2024-2025 Binghamton University Academic Guide
Courses
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HSCI 332 - Forensic Health of Victims
Credits: Variable
Forensic health issues as they relate to victims of violent crimes, such as child abuse, intimate partner violence, elder abuse, sexual violence, human trafficking, stalking, workplace violence, hate crimes, and homicide. Content also includes victim needs and rights; the victim role in the criminal justice system; responses to trauma; crisis intervention; order of protection, victim’s resources; victimization of children, women, men, elders and persons with disabilities.
Pre-requisites: None
Format: On-line Asynchronous
Grade Mode: Nursing Standard Letter
Restrictions: Sophomore level standing and above
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HSCI 333 - Forensic Health of Offenders
Credits: Variable
This course provides an overview of forensic health issues as they relate to perpetrators of violent crimes, including intrafamilial violence, sexual violence, stalking, workplace violence, hate crimes and homicide. Content also includes forensic roles, crime classifications, relationship between animal cruelty and human violence, offender needs and rights, and issues related to juvenile and female offenders. Open to all students, sophomore status and above.
Format: Online Asynchronous
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HSCI 334 - Forensic Pediatrics
Credits: Variable
This course explores the intricacies of forensic pediatrics where children and adolescents are victims and/or offenders of violence. Topics include: the effects of violence on youth, interviewing and assessing children/adolescents, evidence, expert witness testimony, compassion fatigue & vicarious victimization, children of incarcerated parents, child abuse, shaken baby syndrome, Munchausen Syndrome by Proxy, sexual assault and exploitation, the juvenile justice system, delinquency, child delinquents, female delinquents, animal cruelty, arson, gangs, bullying, and child death investigation.
Pre-requisite: None
Format: Online Asynchronous
Grade Mode: Nursing Standard Letter
Restriction: Sophomore level status and above
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HSCI 335 - Med-Legal Death Investigation
Credits: Variable
This course provides an overview of forensic and medicolegal issues as they relate to the investigation of an individual’s death. Content includes how deaths are investigated in the United States, postmortem changes, common injury patterns and findings, cause and manner of death, special types of death investigations, and working with families. Open to all students, sophomore status and above. Some sections may be restricted to Decker School Of Nursing Students.
Online Course
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HSCI 336 - Sexual Offending&Victimization
Credits: Variable
This course provides a practical examination of sexual offending and victimization. While it is open to all upper-division students, it is designed for students who may work with these populations during their careers. Topics include: Underlying Framework; Types of Sexual Assault; Sexual Exploitation and Human Trafficking; Victim Populations & the Effects of Sexual Assault on Victims; Evaluation of Sexual Assault Victims; Interventions for Sexual Assault Victims; Perpetrators of Sexual Violence; Offender Populations; Offender Assessment; Treatment and Supervision of Sex Offenders.
Prerequisite: None
Format: Asynchronous online
Grade Mode: Nursing Standard Letter
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HSCI 431 - Correctional Health
Credits: 3
This course provides a comprehensive overview of correctional health for those students who may want to consider this career path. The course includes: an overview of the US corrections and correctional health systems and roles; legal, ethical and cultural issues; physical health concerns; mental health problems; treatment and programming; sex offender management; violence in correctional facilities; elder, female and juvenile inmates; and reentry.
Prerequisite: None
Format: Asynchronous online
Grade Mode: Nursing Standard Letter
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HSCI 531 - Forensic Health Essentials
Credits: 3
HSCI 531 - Forensic Health Essentials This course provides an overview of various forensic disciplines, as well as forensic assessment, the collection and preservation of evidence, criminal aspects of forensics, death investigation, crime analysis, crime prevention, basic civil issues, such as malpractice, child custody, elder law and personal injury, promoting one’s practice, and the differences between collaboration and consultation. This course is online asynchronous.
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HSCI 532 - Forensic Health of Victims
Credits: 3
This course provides an overview of forensic health issues as they relate to victims of violent crimes, such as intrafamilial violence, sexual violence, stalking, workplace violence, homicide, and other issues. Content includes responding to victim responses to trauma; victim’s resources; victimization of children, women, men, elders and persons with disabilities; and expert witness testimony.
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HSCI 533 - Forensic Health of Offenders
Credits: 3
This course provides an overview of forensic health issues as they relate to perpetrators of violent crimes, including intrafamilial violence, sexual violence, stalking, workplace violence, and homicide. Content also includes forensic roles, crime classifications, wrongful convictions, relationship between animal cruelty and human violence, offender needs and rights, juvenile offenders, and correctional health. Students also receive an introduction to criminal profiling.
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HSCI 534 - Forensic Pediatrics
Credits: 3
Courses under this section will be offered based on availability of instructor and request of students. This course explores the intricacies of forensic pediatrics where children and adolescents are victims and/or offenders of violence. Topics include: the effects of violence on youth, interviewing and assessing children/adolescents, evidence, expert witness testimony, compassion fatigue & vicarious victimization, children of incarcerated parents, child abuse, shaken baby syndrome, fictitious disorder imposed on others, sexual assault and exploitation, the juvenile justice system, delinquency, child delinquents, female delinquents, animal cruelty, arson, gangs, bullying, and child death investigation. Graduate students will also choose from Pediatric Sexual Assault Nurse Examiner, School Violence or Sudden Unexpected Infant Death Investigator modules. Fall semesters.
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HSCI 535 - Medicolegal DeathInvestigatn
Credits: 3
This course provides an overview of forensic and medicolegal issues as they relate to the investigation of an individual’s death. Content includes how deaths are investigated in the United States, postmortem changes, common injury patterns and findings, cause and manner of death, special types of death investigations, and working with families. Dr. Lunn is a medical investigator and criminologist in the Denver metro area with extensive experience in the investigation of violent and high profile deaths having been an invited speaker at local, state and national trainings. In service to the profession, Dr. Lunn is the former Vice President of the American Board of Medicolegal Death Investigators, a committee member for the National Association of Medical Examiners, and a committee member for a NIJ scientific working group.
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HSCI 536 - Sexual Offending&Victimization
Credits: 3
This course provides a practical examination of sexual offending and victimization. While it is open to all graduate students, it is designed for students who may work with these populations during their careers. Modules are: Underlying Framework; Types of Sexual Assault; Sexual Exploitation and Human Trafficking; Victim Populations & the Effects of Sexual Assault on Victims; Evaluation of Sexual Assault Victims; Interventions for Sexual Assault Victims; Perpetrators of Sexual Violence; Offender Populations; Offender Assessment; Treatment and Supervision of Sex Offenders; and Prevention of Sexual Violence. Summer session.
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HWS 232 - Fundamentals of Cooking
Credits: Variable
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INFO 505 - Software Project Mgmt
Credits: 3
Object management concepts and methods focusing on software development and other engineering systems. Problem determination and assessment, solution development, and product release. Investigating and analyzing a problem, determining requirements, defining a solution, managing scope, design reviews, maintenance considerations, budget, financial analysis, affordability, cost/benefit, and commercial potential. Change control, version control, libraries, release management, and archives as applicable to software and engineering. Project Integration and implementation, teamwork, communication management, time management, risk management, formal documentation, professional communication skills, formal writing and professional presentations, and ethical considerations. Assignments include a semester long detailed case study and team project including problem determination, determining requirements, formulating a solution, teamwork, research, communication skills, and formal writing.
Prerequisite: INFO 501, INFO 502. Offered once per year.
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INFO 532 - Database Systems
Credits: 3
Students will also gain technical understanding of and hands-on experience with the information technology required for data analytics. The focus of the course is on traditional databases and structured data. It covers association between data elements and data models (including entity-relationship and relational models), relational database design techniques, database query languages. Students will be exposed to query processing, transaction management, and concurrency control.
Prerequisite: (Can be taken concurrently) INFO 501, INFO 502. Offered at least once every year.
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INFO 533 - Web Based Inf Retrieval&Search
Credits: 3
The course covers web-based systems for storing information, indexing methods, and ways in which indices can be searched. Search methods include Boolean, statistical, inference nets, and knowledge-based models. Techniques such as query expansion will be covered, as well as natural language and linguistic methods. Efficient information retrieval can often be performed in a distributed fashion, with a variety of cloud service providers supporting multiple methods. Integration and data fusion will also be covered.
Prerequisite: (Can be taken concurrently) INFO 501, INFO 502. Offered at least once every year.
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INFO 535 - Applied Data Mining
Credits: 3
With advances in modern technology, such as the widespread use of electronic records or the internet, the sheer volume of data is staggering. The challenge is to distill the data into useful knowledge that has relevance for managerial decisions. Data mining techniques provide solutions to this challenge. This course will introduce the main topics and algorithms in data mining and knowledge discovery. Emphasis will be placed on the algorithmic and systems issues, as well as application of mining in real-world problems. Upon successful completion of this course, students will gain knowledge of key data mining concepts and algorithms, and be able to apply different data mining techniques to solve real-world problems.
Prerequisite: (Can be taken concurrently) INFO 501, INFO 502. Offered at least once a year.
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INFO 536 - Applied Machine Learning
Credits: 3
Machine learning is the science of getting computers to make decisions without being explicitly programmed. This course provides a broad introduction to machine learning and its applications. It introduces students to the key insights behind different machine learning techniques and algorithms as well as an understanding of how and why they work. The course also discusses applications of machine learning and practical guidelines in applying machine learning techniques in real-world problems.
Prerequisite: INFO 501 Inf Sys I Python & Data Mining. Co-Requisite: INFO 535 Applied Data Mining. Expected to be offered at least once every two years.
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INFO 541X - Mob. Appl. for Social Networks
Credits: 3
The course covers app development for both the iOS and Android platforms, with an emphasis on the use of mobile devices to access social network resources. Authorization tokens, RESTful APIs, and Web interfaces in general, will be discussed. Social networks and mobile devices present a range of privacy and ethical challenges; lectures will include consideration of the ethical and legal obligations of apps to protect user privacy, security, and anonymity.
Prerequisite: (Can be taken concurrently) INFO 501, INFO 502. Offered at least once a year.
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INFO 544X - Web-Based Programming
Credits: 3
An in-depth understanding of programming for the World Wide Web: detailed coverage of widely used language(s) for web programming, asynchronous programming, principles of web architecture, web protocols, web design patterns, client-side programming, templating, server-side programming, a technical history of the web, web security. Students are expected to have experience with a modern programming language and will be assigned programming projects using current state-of-the-art web technologies.
Prerequisite: (Can be taken concurrently) INFO 501, INFO 502. Offered at least once a year.
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INFO 554X - Data Analytics for Security
Credits: 3
For large distributed systems, vast quantities of data pass through, and there can be a wide range of requests made. Analyzing trends in data access, and the types of data passing through, can expose anomalies that may be caused by a cyber-attack, or a failure or misconfiguration of the system. This course provides a hands-on approach to applying data analytics technology to securing and maintaining large information systems. Potential topics covered in this course include, but are not limited to, network traffic analysis, system log analysis, malware scanning, user behavior monitoring, threat hunting, data exfiltration detection, and incidence responses.
Prerequisite: INFO 501, INFO 502. Expected to be Offered at least once every two years.
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ISE 447 - Modern Complexity Theory
Credits: 3
The scientific study of complex systems has achieved relevant progress in recent decades. This was possible because electronic computers are required to study interactions, which characterize complexity. Using computers as tools, concepts such as emergence, self-organization, criticality, information, adaptation, robustness, antifragility, evolution, and more have been elaborated in a broad range of domains. Combined with methods such as network science, agent-based modelling, and artificial intelligence, our understanding of complex systems is allowing us to solve problems in novel ways. The lectures will span from formal theories to practical applications to philosophical implications. Students will be encouraged to participate and discuss in class concepts and research papers. Coursework will be adaptive, to accommodate students with or without advanced mathematical/programming backgrounds.
Prerequisites: Senior level standing or permission of the instructor. Term offering my vary: offered at least once per year.
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ITAL 182B - Topics in Italian - 2 Cr.
Credits: 2
Topics in Italian. Topics vary by offering. May be repeated for credit if different subject matter.
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ITAL 497 - Independent Study
Credits: Variable
Independent reading and research on selected topic in consultation with major advisor. s.
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JPN 304 - Business Japanese
Credits: 4
The Business Japanese course is designed to prepare students to use professional Japanese in real-life business situations. It aims to equip students with strong language skills for effective communication in Japanese business contexts. It emphasizes cross-cultural communication and etiquette to navigate the Japanese business environment successfully and students will gain insights into Japanese business manners. Additionally, the course focuses on preparing students for careers in various professional settings, ensuring they are ready to excel in the business world, whether in Japan or in international contexts. Prerequisite: JPN 204. Offered regularly.
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JPN 507 - Fourth Year Japanese I
Credits: 1
Restricted to Graduate Students. Permission of Instructor.
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JUST 470 - Research&Rdg in Jewish Am Lit
Credits: 4
Research and Reading in Jewish American Literature is a project course designed to produce original research. Using skills for investigating any literature, students use and cite primary and secondary sources (including databases and archives) and collaborate on a project focused in Jewish American literature. The course promotes heavy use of the library. Taught through the lens of a major topic in Jewish American or Jewish literature in translation, it will also be useful for advanced students in any literary field. Grading will be based on short research exercises throughout the course and a major report exploring findings to conclude the course. Restricted to students with junior or senior standing. Offered in Fall.
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KOR 480J - Special Topics In Korean
Credits: 4
SPECIAL TOPICS IN KOREAN
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LAT 315 - The “Other” in Latin Comedy
Credits: 4
In this advanced Latin reading course, we will explore selections from several Roman comedies of Plautus that highlight disfranchised contributors (slaves, foreigners, women) to the satirical Greco-Roman world of comedy. Format: Translation and discussion daily; occasional student reports, reading of scholarly articles and small group performances in Latin and English. Video of Latin performance. Prerequisite: LAT 203 or approved equivalent. Offered alternate years.
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LAT 325 - “Africans” in History & Epic
Credits: 4
In this advanced Latin reading course, we will examine the Roman presentation of ‘othered’ ethnic groups in and around the Roman province of Africa, especially the Carthaginians, Numidians and ‘Mauretanians’, in the Dido episodes of Vergil’s Aeneid Books 1, 4 and 6, the first book of Livy’s third decade (Book 21) and Sallust’s Jugurthine War. Through translation, extensive class discussion, and scholastic inquiry, instructor and students will expand our language skills and our understanding of historiographical and poetic interpretation, anthropological constructions of foreign enemy cultures, and Roman historical legendizing. Prerequisite: LAT 203 or approved equivalent. Offered alternate years.
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LEAD 280A - Intro to Transform. Leadership
Credits: 2
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LEAD 280B - Intro to Transform. Ldrship II
Credits: 2
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LEAD 351 - Leadership Skills&Development
Credits: 4
Focuses on individual leadership development. Concentrates on leadership as a dyadic or small-group process, e.g., one leader and several followers. Also provides a survey of the major topical areas of leadership. Students learn how to use technology to enhance their leadership potential up front and working at a distance with others. Prerequisite: MGMT 311. Traditionally semesters.
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LEAD 354 - Innovation and Creativity
Credits: 4
This class will learn what organizations do to stimulate creativity in employees and throughout the organization, manage the innovation process, foster external ties for partnerships for innovation, and bring products to market. Students will interact with Chief Innovation Officers and team members of these organizations. Students will also be encountering and practicing creativity skills and tools themselves in the classroom turned Innovation Lab.
Prerequisite: MGMT 311
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LEAD 480D - Leadership Seminar
Credits: 4
This course addresses Leadership through a wide variety of lenses including Leading Through Storytelling, Leading Teams, Leading Through Authenticity, Leading Through Feedback, Leading During Crises, Leading Innovation, Leading the Future of Work, and others. Acceptance into the course requires a 3.5 GPA, submission of an application essay (2 pages), and one faculty recommendation.
Students will experience a highly interactive learning environment in a small (20 student limit) Honors Seminar format including lectures, breakout groups, coaching, book summary reports, ongoing Q&A/discussions, and a capstone independent group project on ‘The Future of Leadership’. Course content is taught by expert guest faculty and group assignments are supported by experienced professional coaches.
The course is delivered using a unique hybrid design including two in-person class sessions (one near the beginning and one near the end of the semester). Other sessions during the first half of the semester are conducted virtually via Zoom. The second half of the semester is devoted to independent group project work (no formal class sessions), supported by periodic group coaching check-ins. SOM Honors Leadership Academy is led by Adjunct Faculty member (LEAD 480C/580C) and Binghamton University alumnus, Ian Ziskin, President, EXec EXcel Group, who has 42 years of experience as an author, business leader, board advisor and member, coach, consultant, chief HR officer, entrepreneur, professor, and speaker.
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LEAD 551 - Leadership Skills&Development
Credits: 4
This course concentrates on leadership as it occurs in one-on-one situations and in small groups, and surveys the major topical areas of leadership. A significant portion of the course focuses on interpersonal influence through language, framing and specific behaviors, as well as leading for innovation. Traditionally semester.
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LEAD 580D - Leadership Seminar
Credits: 4
This course addresses Leadership through a wide variety of lenses including Leading Through Storytelling, Leading Teams, Leading Through Authenticity, Leading Through Feedback, Leading During Crises, Leading Innovation, Leading the Future of Work, and others. Acceptance into the course requires a 3.5 GPA, submission of an application essay (2 pages), and one faculty recommendation.
Students will experience a highly interactive learning environment in a small (20 student limit) Honors Seminar format including lectures, breakout groups, coaching, book summary reports, ongoing Q&A/discussions, and a capstone independent group project on ‘The Future of Leadership’. Course content is taught by expert guest faculty and group assignments are supported by experienced professional coaches.
The course is delivered using a unique hybrid design including two in-person class sessions (one near the beginning and one near the end of the semester). Other sessions during the first half of the semester are conducted virtually via Zoom. The second half of the semester is devoted to independent group project work (no formal class sessions), supported by periodic group coaching check-ins. SOM Honors Leadership Academy is led by Adjunct Faculty member (LEAD 480C/580C) and Binghamton University alumnus, Ian Ziskin, President, EXec EXcel Group, who has 42 years of experience as an author, business leader, board advisor and member, coach, consultant, chief HR officer, entrepreneur, professor, and speaker.
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LEAD 600 - Advanced OB
Credits: 4
Doctoral-level seminar building on the introductory organizational behavior course by surveying in greater depth topics such as person-situation views, individual differences, dyadic and group processes, leadership and motivation, individual and group development, creativity and performance evaluation.
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LEAD 602 - Theory Testing in OB & L
Credits: 4
Doctoral-level seminar designed to integrate theory, empirical research and advanced methodologies for testing leadership theories.
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LEAD 603 - Special Topics in OB & L
Credits: 4
Doctoral-level seminar covering current topics in Leadership.
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LTRC Z592 - Internship in Literacy
Credits: Variable
Supervised field experience in both early childhood and elementary settings which includes opportunities for practice, demonstration, self-evaluation and validation of competencies gained in the literacy program to provide: (1) opportunity for planning, feedback and evaluation for the collaborative and congruent role with teachers, with input from both peers and faculty, and (2) opportunity to develop skills and strategies for the leadership and consulting role with parents, teachers and other school and community personnel. Offered: semester offered varies (as needed). 1 or
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MATH 584 - Euclid/Non-Eucl Geo (MAT/MST)
Credits: 4
Algebraic (analytic) approach to classical geometries (Euclidean, hyperbolic, projective). Prerequisite: consent of instructor. 4 cr, Every other year.
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MDVL 180F - Medieval/Early Modern Studies
Credits: 4
Medieval/Early Modern Studies
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MDVL 380Q - Medieval/Early Modern Studies
Credits: 4
Medieval/Early Modern Studies
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MDVL 382X - Medieval/Early Modern Studies
Credits: 4
Medieval/Early Modern Studies
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MDVL 580G - Topics in Medieval Studies
Credits: 4
Topics in Medieval Studies. Subject varies by offering.
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ME 303 - Eng Computational Methods
Credits: 3
Application of computational methods to solve engineering and scientific problems. Topics covered include numerical methods (curve fitting, solution of linear and nonlinear equations, integration, ordinary and partial differential equations), graphical visualization and statistical analysis using MATLAB. Prerequisites: ME 212 and ME 302. Offered in the Spring semester and the Summer session.
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ME 423 - Intro to Dynamics of Microsys
Credits: 3
The course aims to introduce the students to the principles of MEMS and Microsystem dynamics and their modeling techniques. The course is multi-disciplinary in nature and will tackle several multi-physics problems, which include vibrations, dynamics, fluid mechanics, heat, electronics and electricity, etc. It will emphasize analytical and some numerical modeling techniques. The topics will include topics such as Sensing and Actuation in MEMS (electrostatic, electrothermal, piezoelectric, electromagnetic, etc), Elements of Lumped-Parameter Modeling in MEMS (stiffness, damping, inertia), case studies of accelerometers, gyroscopes, filters, switches, mirrors, and basic principles of stability and nonlinear analysis of microsystems.
Prerequisites: ME 421. Offered in the Fall.
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ME 473 - Micro/Nanomaterials Processing
Credits: 3
This course will explore how micro and nano-scale materials and devices are produced. Covered topics include the 1) fundamentals of micro and nano-materials processing in material science and transport phenomena, 2) micro and nano-fabrication processes for Micro-Electro-Mechanical Systems (MEMS) and Nano-Electro-Mechanical Systems (NEMS), 3) existing and emerging manufacturing processes for industrial scale production of micro- and nano-scale materials, and 4) Metrology and characterization tools for conducting research in micro and nano-materials processing. This course is cross-listed as a graduate-level course. Completion of additional assignments is required for graduate credits.
Prerequisites: ME 302 or approval of instructor Offered once per year.
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ME 531 - Applied Machine Learning fr ME
Credits: 3
This course covers machine learning fundamentals, some popular and advanced machine learning models. Major topics include supervised learning (logistic regression, support vector machine, artificial neural networks, Gaussian process), unsupervised learning (clustering, dimensionality reduction), convolutional neural networks, generative adversarial networks, physics-constrained/informed neural networks, and optimization algorithms (stochastic gradient descent, Bayesian optimization). This course also covers the applications of machine learning models in mechanical engineering. Students should be familiar with Python basic commands and programming.
Prerequisites: ME303 or equivalent. Offered in the Fall.
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ME 573X - Micro/Nanomaterials Processing
Credits: 3
This course will explore how micro and nano-scale materials and devices are produced. Covered topics include the 1) fundamentals of micro and nano-materials processing in material science and transport phenomena, 2) micro and nano-fabrication processes for Micro-Electro-Mechanical Systems (MEMS) and Nano-Electro-Mechanical Systems (NEMS), 3) existing and emerging manufacturing processes for industrial scale production of micro- and nano-scale materials, and 4) Metrology and characterization tools for conducting research in micro and nano-materials processing. This course is cross-listed as a graduate-level course. Completion of additional assignments is required for graduate credits.
Prerequisites: ME 302 or approval of instructor. Term offered varies.
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MGMT 111 - Intro Decision Making in MGMT
Credits: 4
This course serves as a general introduction to decision making in Management and and the programs and areas of study in thye School of Management. This course is a required first semester course for all School of Management freshmen. Traditionally offered in Fall Semester.
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MGMT 211 - Transfer Career Seminar
Credits: 0
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MGMT 251 - SCHOLARS SOPHOMORE EXPERIENCE
Credits: 1
In this class students will work in teams on a business case. The case competition will last approximately three weeks and will culminate in a final round of presentations of the top three teams at the PwC offices in New York City.
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MGMT 261 - Technical Case Competition
Credits: 1
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MGMT 350 - Scholars Community Project
Credits: 2
PwC Scholars each year undertake a major project for the Binghamton community. Past projects have included building several community playgrounds, restoring an outdoor play area at the Discovery Center and building a bookmobile for a flooded elementary school. Prerequisites: PwC scholars student and Junior standing. Offered in Fall and Spring Semesters.
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MGMT 360 - Analytics Project
Credits: 2
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MGMT 411 - Global Strategic Mgmt
Credits: 4
Capstone course providing conceptual tools for integrating functional skills acquired in previous courses. Emphasis is on strategic and socially responsible operation of the total enterprise in a global environment. Combines lectures with in-depth case analyses and simulations or research studies of actual industries in real time. Students research industries and companies, make oral presentations and write research papers. Prerequisites: CQS 311, OPM 311, MIS 311, Fin 311, MGMT 311, MKTG 311, and senior standing. Traditionally and Spring Semesters
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MGMT 480P - Intro. to Product Management
Credits: 4
Introduction to Product Management is a new, project-based course designed to introduce students to the field of product management, and build the foundational skills to pursue it as a career. The course is meant for students interested in creating the next generation of innovative digital products. Great products often come from people with diverse backgrounds; as such, students from a wide array of academic backgrounds are welcome in the course. Furthermore, no previous product management experience or knowledge is necessary.
For this course, expect a healthy mix of hands-on projects, building products & prototypes from scratch, customer discovery, ideation, introduction to industry tools, discussions with practitioners and mentors, and other forms of experiential learning that mirror the day-to-day activities of product managers at top tech companies.
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MGMT 480R - Real Estate Analysis
Credits: 4
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MGMT 503 - Statistical Analysis For Mgmt.
Credits: 3
Statistical methods and their applications in managerial decision making. Topics include descriptive statistics and basic inferential models.
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MGMT 504 - Programming for Bus Analytics
Credits: 3
Course will cover general Python structure and syntax. To include variables, if statements, and operators, intro to loops and list comprehension, working with functions, data structures (lists, arrays, dictionaries, strings, tuples, etc.) and Debugging.
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MGMT 580P - Intro. to Product Management
Credits: 4
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MGMT 580R - Real Estate Analysis
Credits: 4
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MGMT 581A - Business, Human Rights & Atroc
Credits: 4
SPECIAL TOPICS
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MGMT 581B - Special Topics
Credits: 4
SPECIAL TOPICS
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MGMT 586A - Statistical Analysis For Mgmt
Credits: 2
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MGMT 587F - FIN & ECONOMICS OF HEALTHCARE
Credits: 2
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MGMT 587G - MIS OF HEALTHCARE
Credits: 2
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MGMT 589F - Advanced Tech & Virtual Teams
Credits: 4
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MGMT 589G - Strategic MGMT for Profession
Credits: 4
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MGMT 602 - SEMINAR ON PEDAGOGY IN MGMT
Credits: 2
Covers topics on the application of modern pedagogical theory to college-level teaching in management. Topics differ from semester to semester, but may include implications of personality type, cognitive development and learning theories for teaching management; practica on proper teaching techniques such as lecturing, leading discussions, using team and group learning, and teaching with technology; testing and assessment of learning; evaluation of teaching; and professional development. Traditionally offered in Spring Semesters.
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MGMT 680C - Doctorial Sem in Strat Mgmt
Credits: 4
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MGMT 680D - Multilevel Measure. & Analysis
Credits: 4
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MGMT 687 - Multivariate Statistics
Credits: 4
Multivariate Statistics
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MIS 311 - Information Syst & Application
Credits: 3
The effective deployment of information technologies and computer-based information systems has strategically enabled enterprises to achieve and maintain competitive advantage. In the context of management imperatives and the rapidly changing business environment, this course examines the role of various types of information technologies and systems in organizations, technical foundations of information systems and the development of information systems. Discussion labs provide the opportunity to become proficient in the use of productivity software, such as relational database management systems. Part of the S-Core. Prerequisites: statistics and sophomore standing. Corequisites: CQS 311. and spring semesters.
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MIS 323 - Systems Analy. & Specification
Credits: 4
Provides an understanding of the systems development and modification process. Enables students to choose and adapt system development methodologies. Teaches the principles of high-quality information requirements determination and specification in approaching a project, through effective communication with users and all other stakeholders in systems development and maintenance and appropriate documentation standards. Includes consideration of user interface design issues that are critical for the development of Web-based applications. Prerequisite: MIS 311. and spring semesters
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MIS 480A - Strat Info Systems Comm Sem
Credits: 4
In today’s dynamic business environment, effective communication is essential for the success of any organization. As a crucial component of the workplace, strategic communication plays a pivotal role in bridging the gap between technology and the human element. This advanced course delves into the intricacies of communication, the tool landscape, knowing your audience, timeliness of effective messaging, securely integrating AI into these processes, and equipping you with the knowledge and skills to navigate the ever-evolving digital landscape. Prerequisite MIS 311
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MIS 480D - Practical Data Wrangling
Credits: 4
Particular topics within broad area of MIS. Topics determined in advance. May be repeated for credit. Prerequisites: MIS 311, junior standing. This course equips business students with the skills to clean, organize, and transform raw data for analysis. It covers both theoretical and practical aspects of data wrangling, using tools like Excel and Python to handle various data types including
numerical, textual, and unstructured data. Students will learn through hands-on experience, preparing them for data analysis roles in the industry. Topics include challenges of data wrangling, advanced operations in Excel, Python programming, and exploratory data analysis. Prerequisites include basic knowledge of Python and MIS 311
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MIS 480H - Web Mining/Soc Netwk Analysis
Credits: 4
This course focuses on modeling methods and IT tools to automatically collect and analyze large volumes of data from web pages and social media sites for descriptive and predictive analysis. This course provides an overview of measures, models, and analysis methods used to study social networks to further business interests within organizations using internal and external social media data sources. Students will also learn programming languages for data collection and analysis. Prerequisites: MIS 311 and CQS 311.
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MIS 480J - Intro to Machine Learning
Credits: 4
Machine learning is the field dedicated to enabling computers to learn from data and execute tasks without explicit programming instructions. Its widespread adoption is so ingrained in modern life that we often utilize it unknowingly. This course offers an introduction to machine learning methodologies, encompassing classic supervised and unsupervised algorithms, all geared towards harnessing data for predictive analysis. Throughout this course you will acquire proficiency in utilizing no-code/low-code environments, such as KNIME, for constructing, training, and deploying machine learning workflows to tackle real-world predictive challenges. It is an excellent choice for both beginners and intermediate learners interested in comprehending machine learning concepts and data engineering. By the course’s conclusion, you should have a firm grasp of machine learning fundamentals without the need for coding or extensive mathematical calculations. Although no prior knowledge of machine learning or programming is required, students should possess a basic understanding of calculus, probability theory, and linear algebra.
Prerequisites MIS 311, CQS 311
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MIS 480K - Blockchain Tech & Applications
Credits: 4
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MIS 480N - Emerging Issues Cyber Security
Credits: 4
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MIS 523 - Info.Sys.Analysis&Specificatn.
Credits: 4
This course provides an understanding of the systems development and modification process. It enables students to choose and adapt system development methodologies. In approaching a project, this course teaches students the principles of high-quality information requirements determination and specification through effective communication with users and all other stakeholders in systems development and maintenance and appropriate documentation standards. Participatory approaches like JAD, SSM, ETHICS or prototyping are emphasized. Prerequisite: MGMT 500. SOM grad student only. Offered in Fall.
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MIS 550 - IT Security and Forensics
Credits: 4
The first part of this course covers description of different security technologies including firewalls, intrusion detection and cryptography and identification of potential threats such as malicious software, social engineering, spoofing, and phishing. Students will also learn about managerial aspects including information security policies, security management models and practices, and risk management. The second part of the course covers technical and legal aspects of conducting computer forensic analysis and investigation. Topics include requirements of processing crime scenes, investigation of digital evidence (computers, laptops, etc.), network forensics, e-mail investigation, report writing, and expert testimony in high-tech investigations.
Prerequisite: MGMT 500.
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MIS 580A - Strat Info Systems Comm Sem
Credits: 4
In today’s dynamic business environment, effective communication is essential for the success of any organization. As a crucial component of the workplace, strategic communication plays a pivotal role in bridging the gap between technology and the human element. This advanced course delves into the intricacies of communication, the tool landscape, knowing your audience, timeliness of effective messaging, securely integrating AI into these processes, and equipping you with the knowledge and skills to navigate the ever-evolving digital landscape.
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MIS 580D - Practical Data Wrangling
Credits: 4
This course equips business students with the skills to clean, organize, and
transform raw data for analysis. It covers both theoretical and practical aspects of data
wrangling, using tools like Excel and Python to handle various data types including
numerical, textual, and unstructured data. Students will learn through hands-on
experience, preparing them for data analysis roles in the industry. Topics include
challenges of data wrangling, advanced operations in Excel, Python programming, and
exploratory data analysis. Prerequisites include basic knowledge of Python.
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MIS 580H - Web Mining/Soc Netwk Analysis
Credits: 4
This course focuses on modeling methods and IT tools to automatically collect and analyze large volumes of data from web pages and social media sites for descriptive and predictive analysis. This course provides an overview of measures, models, and analysis methods used to study social networks to further business interests within organizations using internal and external social media data sources. Students will also learn programming languages for data collection and analysis. Recommended prerequisites: MGMT 504.
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MIS 580J - Intro to Machine Learning
Credits: 4
Machine learning is the field dedicated to enabling computers to learn from data and execute tasks without explicit programming instructions. Its widespread adoption is so ingrained in modern life that we often utilize it unknowingly. This course offers an introduction to machine learning methodologies, encompassing classic supervised and unsupervised algorithms, all geared towards harnessing data for predictive analysis. Throughout this course you will acquire proficiency in utilizing no-code/low-code environments, such as KNIME, for constructing, training, and deploying machine learning workflows to tackle real-world predictive challenges. It is an excellent choice for both beginners and intermediate learners interested in comprehending machine learning concepts and data engineering. By the course’s conclusion, you should have a firm grasp of machine learning fundamentals without the need for coding or extensive mathematical calculations. Although no prior knowledge of machine learning or programming is required, students should possess a basic understanding of calculus, probability theory, and linear algebra.
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MIS 580K - Blockchain Tech & Applications
Credits: 4
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MIS 580N - Emerging Issues Cyber Security
Credits: 4
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MIS 581C - Special Topics: Web Applic Dev
Credits: 4
This course introduces students to the fundamental concepts and implementation of e-business. The two major objectives of the course are: 1) To learn web design details with HTML and major web design tools. The variety of resources and web fundamentals are introduced with in-class exercises and assignments. 2) To learn a variety of e-business concepts such as online retailing, online consumer behavior, online customer service, online customer relationship management, business to business e-commerce and collaborative commerce. Students also learn about web design, technologies and strategies required to implement these e-business concepts. Pre-Requisite: MGMT 500.
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MKTG 350 - Dist.Channels & Mktg Relations
Credits: 4
Studies how firms can create and capture value through inter-firm relationships, strategic alliances, and customer relationships.
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MKTG 460 - Strategic Product & Brand MGMT
Credits: 4
Focuses on understanding: a) existing product portfolio issues such as cannibalization, ecosystems, standards, and synergy b) new product topics such as idea generation, concept testing, test marketing and introduction, and c) brand management challenges involving extension, dilution, and valuation. 4cr. Traditionally offerd in the fall semester.
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MKTG 480C - Special Topics:Brand Mgmt
Credits: 4
Particular topics within broad area of marketing topics determined in advance. May be repeated for credit. Prerequisite: consent of instructor.
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MKTG 480M - Behavioral Decision Making
Credits: 4
This is an experiential learning course that will involve working with a firm to help them developing a marketing strategy. The course will involve interacting with the client firm executives, performing secondary and primary research, developing a strategy, and presenting it to the client firm
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MKTG 480Q - Mach Learning & AI MKTG Strat
Credits: 4
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MKTG 480R - Data Mining Techniques in MKTG
Credits: 4
This class covers a variety of analytical tools used in Data Mining, such as visualization, prediction, clustering, and text mining. Students will learn to apply these tools to solve marketing problems in a variety of contexts. Prerequisite MKTG 311.
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MKTG 580Q - Mach Learning & AI MKTG Strat
Credits: 4
This course is designed for students who wish to learn more about emerging practices/strategies in machine learning and artificial intelligence. In addition, students with a secondary interest in the areas of multivariate data analysis (broadly speaking) will also find the content to be beneficial. This course is designed to provide systematic and integrative managerial approaches for developing and implementing successful strategies in ML and AI. It brings together the sharpest concepts and methods for the practicing (or soon to be) manager. By using a variety of real-life examples and in-depth company analyses, the course focuses on the optimal application of tools and techniques across several business settings.
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MKTG 580R - Data Mining Techniques in MKTG
Credits: 4
Data mining stands at the intersection of the fields of statistics and machine learning and covers a wide range of techniques to detect actionable patterns in data and aid decision making. In this course, we will cover some of the methodologies used and learn how to apply data mining principles to the dissection of complex data sets and to drive managerially meaningful decisions.
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