SOCIOLOGICAL THEORY
This course emphasizes the perspectives of foundational thinkers on the evolution and dynamics of social life. Readings address key sociological questions; including the configuration of communities, social control, institutions, exchange, interaction, and culture.
- Department: Sociology
- M 9:10 a.m.-11 a.m.
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Instructor:
Ryan A Hagen
Info - 4 points
PRACTICUM IN DATA ANALYSIS
PRACTICUM IN LARGE-SCALE DATA
This practicum course is meant to offer valuable training to students. Specifically, this practicum will mimicthe typical conditions that students would face in an internship in a large data-intense institution. Thepracticum will focus on four core elements involved in most internships: (1) Developing the intuition andskills to properly scope ambiguous project ideas; (2) practicing organizing and accessing a variety oflarge-scale data sources and formats; (3) conducting basic and advanced analysis of big data; and (4)communicating and “productizing” results and findings from the earlier steps, in things like dashboards,reports, interactive graphics, or apps. The practicum will also give students time to reflect on their work, andhow it would best translate into corporate, non-profit, start-up and other contexts.
- Department: Quantitative Methods/Social Sciences
- W 8:10 p.m.-10 p.m.
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Instructor:
Aracelis Z Torres
Info - 2 points
PRACTICUM IN DATA ANALYSIS II
- Department: Quantitative Methods/Social Sciences
- W 8:10 p.m.-10 p.m.
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Instructor:
Aracelis Z Torres
Info - 2 points
DATA MINING FOR SOCIAL SCIENCE
The class is roughly divided into three parts: 1) programming best practices and exploratory data analysis (EDA); 2) supervised learning including regression and classification methods and 3) unsupervised learning and clustering methods. In the first part of the course we will focus writing R programs in the context of simulations, data wrangling, and EDA. Supervised learning deals with prediction problems where the outcome variable is known such as predicting a price of a house in a certain neighborhood or an outcome of a congressional race. The section on unsupervised learning is focused on problems where the outcome variable is not known and the goal of the analysis is to find hidden structure in data such as different market segments from buying patterns or human population structure from genetics data.
- Department: Quantitative Methods/Social Sciences
- T 8:10 p.m.-10 p.m.
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Instructor:
Benjamin K Goodrich
Info - 4 points
SUSTAINABLE FASHION AND STARTUP STRATEGY
SUST FASHION & STARTUP ST
- Department: Auditing
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Instructor:
Ammar Belal
Info - 0 points
SUSTAINABLE FASHION AND STARTUP STRATEGY
SUST FASHION & STARTUP ST
Fashion’s consistent ranking among the top 3 global polluters has become a decades old fact struggling to gain a proportionate response among the brand startup and sourcing community. With industry revenues set to exceed $1 trillion, there is an opportunity to critically address existing revenue models predicated on traditional metrics, such as constant growth, and singular bottom lines. The course attempts to create a nexus between the fashion entrepreneur and systems thinker to explore strategic solutions that address sustainability though an environmental, social and economic lens. The aim is to foster a mindful, yet critical discourse on fashion industry initiatives, past and present, and to practice various tools that help transition existing organizations and incubate new startups towards sustainable outcomes.
- Department: Sustainability Management
- T 6:10 p.m.-8 p.m.
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Instructor:
Ammar Belal
Info - 3 points
STATISTICS, DATA ANALYSIS, AND CODING FO
STATS, DATA, ANLYS&CODING
Students in the Master of Science in Sustainability Science will encounter a range of scientific problems throughout their Science-specific courses that require a strong foundational level of mathematical and statistical knowledge. In addition, course-work will involve computer coding to read, analyze, and visualize data sets. This course provides an overview of essential mathematical concepts, an introduction to new concepts in statistics and data analysis, and provides computer coding skills that will prepare students for coursework in the Master of Science in Sustainability Science program as well as to succeed in a career having a sustainability science component. In addition to an overview of essential mathematical concepts, the skills gained in this course include statistics, and coding applied to data analysis in the Sustainability Sciences. Many of these skills are broadly applicable to science-related professions, and will be useful to those having careers involving interaction with scientists, managing projects utilizing scientific analysis, and developing science-based policy. Students enrolled in this course will learn through lectures, class discussion, and hands-on exercises that address the following topics: Review of mathematical concepts in calculus, trigonometry, and linear algebra; Mathematical concepts related to working on a spherical coordinate system (such as that for the Earth); Probability and statistics, including use of probability density functions to calculate expectations, hypothesis testing, and the concept of experimental uncertainty; Concepts in data analysis, including linear least squares, time-series analysis, parameter uncertainties, and analysis of fit; Computer coding skills, including precision of variables, arrays and data structures, input/output, flow control, and subroutines, and coding tools to produce basic X-Y plots as well as images of data fields on a global map.
- Department: Sustainability Technology
- M 6:10 p.m.-8 p.m.
- 3 points
PROSEMINAR I
The Proseminar fulfills two separate goals within the Free-Standing Masters Program in Sociology. The first is to provide exposure, training, and support specific to the needs of Masters students preparing to move on to further graduate training or the job market. The second goal is to provide a forum for scholars and others working in qualitative reserach, public sociology, and the urban environment.
- Department: Sociology
- W 10:10 a.m.-noon
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Instructor:
Denise Milstein
CULPA: 9
h-index: 5
Info
- 1 points
FIELD WORK I
This two-semester sequence supports students through the process of finding a fieldwork site, beginning the field work required to plan for and develop a Masters thesis, and the completion of their Masters thesis.
- Department: Sociology
- T 9 a.m.-10 a.m.
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Instructor:
Denise Milstein
CULPA: 9
h-index: 5
Info
- 1 points
TOPICS IN WORLD CINEMA
China
- Department: Film
- M 6:10 p.m.-10 p.m.
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Instructor:
Richard A Pena
CULPA: 16
Info
- 3 points
VIDEO INTENSV OF ORAL HISTORY
ORAL HIST DOC & VISUAL STORY
- Department: Oral History
- W 3:10 p.m.-6 p.m.
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Instructor:
Oscar Frasser
Info - 4 points
THESIS SEMINAR I
This seminar gives you an opportunity to do original sociological research with the support of a faculty member, a teaching assistant, and your fellow classmates.
- Department: Sociology
- T 10:10 a.m.-noon
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Instructor:
Denise Milstein
CULPA: 9
h-index: 5
Info
- 3 points
NATURAL LANG PROCESSING SOCIAL SCIENCES
NATURAL LANG PROC SOC SCI
Social scientists need to engage with natural language processing (NLP) approaches that are found in computer science, engineering, AI, tech and in industry. This course will provide an overview of natural language processing as it is applied in a number of domains. The goal is to gain familiarity with a number of critical topics and techniques that use text as data, and then to see how those NLP techniques can be used to produce social science research and insights. This course will be hands-on, with several large-scale exercises. The course will start with an introduction to Python and associated key NLP packages and github. The course will then cover topics like language modeling; part of speech tagging; parsing; information extraction; tokenizing; topic modeling; machine translation; sentiment analysis; summarization; supervised machine learning; and hidden Markov models. Prerequisites are basic probability and statistics, basic linear algebra and calculus. The course will use Python, and so if students have programmed in at least one software language, that will make it easier to keep up with the course.
- Department: Quantitative Methods/Social Sciences
- T 6:10 p.m.-8 p.m.
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Instructor:
Patrick Houlihan
Info - 4 points
NATURAL LANG PROCESSING SOCIAL SCIENCES
NATURAL LANG PROC SOC SCI
Social scientists need to engage with natural language processing (NLP) approaches that are found in computer science, engineering, AI, tech and in industry. This course will provide an overview of natural language processing as it is applied in a number of domains. The goal is to gain familiarity with a number of critical topics and techniques that use text as data, and then to see how those NLP techniques can be used to produce social science research and insights. This course will be hands-on, with several large-scale exercises. The course will start with an introduction to Python and associated key NLP packages and github. The course will then cover topics like language modeling; part of speech tagging; parsing; information extraction; tokenizing; topic modeling; machine translation; sentiment analysis; summarization; supervised machine learning; and hidden Markov models. Prerequisites are basic probability and statistics, basic linear algebra and calculus. The course will use Python, and so if students have programmed in at least one software language, that will make it easier to keep up with the course.
- Department: Quantitative Methods/Social Sciences
- T 6:10 p.m.-8 p.m.
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Instructor:
Patrick Houlihan
Info - 4 points
THE COMPELLING COMMUNICATOR
- Department: Strategic Communication
- T 10:10 a.m.-noon
- T 2:10 p.m.-4 p.m.
- M 6:10 p.m.-8 p.m.
- None None-None
-
Instructor:
Kevin Visconti
Info - 3 points
GIS & SPATIAL ANALYSIS-SOC SCI
Prerequisites: Undergraduate Statistics This course introduces students to basic spatial analytic skills. It covers introductory concepts and tools in Geographic Information Systems (GIS) and database management. As well, the course introduces students to the process of developing and writing an original spatial research project. Topics to be covered include: social theories involving space, place and reflexive relationships; social demography concepts and databases; visualizing social data using geographic information systems; exploratory spatial data analysis of social data and spatially weighted regression models, spatial regression models of social data, and space-time models. Use of open-source software (primarily the R software package) will be taught as well.
- Department: Quantitative Methods/Social Sciences
- R 10:10 a.m.-noon
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Instructor:
Michael Parrott
Info - 4 points
GIS & SPATIAL ANALYSIS-SOC SCI
Prerequisites: Undergraduate Statistics This course introduces students to basic spatial analytic skills. It covers introductory concepts and tools in Geographic Information Systems (GIS) and database management. As well, the course introduces students to the process of developing and writing an original spatial research project. Topics to be covered include: social theories involving space, place and reflexive relationships; social demography concepts and databases; visualizing social data using geographic information systems; exploratory spatial data analysis of social data and spatially weighted regression models, spatial regression models of social data, and space-time models. Use of open-source software (primarily the R software package) will be taught as well.
- Department: Quantitative Methods/Social Sciences
- R 10:10 a.m.-noon
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Instructor:
Michael Parrott
Info - 4 points
MODERN DATA STRUCTURES
This course is intended to provide a detailed tour on how to access, clean, “munge” and organize data, both big and small. (It should also give students a flavor of what would be expected of them in a typical data science interview.) Each week will have simple, moderate and complex examples in class, with code to follow. Students will then practice additional exercises at home. The end point of each project would be to get the data organized and cleaned enough so that it is in a data-frame, ready for subsequent analysis and graphing. Therefore, no analysis or visualization (beyond just basic tables and plots to make sure everything was correctly organized) will be taught; and this will free up substantial time for the “nitty-gritty” of all of this data wrangling.
- Department: Quantitative Methods/Social Sciences
- M 8:10 p.m.-10 p.m.
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Instructor:
Thomas Brambor
h-index: 9 Info - 4 points
CELLULAR/MOLECULAR IMMUNOLOGY
Prerequisites: two semesters of a rigorous, molecularly-oriented introductory biology course (such as UNC2005 and UN2006), or the instructor's permission. This course will cover the basic concepts underlying the mechanisms of innate and adaptive immunity, as well as key experimental methods currently used in the field. To keep it real, the course will include clinical correlates in such areas as infectious diseases, autoimmune diseases, cancer, and transplantation. Taking this course won't turn you into an immunologist, but it may make you want to become one, as was the case for several students last year. After taking the course, you should be able to read the literature intelligently in this rapidly advancing field.
- Department: Biological Sciences
- MW 2:40 p.m.-3:55 p.m.
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Instructor:
Christian W Schindler
CULPA: 3 Info - 3 points
MACHINE LEARNING SOC SCI
Prerequisites: basic probability and statistics, basic linear algebra, and calculus This course will provide a comprehensive overview of machine learning as it is applied in a number of domains. Comparisons and contrasts will be drawn between this machine learning approach and more traditional regression-based approaches used in the social sciences. Emphasis will also be placed on opportunities to synthesize these two approaches. The course will start with an introduction to Python, the scikit-learn package and GitHub. After that, there will be some discussion of data exploration, visualization in matplotlib, preprocessing, feature engineering, variable imputation, and feature selection. Supervised learning methods will be considered, including OLS models, linear models for classification, support vector machines, decision trees and random forests, and gradient boosting. Calibration, model evaluation and strategies for dealing with imbalanced datasets, n on-negative matrix factorization, and outlier detection will be considered next. This will be followed by unsupervised techniques: PCA, discriminant analysis, manifold learning, clustering, mixture models, cluster evaluation. Lastly, we will consider neural networks, convolutional neural networks for image classification and recurrent neural networks. This course will primarily us Python. Previous programming experience will be helpful but not requisite. Prerequisites: basic probability and statistics, basic linear algebra, and calculus.
- Department: Quantitative Methods/Social Sciences
- M 6:10 p.m.-8 p.m.
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Instructor:
Michael Parrott
Info - 4 points
MACHINE LEARNING SOC SCI
Prerequisites: basic probability and statistics, basic linear algebra, and calculus This course will provide a comprehensive overview of machine learning as it is applied in a number of domains. Comparisons and contrasts will be drawn between this machine learning approach and more traditional regression-based approaches used in the social sciences. Emphasis will also be placed on opportunities to synthesize these two approaches. The course will start with an introduction to Python, the scikit-learn package and GitHub. After that, there will be some discussion of data exploration, visualization in matplotlib, preprocessing, feature engineering, variable imputation, and feature selection. Supervised learning methods will be considered, including OLS models, linear models for classification, support vector machines, decision trees and random forests, and gradient boosting. Calibration, model evaluation and strategies for dealing with imbalanced datasets, n on-negative matrix factorization, and outlier detection will be considered next. This will be followed by unsupervised techniques: PCA, discriminant analysis, manifold learning, clustering, mixture models, cluster evaluation. Lastly, we will consider neural networks, convolutional neural networks for image classification and recurrent neural networks. This course will primarily us Python. Previous programming experience will be helpful but not requisite. Prerequisites: basic probability and statistics, basic linear algebra, and calculus.
- Department: Quantitative Methods/Social Sciences
- M 6:10 p.m.-8 p.m.
-
Instructor:
Michael Parrott
Info - 4 points
DIGITAL MEDIA & ANALYTICS
- Department: Strategic Communication
- W 6:10 p.m.-8 p.m.
- W 2:10 p.m.-4 p.m.
-
Instructor:
Ethan Pew
h-index: 0 Info - 3 points
FUNDAMENTLS OF OMBUDS PRACTICE
FUNDAMENTALS OF OMBUDS PRACTIC
- Department: Negotiation & Conflict Resolution
- F 6:10 p.m.-9 p.m.
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Instructor:
John Zinsser
Info - 3 points
APPLIED ANALYTICS IN ORGANIZATIONAL CONT
APP AN IN ORG CONTEXT
- Department: Applied Analytics
- M 6:10 p.m.-8 p.m.
- W 8:10 p.m.-10 p.m.
- W 6:10 p.m.-8 p.m.
- R 6:10 p.m.-8 p.m.
- R 8:10 a.m.-10 a.m.
- S 12:10 p.m.-2 p.m.
- W 6:10 p.m.-8 p.m.
-
Instructor:
Wajahat Gilani
Info -
Instructor:
Arunava Bhattacharyya
Info -
Instructor:
Lori Cenci
Info -
Instructor:
Cory E Labanow
Info -
Instructor:
Anjana Bhattacharyya
Info - 3 points
ESTIMATING PROJECT COSTS
- Department: Construction Administration
- R 6:10 p.m.-8 p.m.
-
Instructor:
Ian M Taylor
Info - 3 points
Managerial Statistics
- Department: Decision, Risk and Operations
-
Instructor:
Assaf Zeevi
h-index: 40 Info - 3 points
Managerial Statistics
- Department: Decision, Risk and Operations
-
Instructor:
Assaf Zeevi
h-index: 40 Info - 3 points
VALUE-BASED ENTERPRISE RISK MGMT
VALUE-BASED ERM (ONLINE)
- Department: Enterprise Risk Management
- M 8:10 p.m.-10 p.m.
-
Instructor:
Rajeev Dave
Info - 3 points
ELEMENTS OF DRAMATIC NARRATIVE
A lecture and discussion course on the basics of feature-length screenwriting. Using written texts and films screened for class, the course explores the nature of storytelling in the feature-length film and the ways in which it is an extension and an evolution of other dramatic and narrative forms. A basic part of Film’s first year program, the course guides students in developing the plot, characters, conflict and theme of a feature-length story that they will write, as a treatment, by the end of the semester.
- Department: Film
- M 9 a.m.-noon
-
Instructor:
Andrew S Bienen
Info - 3 points
INTRODUCTION TO HUMAN CAPITAL MANAGEMENT
INTRO TO HUMAN CAPITAL MGMT
- Department: Human Capital Management
- T 8:10 p.m.-10 p.m.
- M 8:30 p.m.-10 p.m.
-
Instructor:
Aaron S Wallen
CULPA: 1 h-index: 5 Info -
Instructor:
Jill Larsen
Info - 3 points
CAMPUS PRACTICUM
CAMPUS PRACTICUM I
- Department: Information & Knowledge Strat
- WRFS 8:30 a.m.-6:30 p.m.
- 1 points
CAMPUS PRACTICUM
CAMPUS PRACTICUM III
- Department: Information & Knowledge Strat
- RFS 8:30 a.m.-6:30 p.m.
- 1 points
PRODUCT, PRICING & DISTRIBUTION
PRODUCT, PRICING & DISTRB
PRODUCT, PRICING & DISTRIBUTION
- Department: Insurance Management
-
Instructor:
Louis Weltmann
Info - 3 points
SELF & OTHER IN CLIN ENCOUNTER
- Department: Narrative Medicine
- W 2:10 p.m.-5 p.m.
-
Instructor:
Michael E Davidovits
Info - 4 points
THE WEALTH MANAGEMENT LANDSCAPE
-
This course will provide an overview of the wealth management profession,
including various business models and the role of the advisor within each. Guest
speakers from across the wealth management profession will discuss the various
business models, key trends, including the intersection of technology and wealth
management and the unique nature of each client planner relationship. This course
will also highlight additional services that advisors are offering clients in order to
provide a full suite of solutions. In addition, students will discuss the role and
function of family offices, the scope of services they offer and best practices to
managing a family office.
- Department: Wealth Management
-
Instructor:
William Woodson
Info - 3 points
FICTION WORKSHOP
- Department: Writing
- R 10 a.m.-1 p.m.
- W 2 p.m.-5 p.m.
- F 10 a.m.-1 p.m.
- R 2 p.m.-5 p.m.
-
Instructor:
Diksha Basu
Wikipedia Info -
Instructor:
James Canon
Wikipedia Info -
Instructor:
Anelise I Chen
Info -
Instructor:
Nicholas Christopher
Wikipedia Info -
Instructor:
Joshua Furst
Wikipedia Info -
Instructor:
Rivka R Galchen
CULPA: 6
Info
-
Instructor:
Heidi S Julavits
CULPA: 1 Wikipedia Info -
Instructor:
Victor D Lavalle
CULPA: 2 Wikipedia Info -
Instructor:
Samuel Lipsyte
CULPA: 5
Info
-
Instructor:
Benjamin Marcus
Info - 6 points
UNDERSTAND CONFLICT & COOPERATION
- Department: Auditing
-
Instructor:
Peter T Coleman
h-index: 35 Info - 0 points
FINANCE AND ACCOUNTING FOR THE CONSTRUCT
FIN & ACCTG CONSTRCTN INDUSTRY
- Department: Construction Administration
- W 6:10 p.m.-8 p.m.
-
Instructor:
William Fischer
Info - 3 points
UNDERSTAND CONFLICT & COOPERATION
UNDERSTAND CONF & COOPERATION
- Department: Negotiation & Conflict Resolution
- W 5:10 p.m.-6:50 p.m.
-
Instructor:
Peter T Coleman
h-index: 35 Info - 3 points
PAINTING II
- Department: Visual Arts
- W 10 a.m.-4 p.m.
-
Instructor:
Susanna Coffey
CULPA: 1 Info - 3 points
Molecular Mechanisms
MOLECULAR MECHANISM HLTH/DISEA
- Department: Dental and Oral Surgery
- 0 points
LEGAL ISSUES IN BUILDING CONSTRUCTION
LEGAL ISSUES-BLDG CONSTR
- Department: Construction Administration
- R 6:10 p.m.-8 p.m.
- 3 points
Painting III: Advanced Painting
This advanced painting class will consider contemporary painting in the context of traditional genres, exploring both continuity and discontinuity between contemporary painting and the tradition out of which it arose. Questions considered will include: Do traditional genres such as the history painting, the still-life, the nude, the portrait, the landscape painting have any relevance to contemporary painting? If not, where have these genres migrated to in our contemporary culture? Does contemporary painting exist solely as a cliché of art production, a hand-made status symbol and luxury commodity or can an argument be made for painting as an individual revolt against mass culture? Is painting’s appeal simply due to nostalgia for a now-obsolete technology of representation or does its enduring popularity result from a desire for the physical/personal in a screen-based world? How are contemporary artists using painting today and what critical strategies are available to painters today? Students will be expected to present artwork weekly for individual and group critiques. The course will use an expanded definition of painting so students should feel free to experiment with other media as desired. Students will be required to research historical and contemporary (both art and mass culture) examples of the various genres and to create visual presentations of their research. Supplemental readings will be assigned weekly. Students will spend the last month working on a project of their choice.
- Department: Visual Arts
- R 10 a.m.-4 p.m.
-
Instructor:
Ellen Harvey
Info - 3 points
INTRODUCTION TO NEGOTIATION
- Department: Auditing
-
Instructor:
Martin E Epstein
Info - 0 points
ELEMENTAL TOPICS IN CONSTRUCTION MANAGEM
ELEMENTAL TOPICS IN CNSTR ADMN
- Department: Construction Administration
- M 6:10 p.m.-8 p.m.
- 1.5 points
INTRODUCTION TO NEGOTIATION
INTRO TO NEGO (NECR ONLY)
- Department: Negotiation & Conflict Resolution
- S 9 a.m.-5 p.m.
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Instructor:
Bodi Regan
Info - 3 points
INTRODUCTION TO NEGOTIATION
INTRO TO NEGO (SPS STUDENTS)
- Department: Negotiation & Conflict Resolution
- R 6:10 p.m.-8 p.m.
-
Instructor:
Martin E Epstein
Info - 3 points
INTRODUCTION TO MEDIATION
INTRO TO MEDIATION (NECR ONLY)
- Department: Negotiation & Conflict Resolution
- S 9 a.m.-5 p.m.
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Instructor:
Michele Riley
Info - 3 points
THE BODY IN HEALTH & DISEASE I
- Department: Dental and Oral Surgery
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Instructor:
John T Grbic
h-index: 36 Info - 0 points
U.S. FINANCIAL MARKET STRUCTURE
- Department: School of Professional Studies (DVSP)
- R 6:10 p.m.-8 p.m.
-
Instructor:
Guy M Miller
Info - 3 points
Fieldwork Course in Economics
This course provides an opportunity for students in the Economics Master of Arts Program to engage in off-campus internships for academic credit that will count towards their requirements for the degree. The internships will facilitate the application of economic skills that students have developed in the program and prepare them for future work in the field.
- Department: Economics
- 1 points
SCREENWRITING I
In this introductory workshop, students write several short screenplays over the course of the semester and learn the basics of the craft. Character, action, conflict, story construction, the importance of showing instead of telling, and other essential components are explored.
- Department: Film
- W 2 p.m.-5 p.m.
- M 6 p.m.-9 p.m.
- W 1 p.m.-4 p.m.
- W 9 a.m.-noon
- W 6 p.m.-9 p.m.
- W 2 p.m.-5 p.m.
-
Instructor:
Jamal Joseph
Info - 3 points
ACCOUNTING AND FINANCE FOR TECHNOLOGY
ACCT & FINANCE FOR TECH
An exploration of the central concepts of corporate finance for those who already have some basic knowledge of finance and accounting. This case-based course considers project valuation; cost of capital; capital structure; firm valuation; the interplay between financial decisions, strategic consideration, and economic analyses; and the provision and acquisition of funds. These concepts are analyzed in relation to agency problems: market domination, risk profile, and risk resolution; and market efficiency or the lack thereof. The validity of analytic tools is tested on issues such as highly leveraged transactions, hybrid securities, volatility in initial public offerings, mergers and acquisitions, divestitures, acquisition and control premiums, corporate restructurings, and sustainable and unsustainable market inefficiencies.
- Department: Technology Management
- M 6:10 p.m.-8 p.m.
-
Instructor:
Charissa D Asbury
CULPA: 1 Info - 3 points
ACCOUNTING AND FINANCE FOR TECHNOLOGY
ACCT & FINANCE FOR TECH: EMS
An exploration of the central concepts of corporate finance for those who already have some basic knowledge of finance and accounting. This case-based course considers project valuation; cost of capital; capital structure; firm valuation; the interplay between financial decisions, strategic consideration, and economic analyses; and the provision and acquisition of funds. These concepts are analyzed in relation to agency problems: market domination, risk profile, and risk resolution; and market efficiency or the lack thereof. The validity of analytic tools is tested on issues such as highly leveraged transactions, hybrid securities, volatility in initial public offerings, mergers and acquisitions, divestitures, acquisition and control premiums, corporate restructurings, and sustainable and unsustainable market inefficiencies.
- Department: Technology Management
- R 7:30 p.m.-9 p.m.
-
Instructor:
Charissa D Asbury
CULPA: 1 Info - 3 points
DIGITAL STRATEGY AND LEADERSHIP
DIGITAL STRATEGY & LEADERSHIP
An examination of technology as a crucial aspect of the operation of most businesses. The first part of the course focuses on the structuring and planning of technology projects and investments as well as the analysis of financial returns and their impact on the productivity of the larger organization. The second part of the course focuses on the connections between technology and product development, marketing, and the positioning of an organization in its external environment.
- Department: Technology Management
- T 6:10 p.m.-8 p.m.
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Instructor:
Douglas M Scherer
Info - 3 points
DIGITAL STRATEGY AND LEADERSHIP
DIGITAL STRAT & LDRSHP - NYC
An examination of technology as a crucial aspect of the operation of most businesses. The first part of the course focuses on the structuring and planning of technology projects and investments as well as the analysis of financial returns and their impact on the productivity of the larger organization. The second part of the course focuses on the connections between technology and product development, marketing, and the positioning of an organization in its external environment.
- Department: Technology Management
-
Instructor:
Arthur Langer
Info - 3 points
DIGITAL STRATEGY AND LEADERSHIP
DIGITAL STRAT & LDRSHP - PARIS
An examination of technology as a crucial aspect of the operation of most businesses. The first part of the course focuses on the structuring and planning of technology projects and investments as well as the analysis of financial returns and their impact on the productivity of the larger organization. The second part of the course focuses on the connections between technology and product development, marketing, and the positioning of an organization in its external environment.
- Department: Technology Management
-
Instructor:
Arthur Langer
Info - 3 points
BEHAVIORAL CHALLENGES IN TECHNOLOGY MANA
An in-depth study of the intricacies of managing technical personnel and management teams in a fast paced and evolving business environment. Emphasis is placed on key challenges including the management of multiple technology projects, software development processes, and communications among technology managers and senior managers, developers, programmers, and customers.
- Department: Technology Management
- W 6:10 p.m.-8 p.m.
-
Instructor:
J. Patrick O'Connell
Info - 3 points
SCHEDULNG FOR MODERN CONSTRUCTION
- Department: Construction Administration
- T 6:10 p.m.-8 p.m.
-
Instructor:
Sadia I Janjua
Info - 1.5 points
Research in Economics
This is a required course that facilitates the capstone research paper writing process for second-year students enrolled in the M.A. Program in Economics. The research paper provides an opportunity to write a substantial piece of academic work in which the student is expected to demonstrate mastery of a field, along with the ability to think originally and to convey results clearly in writing.
THE TECHNOLOGY OF RENEWABLE ENERGY
Students are expected to have completed a year of high school physics and chemistry. It would be best to have also taken college level physics and chemistry.
Renewable energy is generated from natural processes that are continuously replenished. Aside from geothermal and tidal power, solar radiation is the ultimate source of renewable energy. In order to have a sustainable environment and economy, CO2 emissions must be reduced (and eventually stopped). This requires that the fossil fuel based technologies underlying our present electricity generation and transportation systems be replaced by renewable energy. In addition, the transition to renewable technologies will move nations closer to energy independence and thereby reduce geopolitical tensions associated with energy trading. This course begins with a review of the basics of electricity generation and the heat engines that are the foundation of our current energy systems. This course will emphasize the inherent inefficiency associated with the conversion of thermal energy to electrical and mechanical energy. The course then covers the most important technologies employed to generate renewable energy. These are hydroelectric, wind, solar thermal, solar photovoltaic, geothermal, biomass/biofuel, tidal and wave power. The course ends with a description of energy storage technologies, energy markets and possible pathways to a renewable energy future.
- Department: Sustainability Technology
- R 6:10 p.m.-8 p.m.
-
Instructor:
Jonathan Hollander
Info - 3 points
OPERATIONS MANAGEMENT IN IT
OPERATIONS MGMT IN IT: EMS
This course provides an examination of the role the technology leader plays in the daily operations and performance management of an organization. The course focuses on how tech leaders can manage both up and down within their organizations through critical examination of current IT topics such as Outsourcing, Cloud Computing, Enterprise Architecture (as a strategy), Information Security, Risk Management, IT Governance, and determining/communicating the business value of IT. Students leave the course with a deep understanding of the dramatically different priorities, skills, and actions required to succeed as an IT leader.
- Department: Technology Management
- W 9 p.m.-10 p.m.
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Instructor:
Craig Cuyar
Info - 3 points
ACTIVATING EMPLOYEES
- Department: Strategic Communication
- W 6:10 p.m.-8 p.m.
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Instructor:
Ethan McCarty
Info - 3 points
INTRAPERSONAL DYNAMICS & CONFLICT
INTRAP. DYNAMICS & CONFLICT
- Department: Negotiation & Conflict Resolution
- SUSU 9 a.m.-5 p.m.
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Instructor:
Barry Sommer
Info - 3 points
TECHNOLOGY AND THE LAW
TECHNOLOGY AND THE LAW: EMS
An examination of the legal issues and challenges confronting today’s technology executives. The course covers copyright, patent infringement, outsourcing contracts, electronic commerce law, intellectual property, and methods of establishing and monitoring legal policies as they relate to the use and security of current and emerging technologies. Course content may be amended at any time in response to changes in legislation as well as developments in the industry.
- Department: Technology Management
- S 11 a.m.-1:30 p.m.
- 3 points