Technology Development and Management

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This track allows students to focus in the ways in which technology solutions can be can developed, implemented, managed, and maintained in organizations.

FALL 2021 Course Descriptions

Course options WITH computational/digital focus:

CDT 30665: Football in America taught by Katherine Walden
Football is one of the most enduringly popular and significant cultural activities in the United States. Since the late 19th century, football has occupied an important place for those wishing to define and understand "America." And Notre Dame football plays a central role in that story, with larger-than-life figures and stories, from Knute Rockne's "Win one for the Gipper" line to the "Four Horsemen" backfield that led the program to a second national championship in 1924. The mythic proportions of the University's football program cast a long shadow on the institution's history, cultural significance, and traditions. This course focuses on Notre Dame football history as an entry point into larger questions about the cultural, historical, and social significance of football in the U.S. Who has been allowed to play on what terms? How have events from Notre Dame football's past been remembered and re-imagined? How has success in Notre Dame football been defined and redefined? In particular, the course will focus on how Notre Dame football became a touchstone for Catholic communities and institutions across the country navigating the fraught terrain of immigration, whiteness, and religious practice. This course will take up those questions through significant engagement with University Archive collections related to Notre Dame football, working with digitized materials to think about questions relating to access and discovery of physical and electronic collections. This course will include hands-on work with metadata, encoding and markup, digitization, and digital preservation/access through a collaboration with the University Archives and the Navari Family Center for Digital Scholarship. Readings for this course will include chapters from texts such as Murray Sperber's Shake Down the Thunder: The Creation of Notre Dame Football (1993), TriStar Pictures' Rudy (1993), Steve Delsohn's Talking Irish: The Oral History of Notre Dame Football (2001), Jerry Barca's Unbeatable: Notre Dame's 1988 Championship and the Last Great College Football Season (2014), David Roediger's Working Toward Whiteness: How America's Immigrants Became White (2005), David Roediger's The Wages of Whiteness: Race and the Making of the American Working Class (1991), and Noel Ignatiev's How the Irish Became White (1995). Class meetings will be split between discussions of conceptual readings and applied work with library and information science technologies and systems. Coursework may include response papers, hands-on work with data, and a final project. Familiarity with archival methods, library/information science, data science, or computer science tools and methods is NOT a prerequisite for this course.

CDT 40200 Privacy & Security taught by James Smith
This course provides students with a practical, hands-on exposure to information security topics. This course follows the curriculum for the industry standard Security+ certification program. Students successfully completing this course will be prepared to take the Security+ certification exam. This credential is a valuable way to demonstrate knowledge of information security topics to potential employers.Students completing this course will be prepared to address the information security issues facing managers and leaders in any organization. The course is also an excellent starting point for those seeking a career in information security or risk management consulting. Specific topics covered include:
  • Network Security
  • Compliance and Operational Security
  • Threats and Vulnerabilities
  • Application, Data and Host Security
  • Access Control and Identity Management
  • Cryptography

CDT 40211: Psychology of Info Analysis taught by Mitche Kajzer
The world is full of information that we are continuously evaluating. As part of the human thought process, we build mental models through which we process, analyze, and form conclusions as to the meaning of that information. This is a natural function of the human cognitive process. We construct our own version of reality based on the information that we have. The problem with this is that we frequently make judgments on large amounts of incomplete and ambiguous information. This is something that the mind is poorly wired to deal with effectively. In addition, we often fail to recognize our inherent biases in evaluation, cause & effect, and estimating probabilities. Some of these biases include confirmation, hindsight, anchoring, availability, and self-serving. The pitfalls set by the human mental process for analyzing information cannot be eliminated; they are part of us. What can be done is to learn how to look for and to recognize these mental obstacles, and how to develop procedures designed to offset them. We must distinguish between what you know and what you believe. The difference between fact and opinion; between knowledge and thinking. Through primary source readings and a declassified book from a government intelligence agency, students will learn how to be self-conscious about their reasoning processes. Students will learn techniques for critical thinking, creative thinking, and analytical thinking. About how you make judgments and reach conclusions, not just about the judgments and conclusions themselves. The goal is to equip students with the thinking and reasoning skills necessary to better construct a more accurate reality.

CDT 40610 Case Study - Computing-Based Entrepreneurship (CSE 40923) taught by Kevin Bowyer or other staff instructors
The purpose of this course is to Inform, Introduce and (hopefully) Inspire you. You will become Informed about computing-based entrepreneurship case studies across a wide variety of areas: computer software, computer hardware, healthcare technologies, databases, web services, data analytics and more. You will also become Informed about different aspects of the entrepreneurship challenge. You will be Introduced to guest speakers who are, or who have been, principals in developing technology, founding companies, running companies, selecting technologies for venture capital investment, etc. As a result, you will hopefully be Inspired to consider pursuing computing-based entrepreneurship opportunity.

CDT 40640 Data Science taught by Meng Jiang
Data mining and machine learning techniques have been widely used in many domains. The focus of this course will primarily be on fundamental concepts and methods in data science, with relevant inclusions and references from probability, statistics, pattern recognition, databases, and information theory. The course will give students an opportunity to implement and experiment with some of the concepts (e.g., classification, clustering, frequent pattern mining), and also apply them to the real-world data sets. Instructor permission required

Course options WITHOUT computational/digital focus (only one is allowed):

CDT 20510 Science, Technology, and Society(STV 20556) taught by Samuel Hall
This course introduces the interdisciplinary field of science and technology studies. Our concern will be with science and technology (including medicine) as social and historical, i.e., as human, phenomena. We shall examine the divergent roots of contemporary science and technology, and the similarities and (sometimes surprising) differences in their methods and goals. The central theme of the course will be the ways in which science and technology interact with other aspects of society, including the effects of technical and theoretical innovation in bringing about social change, and the social shaping of science and technology themselves by cultural, economic and political forces. Because science/society interactions so frequently lead to public controversy and conflict, we shall also explore what resources are available to mediate such conflicts in an avowedly democratic society.
 
CDT 40630 Ethical and Professional Issues (CSE 40175) taught by Kevin Bowyer or other staff instructors
This course seeks to develop a solid foundation for reasoning about the difficult ethical, professional, and social controversies that arise in the computing field. Emphasis is placed on identifying the appropriate legal and professional context and applying sound critical thinking skills to a problem. Topics covered include relevant professional codes of ethics, encryption/privacy/surveillance, freedom of speech, "cracking" of computer systems, development of safety-critical software, whistle blowing, and intellectual property. This course relies heavily on case study of real incidents, both historical and current.
 

WINTER 2021 Course Descriptions

Course options WITH computational/digital focus:

CDT 24610 Web Development Bootcamp taught by TBD
Web development is an in-demand skill that spans across all job markets. However, getting into web development can feel somewhat daunting to those without backgrounds in computer science. Designed for students who have little or no prior coding/programming experience, South Bend Code School?s 3-week Web Development Bootcamp will demystify programming for the web, provide an introduction to databases, and equip students with the skills to deploy web applications online. Students will leave the bootcamp with a market-ready portfolio of work and a Certificate of Completion from South Bend Code School that will demonstrate their knowledge and skills to potential employers.If you?ve been wondering how to break into the world of programming and get hands-on, practical experience building web applications, this bootcamp is for you! 0-credit hour

Course options WITHOUT computational/digital focus:

CDT 30040 Technology, Culture, Careers taught by Sarvanan Devaraj
This course is designed to introduce students to the vibrant culture of innovation, emerging technologies, and career opportunities in the technology industry and in Silicon Valley. Industry experts from innovative companies will present on topics across a wide spectrum of functional areas such as - new product idea generation and design, funding, operations and scaling, marketing, data science, and other topics. While the course is open to all students, those attending/planning for the Silicon Valley Semester offered by ND California are encouraged to sign up. 1-credit hour

SPRING 2021 Course Descriptions

Course options WITH computational/digital focus:

CDT 24505 Data Ethics taught by Don Howard
Philosophical exploration of ethical issues involved in data science.

CDT 30200 Privacy and Security taught by Jared Bulosan
In today’s digital age, people and organizations produce and deal with unprecedented amounts of data. Thus, issues concerning information privacy and security have taken on critical importance. Information privacy and security are fundamentally about data protection. Information privacy refers to decisions around what information should be protected, from whom, why, and issues related to the ownership of information; whereas information security refers to the tactics and technologies to ensure data protection. In this course, we will address questions such as: How should organizations manage privacy and security issues? What are the various privacy and security threats that organizations and individuals face? What are the current advancements in privacy and security technologies and government regulations? We will learn about economics of privacy, biases and heuristics in privacy decisions, privacy ethics, social engineering, and public policy and regulations. Also, we will gain an understanding of security threats and gain insight into managerial best practices for managing information security. This course will involve a number of assignments along with interactive in-class exercises aimed at enhancing your privacy and security decisions.

CDT 30390 Sport and Big Data taught by Katherine Walden
Sport is one of the most enduringly popular and significant cultural activities in the United States. Data has always been a central part of professional sport in the US, from Henry Chadwick's invention of the baseball box score in the 1850s to the National Football League's use of Wonderlic test scores to evaluate players. This course focuses on the intersecting structures of power and identity that shape how we make sense of the "datification" of professional sport. By focusing on the cultural significance of sport data, this course will put the datafication of sport in historical context and trace the ways the datafication of sport has impacted athletes, fans, media, and other stakeholders in the sport industry. The course will also delve into the technology systems used to collect and analyze sport data, from the TrackMan and PITCHf/x systems used in Major League Baseball to the National Football League's Next Gen Stats partnership to emerging computer vision and artificial intelligence research methods. Readings for this course will draw on texts like Christopher Phillips' Scouting and Scoring: How We Know What We Know About Baseball (2019), Ruha Benjamin's Captivating Technology: Race, Carceral Technoscience, and Liberatory Imagination in Everyday Life (2019), and Michael Lewis' Moneyball: The Art of Winning an Unfair Game (2004). Class meetings will be split between discussions of conceptual readings and applied work with sport data and technology systems. Coursework may include response papers, hands-on work with data, and a final project. Familiarity with statistical analysis, data science, or computer science tools and methods is NOT a prerequisite for this course.

CDT 30395 Race and Technologies of Surveillance taught by Katherine Walden
The United States has a long history of using its most cutting-edge science and technology to discriminate, marginalize, oppress, and surveil. The poorhouse and scientific charity of an earlier era have been replaced by digital tracking and automated decision-making systems like facial recognition and risk prediction algorithms. This course focuses on how automated systems are tasked with making life-and-death choices: which neighborhoods get policed, which families get food, who has housing, and who remains homeless. This course will examine black box tools used in K-12 education, social services, and the criminal justice system to better understand how these technologies reinforce and worsen existing structural inequalities and systems of oppression. Class meetings will be split between discussions of conceptual readings and applied work with technology systems. Readings for this course will draw on texts that include Safiya Noble's Algorithms of Oppression: How Search Engines Reinforce Racism (2018), Virginia Eubanks' Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (2018), Catherine D'Ignazio and Lauren Klein's Data Feminism (2020), and Meredith Broussard's Artificial Unintelligence: How Computers Misunderstand the World (2019). This course will also examine the advocacy and activism work undertaken by groups like Our Data Bodies, Data 4 Black Lives, Algorithmic Justice League, Auditing Algorithms, Big Brother Watch, and Chicago-based Citizens Police Data Project. Coursework may include response papers, hands-on work, and a final project. Familiarity with statistical analysis, data science, or computer science tools and methods is NOT a prerequisite for this course.

CDT 30660 Data Storytelling taught by Jennifer Cronin
A principal challenge for anyone working with ubiquitous data is communicating results of an analysis to stakeholders. This course teaches students the art of clear, effective, and engaging data presentation with attention to the business necessity of translating complex technical subjects into actionable insights for a lay audience. Students will harness the power of storytelling for the strategic benefit of an organization by turning a raw set of data into a compelling message that resonates with an intended audience. 1.500 Credit hours
Note: look for 2 sections to complete a semester at 3.000 credit hrs

CDT 37610 - Section 01: Tech Dev and Soc Media taught by Chuck Crowell
This course is intended to be used only for special projects that are approved in advance by the department. Special requirements and arrangement must be made to take this course.

CDT 40120 VCD 10: Visualization of Data taught by Neeta Verma
The course focuses on the relevance of data in the current socio-political and economicdynamic. It defines how numbers and data can be turned into compelling narratives tocommunicate complex ideas using large data sets and then reframing them using graphicdesign principles. Powerful and compelling rendition of data help in determining discourse,creating awareness, affecting policy, and assisting understanding of issues that surround us inthis complex world. Assignments focus on the crucial role that designers can play in packaginginformation in ways where dense and incomprehensible data can be made comprehensible andaccessible for all audiences.The course is aimed at developing an understanding of what data means to humans and howdoes its visualization helps communicate ideas in the fields of medicine, technology and socialsciences. All assignments touch upon measurement, collection, reporting, analysis butultimately focuses on visualization. Visualization is when the data comes alive and is ready to beused to communicate a complex concept be it numeric, spatial, process or temporal. Types ofdata covered in this course include but are not limited to: geographical, cultural, scientific,financial, statistical, meteorological, natural, and transportation data.The design process for each assignment therefore explores static, dynamic, interactive, and 3-dimensional formats of representation in an effort to understand why a certain format is moresuitable for the nature of data, its analysis and therefore its visual representation.Proficiency in Excel is required.

CDT 40205 Computer Security taught by John McEachen
This course is a survey of topics in realm of computer security. This course will introduce the students to many contemporary topics in computer security ranging from PKIs (Public Key Infrastructures) to cyber-warfare to security ethics. Students will learn fundamental concepts of security that can be applied to many; traditional aspects of computer programming and computer systems design. The course will culminate in a research project where the student will have an opportunity to more fully investigate a topic related to the course. Instructor permission required

Course options WITHOUT computational/digital focus (only one is allowed):

CDT 20510 Science, Technology, and Society(STV 20556) taught by Anna Geltzer
This course introduces the interdisciplinary field of science and technology studies. Our concern will be with science and technology (including medicine) as social and historical, i.e., as human, phenomena. We shall examine the divergent roots of contemporary science and technology, and the similarities and (sometimes surprising) differences in their methods and goals. The central theme of the course will be the ways in which science and technology interact with other aspects of society, including the effects of technical and theoretical innovation in bringing about social change, and the social shaping of science and technology themselves by cultural, economic and political forces. Because science/society interactions so frequently lead to public controversy and conflict, we shall also explore what resources are available to mediate such conflicts in an avowedly democratic society.
 
CDT 40630 Ethical and Professional Issues (CSE 40175) taught by Kevin Bowyer or other staff instructors
This course seeks to develop a solid foundation for reasoning about the difficult ethical, professional, and social controversies that arise in the computing field. Emphasis is placed on identifying the appropriate legal and professional context and applying sound critical thinking skills to a problem. Topics covered include relevant professional codes of ethics, encryption/privacy/surveillance, freedom of speech, "cracking" of computer systems, development of safety-critical software, whistle blowing, and intellectual property. This course relies heavily on case study of real incidents, both historical and current.
 

SUMMER 2021 Course Descriptions

Course options WITH computational/digital focus:

CDT 24510 Robot Ethics (Online) taught by TBD
Robots or "autonomous systems" play an ever-increasing role in many areas, from weapons systems and driverless cars to health care and consumer services. As a result, it is ever more important to ask whether it makes any sense to speak of such systems' behaving ethically and how we can build into their programming what some call "ethics modules." After a brief technical introduction to the field, this course will approach these questions through contemporary philosophical literature on robot ethics and through popular media, including science fiction text and video. This is an online course with required, regular class sessions each week. Class meetings are online via Zoom webinar software (provided by the University).Note: this course is delivered fully online. The course design combines required live weekly meetings online with self-scheduled lectures, problems, assignments, and interactive learning materials. To participate, students will need to have a computer with webcam, reliable internet connection, and a quiet place to participate in live sessions.

CDT 24641 R Programming (Online) taught by Alan Huebner
In this course, you will learn the foundational skills necessary in R that will enable you to acquire and manipulate data, complete exploratory data analysis (EDA), and create visualizations to communicate your findings.
**Note: this course is delivered fully online. The course design combines required live weekly meetings online with self-scheduled lectures, problems, assignments, and interactive learning materials. To participate, students will need to have a computer with webcam, reliable internet connection, and a quiet place to participate in live sessions. Students who will be on the Main campus are not eligible to enroll in this course.

CDT 24642 Python Programming (Online) taught by John Dillion
In this course, you will learn the foundational skills necessary in Python that will enable you to acquire and manipulate data, model data for the purposes of scientific analysis, and create visualizations to communicate your findings. The course will introduce you to efficient scientific computing using NumPy. You will learn how to apply the pandas library to perform a variety of data manipulation tasks, including selecting, subsetting, combining, grouping, and aggregating data. You will also learn how to generate and customize visualizations with matplotlib. The course will give you the basic ideas and intuition behind modern data analysis methods and their applications, with a strong focus on a course project and weekly assignments.
**Note: this course is delivered fully online. The course design combines required live weekly meetings online with self-scheduled lectures, problems, assignments, and interactive learning materials. To participate, students will need to have a computer with webcam, reliable internet connection, and a quiet place to participate in live sessions. Students who will be on the Main campus are not eligible to enroll in this course.

CDT 34643 Probability & Statistics for Data Science (Online) taught by Alan Huebner
In this course, you will learn the fundamentals of probability theory and statistical inference used in data science. These foundational principles and techniques will allow you to transform data science problems into mathematical terms and validate them as statistical statements.
Note: this course is delivered fully online. The course design combines required live weekly meetings online with self-scheduled lectures, problems, assignments, and interactive learning materials. To participate, students will need to have a computer with webcam, reliable internet connection, and a quiet place to participate in live sessions.

Students with other prerequisite courses or equivalent background preparation may enroll by permission of the instructor or permission of the Director of Undergraduate Studies, Professor Alan Huebner (Alan.Huebner.10@nd.edu).

CDT 44640 Data Science taught by TBD
Data science can be viewed as the art and craft of extracting knowledge from large bodies of structured and unstructured data using methods from many disciplines, including (but not limited to) machine learning, databases, probability and statistics, information theory, and data visualization. This course will focus on the process of data science -- from data acquisition to analytics methods to deployment, and will walk the students through both the technical and use-case aspects in the process. It will place a larger emphasis on the machine learning component, with relevant inclusions and references from other disciplines. The course will give students an opportunity to implement and experiment with some of the concepts as part of a class project, in addition to the hands-on assignments using the Python programming language. Additionally, the course touches upon some of the advances in related topics such as big data and discuss the role of data mining in contemporary society. The course has been designed and developed by Nitesh Chawla, the Frank Freimann Professor of Computer Science and Engineering and Director of iCeNSA at the University of Notre Dame.

Note: this course is delivered fully online. The course design combines required live weekly meetings online with self-scheduled lectures, problems, assignments, and interactive learning materials. To participate, students will need to have a computer with webcam, reliable internet connection, and a quiet place to participate in live sessions.

Students enrolling in this course should have taken one or more courses or implemented one or more projects involving Python programming and one or more courses in probability or statistics.

Students enrolling in this course should have taken one or more courses or implemented one or more projects involving Python programming and one or more courses in probability or statistics.