products that result from the work of data scientists. Privacy and ethical issues are discussed. Students will work with data from the financial, epidemiological, educational, and other domains. The course provides many case studies and examples of real-world data that students work with using the R programming language as well as the structured query language (SQL). This course does not satisfy requirements for the CS major.

Course introduces students to writing and reporting for radio or podcasting. Students will practice pitching stories, arranging and conducting interviews, as well as writing and mixing radio scripts.  

How can journalists use data to find stories? How can they tell stories through data? This hands-on course provides students with the knowledge and skills necessary to begin gathering, analyzing and visualizing interactive, data-driven stories. Students will work in small groups to tackle questions pertaining to ethical data sourcing, data analysis and making data meaningful for the public. They will also produce their own exciting and thought-provoking digital news stories. Prior experience with advanced statistics, web design or computer programming is neither assumed nor necessary, and course content will adapt to students' collective skills. However, a willingness to experiment, learn new technologies and embrace iteration in a cooperative environment is a must.

Students will learn basic web design, HTML and CSS skills, and by the end of the semester they will be able to build a basic website, including how to incorporate JavaScript plugins. The course will also cover online ethics, mobile strategy, search engine optimization, and the role of social media in successfully publishing journalism work online.

This course explores the historical origins of Alternative Dispute Resolution (ADR) in immigrant, religious, and indigenous communities in the U.S. and its development over the past 300 years.  Why have advocates in the legal, commercial, labor, educational, and community sectors promoted its use?  What has their impact been on the various forms of ADR?  Whose interests are served by ADR?  A critical analysis of mediation, arbitration, negotiation, and online dispute resolution in comparison to the judicial system include attention to how issues of power imbalances and identity impact ADR.  We will also briefly explore international dispute resolution and consider its similarities and differences to ADR in this country.

Explore a broad range of topics related to constitutional law as well as controversies in the area of intellectual property law, and explore the current debate on cryptography, online gambling, internet taxes, as well as new problems raised by the spread of wireless technologies. Finally, students will consider several issues that touch on ecommerce and online dispute resolution. 

This course will introduce students to the use of probabilisitic methods in computational linguistics, focusing on problems of disambiguation and classification. Students will be introduced to basic probability and information theory, as well as basic tools used in NLP applications such as Hidden Markov Models. Topics covered will include the application of statistical methods to problems of word sense disambiguation, part of speech tagging, and sentiment analysis. This course complements LINGUIST 409, though LINGUIST 409 is not a formal prerequisite. This course requires that enrolled students have already satisfied their basic math requirements (R1), but no specialized math background is assumed.

The world is becoming increasingly data rich, and our ability to make good decisions in all realms - from personal to policy - rests on our abilities to analyze and convey data in meaningful ways.  Unfortunately, human beings are limited in our perceptual and cognitive abilities, making it difficult for us to use these large amounts of data. Data visualization holds promise as one mechanism for making sense of and presenting large amounts of data in a way that reduces information overload, and supports comprehension, memory, and decision-making. This course will prepare students to become visualization designers by providing them with an overview of visualization-types, design strategies, hands-on experience developing visualizations, and approaches to evaluate the effectiveness of the visualizations they create. Students will also become effective visualization consumers, equipped with the knowledge to assess the credibility of visualizations, detect misrepresentations of data, and reason about alternative explanations for the data. We will use an array of real-world examples from sources such as finance, healthcare, government policy, social science, and sports.

Explores the internet's impact on the marketing discipline and the effective use of this technology; the internet's effect on marketing strategy, consumer behavior, advertising, retailing, and distribution. Prerequisite: MARKETNG 300 or 301

Technology is at the center of many valuable marketing tools and practices. For example, marketers commonly use social media, such as Twitter, Youtube, Facebook, and Instagram; and with various technologies, new approaches and principles have emerged,
such as permission marketing and inbound marketing. New types, and increased amounts, of data associated with consumer use of technologies has made marketing analytics vital to effective decision making and performance diagnostics and evaluation (e.g., ROI). It is extremely important for marketers to understand how to effectively use these technologies, leverage new approaches and principles, and understand how to analyze and leverage associated data.

Language is the main and most fundamental form of human communication. Through language we are able to communicate and express different kinds of needs, attitudes, feelings and intentions. One of the main data sources from language is text data such as e-news, company reports, emails, online communities, social media conversations and customer reviews. Text data is growing exponentially offering organizations unprecedented resources to monitor customer experience feedback and brand communications (Forbes 2016). However, there are three main characteristics that make challenging the analysis of text: It’s unstructured, it has high volume and it varies across time.This has resulted in the development of an emerging class of research methods using text mining, the process of structuring large volumes of text data to discover explicit and implicit meanings. Text mining methods are currently applied on a wide range of business contexts such as automated sentiment detection from social media, speech recognition in call centers and customer’s keyword search patterns (Forrester 2016).In this course, students will learn how to use this type of data for marketing research and how to develop analytics solutions in the areas of customer experience, sentiment analysis, marketing communications and segmentation. In particular, we will focus on developing innovative text analytic solutions for marketing problems, implement them through a text mining model and evaluate them by assessing their accuracy.The specific objectives of this course are *Understanding how textual data can be used for market research and gaining consumer insight * Introducing the text mining process, its main stages and components *Providing hands on training on using text analytics tools and software.

Introduction to MIDI and computer music synthesis. Prerequisite: consent of instructor.

This survey course will provide a state-of-the-art overview of the role of information technology in healthcare with emphasis on essential content and applications in healthcare informatics.

This course provides an introduction to Business Intelligence and Analytics,including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision making. Business Intelligence requires foundation knowlede in data models and data retrieval, thus this course will review logical datamodels for both relational database systems and data warehouses.Students will learn to extract and manipulate data from these systems using Structured Query Language (SQL). This course covers visualization, reporting, and dashboard design with experiential learning using leading industry applications, including Excel PivotTables, SAP Business Warehouse, SAP Business Objects Analysis, Microsoft Access,and,Tableau.

Computer simulation presented for carrying out trial-and-error experiments on computer approximations of real, management systems. The goal is to 1) validate a new idea quickly, 2) diagnose potential product design problems, 3) optimize performance of complex systems, and 4) learn about something complex. The Arena environment, based on the SIMAN language, used to build models and video game-like animations.

Provides an introduction to project management, focusing on the integration of business operations and information management, and techniques to effectively manage the implementation of such projects.

This course covers topics in Advanced Business Intelligence and Analytics, including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision making. Business Intelligence requires foundation knowledge in data storage and retrieval, thus this course provides content on conceptual data models for both database management systems and data warehouses. Students will learn to extract and manipulate data from these systems. Data mining, visualization, and statistical analysis along with reporting options such as management dashboards and balanced scorecards will be covered. Technologies utilized in the course include SAP Predictive Analysis Suite, Tableau, SPSS, and RapidMiner. OIM 240 Business Data Analysis is a prerequisite for this course.

Introduction to Symbolic Logic. Two logical systems are examined:  Sentential Logic and Predicate Logic. Work is equally divided between translating English sentences into symbolic notation, and constructing formal derivations.  (Gen.Ed. R2)

The study of networks in political science, the social sciences and beyond has grown rapidly in recent years.  This course is a comprehensive introduction to methods for  analyzing  network  data.   We  will  cover  network  data  collection  and  management,  the formulation of network theory and hypotheses, network visualization and description;  and methods  for  the  statistical  analysis  of  networks.  The course will introduce multiple applications of political network analysis in the real world.

The course examines power and uses of digital technologies in national, transnational and global governance. Topics include inequalities, transparency, civil society, state capacity, privacy, social movements, cyberwar and electoral politics. Satisfies the Integrative Experience requirement for BA-PolSci majors.

The aim of this course is to provide students with the skills necessary to tell interesting and useful stories in real-world encounters with data. Specifically, they will develop the statistical and programming expertise necessary to analyze datasets with complex relationships between variables. Students will gain hands-on experience summarizing, visualizing, modeling, and analyzing data. Students will learn how to build statistical models that can be used to describe and evaluate multidimensional relationships that exist in the real world. Specific methods covered will include linear, logistic, and Poisson regression. This course will introduce students to the R statistical computing language and by the end of the course will require substantial independent programming. To the extent possible, the course will draw on real data sets from biological and biomedical applications. This course is designed for students who are looking for a second course in applied statistics/biostatistics (e.g. beyond PUBHLTH 391B or STAT 240), or an accelerated introduction to statistics and modern statistical computing.

We will explore and develop a variety of univariate time-series techniques. We will show how to use these techniques to make forecasts for different economic variables. We will compare forecasts using univariate methods with forecasts obtained using econometric models.

Formerly RES-ECON 497A.

Basic concepts in econometric methods. Estimation of the general linear model with applications to theoretical economic models. Introduction to problems and methods to solve problems common in economic data. Nonlinear models, binary independent variables and binary dependent viable methods. Application of methods to real world data; emphasis is on application through use of econometric software. Students undertake research projects.

Students who are interested in the course but have not completed all of the prerequisites can email the course instructor to request permission to enroll.

This is an information technology course for non-technical students. Some questions to be addressed are: How should one address the Internet latency problem when the speed of your delivery of content to your customers is at stake? How do firms secure their tangible and intangible assets that face ever mounting threats from cyber-attacks? What is happening behind the scenes in B2B marketplaces? How can businesses effectively exploit the power of search engine marketing (SEM) and mobile and location-based marketing?
Through class discussion and hands-on Web site design projects with local companies, students will have the opportunity to: (1) Understand Internet enabling technology and its impact on a firm’s business processes and strategies. Class discussions will focus on Internet security, e-commerce payments, search engine marketing, and B2B marketplaces, plus the positioning of Internet strategies in relation to a company’s overall business framework. (2) Act as consultants and provide e-Solutions to a local client by designing a prototypical Web site and developing a set of business strategies.

In this graduate-level technology course, we reverse the idiom about “not being able to see the forest for the trees” into an almost opposite approach of: “comprehending the trees in order to perceive the forest.” Readings focus on technology fundamentals such as Internet network architecture and limitations; e-Commerce implementation methodology, Internet Marketing, and the transforming impact of technology on B2B commerce, e-Commerce security and encryption (PKI), and the consequently inevitable security threats and defense mechanisms. Class discussions and student research work concentrate on the business implications of technology, presenting both opportunities and challenges.
More importantly, students will have the hands-on opportunity to design an effective Web site and provide comprehensive e-business recommendations for a small business, from marketing strategy to technology management.

This course will revolve around how various sport properties are leveraging new media and new technologies, specifically, the Internet and mobile technology.  Modules to be discussed include ecommerce, sponsorship, social networking and online communities, streaming video, user-enhanced content, and user-generated content.

Introduction to the range of computer applications available for the environmental design professions. Site analysis techniques, computer aided design, and methods of data management on the computer.