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.

Course options with computational/digital focus:

CDT 24641 System & Tech: R (Online) taught by TBD (SUMMER)
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 System & Tech: Python (Online) taught by TBD (SUMMER)
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 Prob & Stats: Data Science (Online) taught by TBD (SUMMER)
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 who will be on the Main campus are not eligible to enroll in this course.

CDT 30200 Privacy and Security formerly Networking and Security taught by Jason Williams (SPRING)
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 40200 Information Security taught by James Smith (FALL)
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 40205 Computer Security taught by Walter Scheirer (SPRING)
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

CDT 40610 Case Study - Computing-Based Entrepreneurship (CSE 40923) taught by Kevin Bowyer or other staff instructors (FALL)
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 or 44640(Summer) taught by Meng Jiang (SUMMER, FALL, & SPRING)
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 who will be on the Main campus are not eligible to enroll in this course.
*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. Instructor permission required

CDT 40650 Entrepreneurship: Building a High-Tech Startup(CSE 40924) taught by Robert McLaughlin (Fall)
This course will cover formulation of the "idea" for the startup, attributes of successful tech startups, understanding the market, structuring the company, building a team and organization, financial indicators, launching, early marketing and growth, and business plan structure.

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

CDT 20515 Data and AI Ethics taught by Emanuele Ratti (SPRING)
In the last decade, the Big Data revolution and developments in Artificial Intelligence (AI) have both created promises and raised several ethical issues. Computational emerging technologies have fostered the achievement of apparent benefits, while at the same they seem to exacerbate social inequalities and threaten even our own existence as a species. In this course, we will discuss those ethical and societal issues related to the development of AI and Big Data that have direct and concrete consequences on the way we perceive ourselves as persons, as members of society, and the way we conceive our place as a species on this planet. These issues will be analyzed in light of major ethical theories, but a special emphasis will be placed on virtue ethics. Recent works in virtue ethics are well positioned to make sense of the importance of our place as human beings on this planet, but at the same time they can account for the indispensable roles that machines play in our environment. The course is divided in three main parts. In the first part, I will introduce the main ethical frameworks, and in particular virtue ethics. In the second part, we will discuss AI. Societal and ethical issues raised by AI include the threats posed to the existence of our species; whether we should trust AI or we should find a way to build artificial agents with moral characteristics; whether AI will do most of our jobs in the future and if this scenario is desirable. In the third part, we will focus on selected issues concerning the Big Data revolution, such as how the autonomy of very complex algorithms can shape our lives in opaque ways and whether transparency is desirable; if the design of algorithms may hide bias leading to social inequalities; how algorithms are changing the way healthcare is provided.Upon successful completion of this course, you will be able to: 1. Define and sketch focal points of the virtue ethics and other relevant ethical theories 2. Identify moral theories in arguments provided in support or in opposition to the use of certain AI-related and Big Data technologies 3. Compare different arguments and highlight strengths and weaknesses.

CDT 20510 Science, Technology, and Society(STV 20556) taught by Anna Geltzer (FALL)
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 (FALL & SPRING)
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.