NONFICTION WORKSHOP

• Department: Writing
• F 2 p.m.-5 p.m.
• None None-None
• T 2 p.m.-5 p.m.
• Instructor: Sarah L Perry
  Info
• Instructor: Maria Venegas
  Info
• Instructor: Brenda Wineapple
  Wikipedia Info
• 6 points

PRIN/APPL OF SOCIETY & CULTURE

Prerequisites: graduate standing. Introductory survey of major concepts and areas of research in social and cultural anthropology. Emphasis is on both the field as it is currently constituted and its relationship to other scholarly and professional disciplines. Required for students in Anthropology Department's master degree program and for students in the graduate programs of other departments and professional schools desiring an introduction in this field.

• Department: Anthropology
• M 2:10 p.m.-4 p.m.
• Instructor: Ellen Marakowitz
  CULPA: 1 Info
• 3 points

PROBABILITY

Prerequisites: At least one semester of calculus.
A calculus-based introduction to probability theory. Topics covered include random variables, conditional probability, expectation, independence, Bayes' rule, important distributions, joint distributions, moment generating functions, central limit theorem, laws of large numbers and Markov's inequality.

• Department: Statistics
• TR 8:40 a.m.-11:25 a.m.
• Instructor: Regina Dolgoarshinnykh
  CULPA: 2 Info
• 3 points

STATISTICAL INFERENCE

Prerequisites: STAT GR5203 or the equivalent, and two semesters of calculus.
Calculus-based introduction to the theory of statistics. Useful distributions, law of large numbers and central limit theorem, point estimation, hypothesis testing, confidence intervals, maximum likelihood, likelihood ratio tests, nonparametric procedures, theory of least squares and analysis of variance.

• Department: Statistics
• MW 6:10 p.m.-8:55 p.m.
• Instructor: Bodhisattva Sen
  h-index: 24 Info
• 3 points

APPLIED ANALYTICS FRAMEWORKS & METHDS II

APP AN FRAMEWORKS & METHODS II

• Department: Applied Analytics
• M 6:10 p.m.-8 p.m.
• M 8:10 p.m.-10 p.m.
• Instructor: David Shilane
  Info
• 3 points

LINEAR REGRESSION MODELS

Prerequisites: STAT GR5203 and GR5204 or the equivalent.
Theory and practice of regression analysis, Simple and multiple regression, including testing, estimation, and confidence procedures, modeling, regression diagnostics and plots, polynomial regression, colinearity and confounding, model selection, geometry of least squares. Extensive use of the computer to analyse data.

• Department: Statistics
• TR 6:10 p.m.-7:25 p.m.
• MW 8:40 a.m.-9:55 a.m.
• 3 points

STAT COMP & INTRO DATA SCIENCE

Corequisites: STAT GR5204 and GR5205 or the equivalent.
Introduction to programming in the R statistical package: functions, objects, data structures, flow control, input and output, debugging, logical design, and abstraction.  Writing code for numerical and graphical statistical analyses.  Writing maintainable code and testing, stochastic simulations, paralleizing data analyses, and working with large data sets.  Examples from data science will be used for demonstration.

• Department: Statistics
• F 2:40 p.m.-5:25 p.m.
• Instructor: Thibault Vatter
  h-index: 8 Info
• 3 points

STAT COMP & INTRO DATA SCIENCE

Corequisites: STAT GR5204 and GR5205 or the equivalent.
Introduction to programming in the R statistical package: functions, objects, data structures, flow control, input and output, debugging, logical design, and abstraction.  Writing code for numerical and graphical statistical analyses.  Writing maintainable code and testing, stochastic simulations, paralleizing data analyses, and working with large data sets.  Examples from data science will be used for demonstration.

• Department: Statistics
• F 2:40 p.m.-5:25 p.m.
• Instructor: Thibault Vatter
  h-index: 8 Info
• 3 points

STAT COMP & INTRO DATA SCIENCE

Corequisites: STAT GR5204 and GR5205 or the equivalent.
Introduction to programming in the R statistical package: functions, objects, data structures, flow control, input and output, debugging, logical design, and abstraction.  Writing code for numerical and graphical statistical analyses.  Writing maintainable code and testing, stochastic simulations, paralleizing data analyses, and working with large data sets.  Examples from data science will be used for demonstration.

• Department: Statistics
• F 2:40 p.m.-5:25 p.m.
• F 8:40 a.m.-9:55 a.m.
• Instructor: Thibault Vatter
  h-index: 8 Info
• Instructor: Gabriel Young
  CULPA: 7 Info
• 3 points

PYTHON FOR DATA ANALYSIS

• Department: Applied Analytics
• S 12:10 p.m.-2 p.m.
• T 8:10 p.m.-10 p.m.
• Instructor: Helga Hartelt Baez
  Info
• Instructor: Max Vilenchik
  Info
• 3 points

DIRECTING I

Corequisites:
FILM R6037
,
FILM R6095
.
Students explore the grammatical rules and narrative elements of cinematic storytelling by completing a minimum of three short, nondialogue exercises and two sound exercises, all shot and edited in video. Emphasizes using the camera as an articulate narrator to tell a coherent, grammatically correct, engaging, and cinematic story. Technical workshops on camera, lighting, sound, and editing accompany the workshops, as well as lectures that provide a methodology for the director.

• Department: Film
• W 2 p.m.-5 p.m.
• R 2 p.m.-5 p.m.
• M 10 a.m.-1 p.m.
• M 2 p.m.-5 p.m.
• R 2 p.m.-5 p.m.
• M 6 p.m.-9 p.m.
• Instructor: Hilary Brougher
  Wikipedia Info
• 3 points

MICROECONOMICS ANALYSIS I

• Department: Economics
• MW 1:10 p.m.-2:25 p.m.
• Instructor: Wouter R Vergote
  CULPA: 15 Info
• 3 points

MACROECONOMICS ANALYSIS I

• Department: Economics
• TR 4:10 p.m.-5:25 p.m.
• Instructor: Ronald Miller
  CULPA: 4 Info
• 3 points

ADVANCED MICROECONOMICS

• Department: Economics
• M 10:10 a.m.-noon
• 3 points

ADVANCED MACROECONOMICS

• Department: Economics
• W 4:10 p.m.-6 p.m.
• Instructor: Irasema Alonso
  CULPA: 12 Info
• 3 points

QUANT MTHDS IN INVESTMENT MGMT

Prerequisites: Knowledge of statistics basics and programming skills in any programming language. 
Surveys the field of quantitative investment strategies from a "buy side" perspective, through the eyes of portfolio managers, analysts and investors. Financial modeling there often involves avoiding complexity in favor of simplicity and practical compromise. All necessary material scattered in finance, computer science and statistics is combined into a project-based curriculum, which give students hands-on experience to solve real world problems in portfolio management. Students will work with market and historical data to develop and test trading and risk management strategies. Programming projects are required to complete this course.

• Department: Mathematics
• T 7:40 p.m.-10 p.m.
• Instructor: Alexander Greyserman
  Info
• 3 points

DELIVERING THE STRAT MESSAGE

DELIV THE STRAT MESSAGE

• Department: School of Professional Studies
• W 6:10 p.m.-8 p.m.
• 3 points

DELIVERING THE STRAT MESSAGE

DELIV STRAT MESSAGE - CEU

• Department: School of Professional Studies
• W 6:10 p.m.-8 p.m.
• 3 points

DELIVERING THE STRAT MESSAGE

• Department: School of Professional Studies
• M 6:10 p.m.-8 p.m.
• 3 points

DELIVERING THE STRAT MESSAGE

DELIV STRAT MESSAGE - CEU

• Department: School of Professional Studies
• M 6:10 p.m.-8 p.m.
• 3 points

DIRECTING ACTORS I

• Department: Film
• W 6 p.m.-9 p.m.
• W 2 p.m.-5 p.m.
• R 10 a.m.-1 p.m.
• M 10 a.m.-1 p.m.
• M 2 p.m.-5 p.m.
• Instructor: Adrienne Weiss
  Info
• Instructor: Mikael Sodersten
  Info
• Instructor: Jodie Markell
  Wikipedia Info
• Instructor: John Rubin
  Info
• Instructor: Shira-Lee Shalit
  Info
• 3 points

ADVANCED MACHINE LEARNING

DATA MINING

Prerequisites: STAT GR5241
This course covers some advanced topics in machine learning and has an emphasis on applications to real world data.  A major part of this course is a course project which consists of an in-class presentation and a written project report.

• Department: Statistics
• TR 4:10 p.m.-5:25 p.m.
• 3 points

EXTERNAL STAKEHOLDER REQUIREMENTS

• Department: Enterprise Risk Management
• T 8:10 p.m.-10 p.m.
• 3 points

EXTERNAL STAKEHOLDER REQUIREMENTS

EXT STAKEHOLDER REQ (ONLINE)

• Department: Enterprise Risk Management
• T 6:10 p.m.-8 p.m.
• Instructor: R S Forston
  Info
• 3 points

VALUE OF BRAND

• Department: Strategic Communication
• M 6:10 p.m.-8 p.m.
• None None-None
• Instructor: Joseph E Pantigoso
  Info
• 3 points

PROG FOR QUANT & COMP FINANCE

This course covers programming with applications to finance. The applications may include such topics as yield curve building and calibration, short rate models, Libor market models, Monte Carlo simulation, valuation of financial instruments such as options, swaptions and variance swaps, and risk measurement and management, among others. Students will learn about the underlying theory, learn coding techniques, and get hands-on experience in implementing financial models and systems.

• Department: Mathematics
• R 8:10 p.m.-10 p.m.
• Instructor: Keith Lewis
  Info
• 3 points

STRATEGIC VISUAL COMMUNICATION

• Department: Strategic Communication
• M 4:10 p.m.-6 p.m.
• 3 points

CAPITAL MARKETS & INVESTMENTS

Risk/return tradeoff, diversification and their role in the modern portfolio theory, their consequences for asset allocation, portfilio optimization.  Capitol Asset Pricing Model, Modern Portfolio Theory, Factor Models, Equities Valuation, definition and treatment of futures, options and fixed income securities will be covered.

• Department: Mathematics
• F 5 p.m.-7:20 p.m.
• Instructor: Alexei Chekhlov
  CULPA: 3 h-index: 10 Info
• 3 points

COMMUNICATION RESEARCH & INSIGHTS

COMM RESEARCH & INSIGHTS

• Department: Strategic Communication
• R 8:10 p.m.-10 p.m.
• 3 points

ADVANCED DATA ANALYSIS

Prerequisites: W4315 and either another statistics course numbered above the 4200 or permission of instructor.
Required for the major in statistics. Data analysis using a computer statistical package and selected exploratory data analysis subroutines. Topics include editing of data for errors, exploratory and standard techniques for one-way analysis of variance, linear regression, and two-way analysis of variance. Material is presented in case-study format.

• Department: Statistics
• F 5:10 p.m.-7:40 p.m.
• Instructor: Demissie Alemayehu
  h-index: 14 Info
• 3 points

RESEARCH DESIGN

• Department: Applied Analytics
• M 6:10 p.m.-8 p.m.
• T 6:10 p.m.-8 p.m.
• T 8:10 p.m.-10 p.m.
• W 6:10 p.m.-8 p.m.
• R 6:10 p.m.-8 p.m.
• F 12:10 p.m.-2 p.m.
• F 2:10 p.m.-4 p.m.
• F 10:10 a.m.-noon
• T 6:10 p.m.-8 p.m.
• 3 points

STRATEGIC COMM FOR RISK PROFESSIONALS

STRAT COMM FOR RISK PROF

• Department: Enterprise Risk Management
• F 2:10 p.m.-4 p.m.
• M 6:10 p.m.-8 p.m.
• M 8:10 p.m.-10 p.m.
• T 6:10 p.m.-8 p.m.
• T 8:10 p.m.-10 p.m.
• W 6:10 p.m.-8 p.m.
• W 8:10 p.m.-10 p.m.
• R 6:10 p.m.-8 p.m.
• R 8:10 p.m.-10 p.m.
• M 6:10 p.m.-8 p.m.
• M 8:10 p.m.-10 p.m.
• M 6:10 p.m.-8 p.m.
• Instructor: Sim Segal
  Info
• Instructor: Violet Diamant
  Info
• 3 points

STRATEGIC COMM FOR RISK PROFESSIONALS

STRAT COMM FOR RISK PROF (ONL)

• Department: Enterprise Risk Management
• T 6:10 p.m.-8 p.m.
• Instructor: Steve Lindo
  Info
• 3 points

FOUNDATIONS FOR THE KNOWLEDGE-DRIVEN ORG

INFO & KNOWLDGE, 21ST CEN

• Department: Information & Knowledge Strat
• 3 points

HEDGE FUNDS STRATEGIES & RISK

The hedge fund industry has continued to grow after the financial crisis, and hedge funds are increasingly important as an investable asset class for institutional investors as well as wealthy individuals. This course will cover hedge funds from the point of view of portfolio managers and investors. We will analyze a number of hedge fund trading strategies, including fixed income arbitrage, global macro, and various equities strategies, with a strong focus on quantitative strategies. We distinguish hedge fund managers from other asset managers, and discuss issues such as fees and incentives, liquidity, performance evaluation, and risk management. We also discuss career development in the hedge fund context.

• Department: Mathematics
• T 8:10 p.m.-10 p.m.
• Instructor: Eric Yeh
  Info
• 3 points

POETRY WORKSHOP

• Department: Writing
• W 2 p.m.-5 p.m.
• R 10 a.m.-1 p.m.
• F 2 p.m.-5 p.m.
• R 10 a.m.-1 p.m.
• Instructor: Timothy B Donnelly
  Info
• Instructor: Shane McCrae
  Wikipedia Info
• Instructor: Emily F Skillings
  Info
• Instructor: Wendy Xu
  Info
• 6 points

MANAGING INFORMATION & KNOWLEDGE

In this course students learn the principles of management as they relate to enterprise-wide information and knowledge services. Attention is given to the philosophy and history of information and knowledge services, specifically as this background affects students’ future performance as managers and leaders in the workplace. The focus is on management and leadership skills, knowledge sharing, and the role of knowledge strategy in strengthening the corporate knowledge culture.

• Department: School of Professional Studies
• W 6:10 p.m.-8 p.m.
• Instructor: Guy St. Clair
  Wikipedia Info
• 3 points

MANAGING INFORMATION & KNOWLEDGE

MANAGING INFO & KNWLDGE - CEU

In this course students learn the principles of management as they relate to enterprise-wide information and knowledge services. Attention is given to the philosophy and history of information and knowledge services, specifically as this background affects students’ future performance as managers and leaders in the workplace. The focus is on management and leadership skills, knowledge sharing, and the role of knowledge strategy in strengthening the corporate knowledge culture.

• Department: School of Professional Studies
• W 6:10 p.m.-8 p.m.
• Instructor: Guy St. Clair
  Wikipedia Info
• 3 points

KNOWLEDGE PROCESSES, PRACTICES & GOVERNA

FINDABILITY & INNOVATION

• Department: Information & Knowledge Strat
• Instructor: Ralph Poole
  h-index: 0 Info
• 3 points

LEADING BUSINESS ANALYTICS FOR THE ENTER

BUSINESS ANALYTICS MANAGEMENT

• Department: Information & Knowledge Strat
• Instructor: Jeanne G Harris
  Wikipedia h-index: 27 Info
• 3 points

SCIENCE FOR BIOETHICISTS

SCI FOR BIOETHICISTS (ONLINE)

• Department: Bioethics
• W 4:30 p.m.-6 p.m.
• Instructor: Jennifer M Gumer
  Info
• 3 points

SCIENCE FOR BIOETHICISTS

SCI FOR BIOETHICISTS (ONLINE)

• Department: Bioethics
• W 4:30 p.m.-6 p.m.
• Instructor: Jennifer M Gumer
  Info
• 3 points

SQL & RELATIONAL DATABASES

• Department: Applied Analytics
• M 8:10 p.m.-10 p.m.
• T 8:10 p.m.-10 p.m.
• Instructor: Nikolaos Machairas
  Info
• 3 points

ECONOMIC POLICY ANALYSIS

ECONOMICS POLICY ANALYSIS

• Department: Economics
• T 12:10 p.m.-2 p.m.
• 3 points

PHILOSOPHY OF BIOETHICS

• Department: Bioethics
• R 12:10 p.m.-2:40 p.m.
• Instructor: Arthur Kuflik
  Info
• 3 points

PHILOSOPHY OF BIOETHICS

PHIL OF BIOETHICS (ONLINE)

• Department: Bioethics
• W 6:10 p.m.-8 p.m.
• M 7:30 p.m.-9:30 p.m.
• Instructor: Arthur Kuflik
  Info
• Instructor: Jennifer M Gumer
  Info
• 3 points

PHILOSOPHY OF BIOETHICS

PHIL OF BIOETHICS (ONLINE)

• Department: Bioethics
• M 7:30 p.m.-9:30 p.m.
• M 9:30 a.m.-11:30 a.m.
• Instructor: Jennifer M Gumer
  Info
• Instructor: Arthur Kuflik
  Info
• 3 points

PHILOSOPHY OF BIOETHICS

PHIL OF BIOETHICS (SAN FRAN)

• Department: Bioethics
• Instructor: Arthur Kuflik
  Info
• 3 points

STRATEGIC RISK MANAGEMENT

STRATEGIC RISK MGMT

• Department: Enterprise Risk Management
• R 8:10 p.m.-10 p.m.
• M 8:10 p.m.-10 p.m.
• Instructor: Carlo Di Florio
  Info
• 3 points

STRATEGIC RISK MANAGEMENT

STRAT RISK MGMT (ONLINE)

• Department: Enterprise Risk Management
• T 6:10 p.m.-8 p.m.
• Instructor: Cecil R House
  Info
• 3 points

FINANCIAL RISK MGMT & REGULATION

FINANCIAL RISK MGMT & REGULATN

Prerequisites: student expected to be mathematically mature and familiar with probability and statistics, arbitrage pricing theory, and stochastic processes.
The course will introduce the notions of financial risk management, review the structure of the markets and the contracts traded, introduce risk measures such as VaR, PFE and EE, overview regulation of financial markets, and study a number of risk management failures. After successfully completing the course, the student will understand the basics of computing parametric VaR, historical VaR, Monte Carlo VaR, cedit exposures and CVA and the issues and computations associated with managing market risk and credit risk. The student will be familiar with the different categories of financial risk, current regulatory practices, and the events of financial crises, especially the most recent one.

• Department: Mathematics
• R 8:10 p.m.-10 p.m.
• Instructor: Harvey Stein
  h-index: None Info
• 3 points

LAW & BIOETHICS

• Department: Bioethics
• T 8:10 p.m.-10 p.m.
• Instructor: David N Hoffman
  h-index: 2 Info
• 3 points

LAW & BIOETHICS

• Department: Bioethics
• T 8:10 p.m.-10 p.m.
• 0 points

MACHINE LEARNING: CONCEPTS & APPLICATION

• Department: Applied Analytics
• F 12:30 p.m.-2:50 p.m.
• T 8:10 p.m.-10:30 p.m.
• Instructor: Siddhartha Dalal
  Info
• Instructor: Jinjun Xiong
  Info
• 3 points

OPERATIONAL RISK MANAGEMENT

OPERATIONAL RISK MGMT

• Department: Enterprise Risk Management
• R 6:10 p.m.-8 p.m.
• W 8:10 p.m.-10 p.m.
• M 8:10 p.m.-10 p.m.
• Instructor: Prasad Kodali
  Info
• 3 points