DIR RSCH 20TH-C RUSSIAN LIT I

Prerequisites: the department's permission.

• Department: Slavic Languages
• Instructor: Mark Lipovetsky
  Wikipedia Info
• 2-4 points

VISITING ARTISTS

• Department: Theatre Arts
• T 10 a.m.-noon
• Instructor: Anne Bogart
  Wikipedia Info
• 3 points

CLASSICAL CHINESE POETRY

This graduate seminar aims to introduce students to poetry and poetics in the eighth century, the High Tang. We will trace the changes and transformations of poetic language and social functions of
shi
and
fu
poetry, in conjunction with the expansion of the literary scene from the court/capital to the community of serving officials, who traveled throughout the empire, wrote about their “provincial” experiences, and formed literary connections with one another through poetry. We will examine major poets, including Zhang Jiuling, Meng Haoran, Wang Wei, Li Bai, and Du Fu, and think about what happens to their poetry and their imagination of the empire when the court/capital started to lose its status as the center of cultural production and the arbiter of tastes. Students will also learn methods, sources, and bibliographic traditions as part of the study of medieval literature. We will explore questions such as: What can eight-century anthologies tell us about contemporary literary tastes? How were literary collections of eighth-century poets preserved, transmitted and reconstituted in later periods? How might the “High Tang” look different when we take into consideration of changes in values and bibliographic interventions of later periods?

Prerequisite: students should have at least two years of experience learning literary Chinese.

• Department: East Asian Languages and Cultures
• M 4:10 p.m.-6 p.m.
• Instructor: Lu Kou
  Info
• 4 points

QUANTUM FIELD THEORY II

Prerequisites: PHYS G6037-G6038. Relativistic quantum mechanics and quantum field theory.

• Department: Physics
• TR 2:40 p.m.-3:55 p.m.
• Instructor: Alberto Nicolis
  Info
• 4.5 points

THEATRE PRACTICUM II

IMPULSE/STIMULUS/SPECIFICITY

TBD

• Department: Theatre Arts
• M 2:10 p.m.-5 p.m.
• Instructor: Tina Benko
  Info
• 3 points

S ADVANCED PATENTS

• Department: Law
• T 6:20 p.m.-8:10 p.m.
• 2 points

THEATRE PRACTICUM III

SELF TO PERFORMANCE

• Department: Theatre Arts
• TR 2:10 p.m.-5 p.m.
• 0-3 points

THEATRE PRACTICUM III

EARLY CAREER PREP

• Department: Theatre Arts
• W 10 a.m.-1 p.m.
• Instructor: Scott V Whitehurst
  Info
• 0-3 points

Graduate Seminar in Japanese Cinema and

Grad Seminar Japanese Cin

In this course, we will examine a series of key writings on cinema and visual culture in Japan from the 1910s to the late 1960s.  Major topics will include:

1. Cinema and its technology/technics (sound, color, and film form)

2. Cinema and its intersection with politics and aesthetics (Marxism and the Proletarian Film Movement, cinematic realism, colonialism, Third Worldism, and Japanese New Wave)

3. The articulations of cinema in broader intellectual, technological, socio-cultural, and institutional discourse (film education, documentary, and 
bunka eiga
)

In an attempt to explore the transitional position of cinema and media culture in Japanese cultural history, the course also critically approaches contact points between cinema, theatre (especially
shingeki
), literature, photography, and television.  All mandatory readings each week will be primary sources in Japanese, and additional scholarly and/or theoretical writings in English will also be assigned or provided for reference.

• Department: East Asian Languages and Cultures
• W 4:10 p.m.-6 p.m.
• Instructor: Takuya Tsunoda
  Info
• 4 points

C JURISPRUDENCE OF WAR

This is a Law School course. For more detailed course information, please go to the Law School Curriculum Guide at: http://www.law.columbia.edu/courses/search

• Department: Law
• MW 10:40 a.m.-noon
• 3 points

S AMERICAN JURISPRUDENCE

• Department: Law
• M 6:20 p.m.-8:10 p.m.
• 2 points

CONDENSED MATTER PHYSICS II

• Department: Physics
• TR 4:10 p.m.-5:25 p.m.
• Instructor: Yasutomo Uemura
  Info
• 3 points

PUBLIC HEALTH PRACTICE SEMINAR

• Department: Public Health
• F 11:30 a.m.-12:50 p.m.
• Instructor: Heather Krasna
  h-index: 5 Info
• 0.5 points

Tutorial in general public health

TUTORIAL GENERAL PUBLIC H

Tailored to the particular interests and needs of individual students, the tutorials take many forms-literature reviews, research projects, field trips, and other special studies or learning experiences. Their objective is to enrich the student’s program. General public health subject areas for tutorials might include dental public health, health education, international health, nutrition, drug abuse, and other topical concerns not specifically dealt with in formal courses or in departmental or other study programs.

• Department: General Public Health
• Instructor: Stephen P Kachur
  Info
• 0-6 points

M.A. ESSAY DIRECTION

• Department: French
• 6 points

INDIV PROJECTS IN MUSICOLOGY

INDIV PROJECT IN MUSICOLOGY

Sec. 1: Ethnomusicology; Sec. 2: Historical Musicology; Sec. 3: Music Theory; Sec. 4: Music Cognition; Sec. 5: Music Philosophy.

• Department: Music
• Instructor: Susan Boynton
  CULPA: 18 Info
• Instructor: Alessandra M Ciucci
  CULPA: 1 Info
• Instructor: Julia Doe
  Info
• Instructor: Kevin Fellezs
  CULPA: 4 Info
• Instructor: Aaron A Fox
  CULPA: 7 Info
• Instructor: Walter M Frisch
  CULPA: 17 Info
• Instructor: Giuseppe Gerbino
  CULPA: 12 Info
• Instructor: Knar Abrahamyan
  Info
• Instructor: Mariusz Kozak
  CULPA: 4 h-index: 5 Info
• Instructor: Elaine Sisman
  CULPA: 13 Wikipedia Info
• Instructor: Benjamin A Steege
  Info
• Instructor: Christopher J Washburne
  CULPA: 31 Info
• 3 points

INDIV PROJECTS IN MUSICOLOGY

Sec. 1: Ethnomusicology; Sec. 2: Historical Musicology; Sec. 3: Music Theory; Sec. 4: Music Cognition; Sec. 5: Music Philosophy.

• Department: Music
• Instructor: Ruth Opara
  Info
• 3 points

Applied Regression I

APPLIED REGRESSION I

This course will provide an introduction to the basics of regression analysis. The class will proceed systematically from the examination of the distributional qualities of the measures of interest, to assessing the appropriateness of the assumption of linearity, to issues related to variable inclusion, model fit, interpretation, and regression diagnostics. We will primarily use scalar notation (i.e. we will use limited matrix notation, and will only briefly present the use of matrix algebra).

• Department: Biostatistics
• R 1 p.m.-3:50 p.m.
• Instructor: Stanley Lemeshow
  Info
• 3 points

Healthcare Management, Design, and Strat

Healthcare Mgmt Design &

COURSE DESCRIPTION AND LEARNING OBJECTIVES
The U.S. healthcare system is an enormously complex, trillion-dollar industry, accounting for approximately 18% of GDP. The healthcare sector is vast and covers multiple different players from patients, providers, payors, to bio/pharma developers and innovators. Each part of the healthcare sector brings a different set of business challenges that touch on aspects from Finance, Marketing, Operations, Accounting, and more. The healthcare industry is going through a transformation with the development of new technologies, increased sophistication and adoption of electronic medical records systems and data collection architectures, and new models of the delivery of care and payment systems. This tremendous dynamism is unmatched by any other industry and offers incredible opportunities for new business endeavors. This course provides students the opportunity to learn about i) approaches to doing consulting; ii) key considerations diving strategic decision-making in the healthcare industry; and iii) the chance to put these concepts to practice by working on a set of company-sponsored applied projects. Student teams of 5-6 people, with 3-4 MBA (CBS) students and 1-2 medical (CUIMC) students, will work hand in hand with the instructors and company representatives to achieve company goals through the practical application of fundamental core business practices. Through these projects, students will be exposed to the unique challenges and opportunities in the healthcare sector. Some examples of potential projects include:

For a pharmaceutical company, evaluate the commercial potential of a new therapeutic class.
Evaluate and identify improvement opportunities in the patient evaluation process of a clinical unit at CUIMC. Redesign the standard workflow ad evaluate the financial and operational impact of these changes.
Utilize consumer predictive analytics to guide marketing strategies for a biotech device.
The scope of sponsoring companies spans large firms in biotech and pharmaceuticals, smaller startups in healthcare analytics and/or biotech, large provider systems, as well as smaller clinics. Companies provide the project scope and relevant data, faculty provides guidance on best practices, and your team will provide the answers.

Throughout this course, students will execute on a healthcare project to:
Use tools and ideas from operations, business analytics, finance, marketing, and strategy to solve interesting and exciting business proble

• Department: Decision, Risk and Operations
• T 6 p.m.-9:15 p.m.
• 3 points

Academic Careers Workshop

This course is open to all graduate students in English and Comparative Literature who have passed their oral exams. The course, which students may take for R-credit, has several aims. It will help you: sharpen the focus of your dissertation and clarify the nature of its contribution; expand your scholarly profile, illuminating the breadth of what you have to offer academic life; and launch activities that can make your potential contributions visible and legible. We will look closely at the kinds of materials you will circulate on the job market: cover letters,
CV
s, teaching statements, research statements, DEI statements, teaching portfolios, and more. We will workshop these in the seminar, while also practicing the oral forms you will encounter in the job market: interviews, presentations, job talks. At the same time, one of the central aims of the seminar is to help you develop your sense of who you are as a scholar, teacher, and member of the profession more broadly, whether you are just post-orals or about to defend your dissertation. Thus, throughout the semester we will engage in exercises such as elevator pitches or the production of creative, collaborative, and / or public humanities projects that will help you expand the universe of professional possibilities and highlight the richness of your potential contributions.

Preparing yourself for the academic job market can be emotionally wrenching, but it can also be exciting. The seminar will serve not only as a workshop but also as a supportive community of scholars, teachers, readers, and writers helping one another envision the work they might do and, at the same time, remember why it matters.

• Department: English and Comparative Literature
• M 4:10 p.m.-6 p.m.
• Instructor: Julie S Peters
  CULPA: 5 Info
• 4 points

APPLIED REGRESSION I

• Department: ONLINE MS IN EPIDEMIOLOGY
• Instructor: Tonguc Yaman
  Info
• 3 points

Applied Regression

This course will provide students with a thorough introduction to applied regression analysis, which has been a commonly used and almost standard method for analyzing continuous response data in Public Health research. Topics covered include simple linear regression, multiple linear regression, analysis of variance, parameter estimation, hypothesis testing, interpretation of estimates, interaction terms, variable recoding, examination of validity of underlying assumptions, regression diagnostics, model selection, logistic regression analysis, generalized linear models as well as discussions on relationships of variables in research and using regression results for either prediction or estimation purposes. Real data are emphasized and analyzed using SAS.

• Department: General Public Health
• W 7 p.m.-8 p.m.
• Instructor: Dan Liao
  Info
• 3 points

ADVANCED TOPICS IN IEOR

Diffusion Models AI & RL

Selected topics in IEOR. Content varies from year to year. May be repeated for credit.

• Department: Industrial Engineering and Operations Research
• MW 10:10 a.m.-11:25 a.m.
• Instructor: Xunyu Zhou
  h-index: 54 Info
• 3 points

ADVANCED TOPICS IN IEOR

Advanced topics in RL

Selected topics in IEOR. Content varies from year to year. May be repeated for credit.

• Department: Industrial Engineering and Operations Research
• MW 11:40 a.m.-12:55 p.m.
• Instructor: Shipra Agrawal
  h-index: 24 Info
• 3 points

ADVANCED TOPICS IN IEOR

Contextual Optimization

Selected topics in IEOR. Content varies from year to year. May be repeated for credit.

• Department: Industrial Engineering and Operations Research
• F 10:10 a.m.-12:40 p.m.
• Instructor: Adam N Elmachtoub
  CULPA: 1 h-index: 13 Info
• 3 points

ADVANCED TOPICS IN IEOR

Asymp for Stoch Serv Syst

Selected topics in IEOR. Content varies from year to year. May be repeated for credit.

• Department: Industrial Engineering and Operations Research
• R 2:40 p.m.-5:10 p.m.
• Instructor: Martin Reiman
  Wikipedia Info
• 3 points

ADVANCED TOPICS IN IEOR

Scheduling Algorithms

Selected topics in IEOR. Content varies from year to year. May be repeated for credit.

• Department: Industrial Engineering and Operations Research
• TR 10:10 a.m.-11:25 a.m.
• Instructor: Clifford Stein
  CULPA: 31 Wikipedia h-index: 53 Info
• 3 points

ADVANCED APPLICATION OF THEORY TO PRACT

• Department: Rehabilitation Medicine (RMED)
• Instructor: Glen Gillen
  Info
• 3 points

Gross Anatomy

This intensive 15-week course during the first term of the DPT curriculum provides students with detailed coverage of human anatomy through lecture and cadaver dissection. The focus of the course is on structure and the integral relationship between structure and function. A comprehensive understanding of normal structure and function provides the foundation for understanding abnormal structure and function. Both the lecture and laboratory components of the course are critical to success in the program and as a competent entry-level clinician.

This course uses a regional approach to study the gross anatomical structures of the human body, with emphasis on the musculoskeletal system and its associated vascular and neural elements. The structure of synovial joints and their soft tissue support systems will be addressed. The thoracic, abdominal, and pelvic cavities will be explored. Aspects of structure and function as they relate to clinical correlates will be highlighted throughout the course.

• Department: Physical Therapy
• 7 points

VISUAL ART LAB

• Department: Visual Arts
• F 1 p.m.-4 p.m.
• Instructor: Rirkrit Tiravanija
  Wikipedia Info
• 3 points

Ex. In-House Counsel

• Department: Law
• M 4:20 p.m.-6:10 p.m.
• None None-None
• W 4:20 p.m.-6:10 p.m.
• None None-None
• T 4:20 p.m.-6:10 p.m.
• None None-None
• 2 points

Patient Oriented Research Career Develop

POR CAREER DEVELOPMENT CO

The main objective of this course is to provide Columbia University's Clinical & Translational Science award trainees, students, and scholars with skills and knowledge that will optimize their chances of entering into a satisfying academic career. The course will emphasize several methodological and practical issues related to the development of a science career. The course will also offer support and incentives by facilitating timely use of CTSA resources, obtaining expert reviews on writing and curriculum vitae, and providing knowledge and resources for the successful achievement of career goals.

• Department: Biostatistics
• T 3 p.m.-3:50 p.m.
• Instructor: Marisa N Spann
  Info
• 0.5 points

Business Analytics II: Foundations of AI

Business Analytics 2: AI

Business analytics refers to the ways in which enterprises such as businesses, non-profits, and governments use data to gain insights and make better decisions. Business analytics is applied in operations, marketing, finance, and strategic planning among other functions. Modern data collection methods – arising in bioinformatics, mobile platforms, and previously unanalyzable data like text and images – are leading an explosive growth in the volume of data available for decision making. The ability to use data effectively to drive rapid, precise, and profitable decisions has been a critical strategic advantage for companies as diverse as Walmart, Google, Capital One, and Disney. Many startups are based on the application of AI & analytics to large databases. With the increasing availability of broad and deep sources of information – so-called “Big Data” – business analytics are becoming an even more critical capability for enterprises of all types and all sizes. AI is beginning to impact every dimension of business and society. In many industries, you will need to be literate in AI to be a successful business leader. The Business Analytics sequence is designed to prepare you to play an active role in shaping the future of AI and business. You will develop a critical understanding of modern analytics methodology, studying its foundations, potential applications, and – perhaps most importantly – limitations.

• Department: Decision, Risk and Operations
• W 2:20 p.m.-5:35 p.m.
• Instructor: Charles R Guetta
  Info
• 1.5 points

NEUROSCIENCE AND COGNITION

• Department: Rehabilitation Medicine (RMED)
• Instructor: Katherine Dimitropoulou
  Info
• 3 points

Probability

PROBABILITY

The course aims to present the fundamental principles behind probability theory and lay the foundations for various kinds of statistical/biostatistical courses such as statistical inference, multivariate analysis, regression analysis, clinical trials, asymptotics, and so on. Students will learn how to implement probability methods in various types of applications.

• Department: Biostatistics
• MW 10 a.m.-11:20 a.m.
• Instructor: Tian Gu
  Info
• 3 points

Assyrian Art

The seminar will study Assyrian art and architecture of the ninth through the seventh centuries BC, with attention to the primary works of art and monuments, as well as Assyrian art practices, ancient concepts of aesthetics and image ontologies. In the first weeks of the seminar we will also study the history of the reception and collecting of Assyrian art and antiquities in nineteenth century Europe, and more generally, the relationship of European imperialism and the rise of modern scientific archaeology. The main focus of the seminar will be on the ancient works of art and architecture within their own historical context. A reading knowledge of German and French is expected. Permission of the instructor is required. Applications can be submitted to the Department of Art History.

• Department: Art History and Archaeology
• T 4:10 p.m.-6 p.m.
• Instructor: Zainab Bahrani
  CULPA: 11 Wikipedia Info
• 4 points

Data Science I

Contemporary biostatistics and data analysis depends on the mastery of tools for computation, visualization, dissemination, and reproducibility in addition to proficiency in traditional statistical techniques. The goal of this course is to provide training in the elements of a complete pipeline for data analysis. It is targeted to MS, MPH, and PhD students with some data analysis experience.

• Department: Biostatistics
• TR 10 a.m.-11:20 a.m.
• Instructor: Arthur Jeff Goldsmith
  Info
• 3 points

SEM-HISTROCL MUSICLGY-BAROQUE

• Department: Music
• W 10:10 a.m.-noon
• Instructor: Giuseppe Gerbino
  CULPA: 12 Info
• 3 points

Case Based Application

• Department: Rehabilitation Medicine (RMED)
• Instructor: Daniel L Geller
  Info
• 1 points

Introduction to Mathematical Statistics

Intro Mathematical Statis

The first portion of this course provides an introductory-level mathematical treatment of the fundamental principles of probability theory, providing the foundations for statistical inference.  Students will learn how to apply these principles to solve a range of applications.  The second portion of this course provides a mathematical treatment of (a) point estimation, including evaluation of estimators and methods of estimation; (b) interval estimation; and (c) hypothesis testing, including power calculations and likelihood ratio testing.

• Department: Biostatistics
• MW 10 a.m.-11:20 a.m.
• Instructor: Todd Ogden
  Info
• 3 points

Service Operations Management

This course examines both traditional and new approaches for achieving operational competitiveness in service businesses. Major service sectors such as health care, repair / technical support services, banking and financial services, transportation, restaurants, hotels and resorts are examined. The course addresses strategic analysis and operational decision making, with emphasis on the latter. Its content also reflects results of a joint research project with the consulting firm Booz Allen Hamilton, which was initiated in 1996 to investigate next-generation service operations strategy and practices. Topics include the service concept and operations strategy, the design of effective service delivery systems, productivity and quality management, response time (queueing) analysis, capacity planning, yield management and the impact of information technology. This seminar is intended for students interested in consulting, entrepreneurship, venture capital or general management careers that will involve significant analysis of a service firms operations.

• Department: Decision, Risk and Operations
• W 9 a.m.-12:15 p.m.
• W 2:20 p.m.-5:35 p.m.
• R 9 a.m.-12:15 p.m.
• R 2:20 p.m.-5:35 p.m.
• Instructor: Medini Singh
  Info
• 3 points

Capstone One Portfolio

• Department: Rehabilitation Medicine (RMED)
• Instructor: Amanda M Lange
  Info
• 3 points

Survival Analysis

SURVIVAL ANALYSIS

This course focuses on methods for the analysis of survival data, or time-to-event data. Survival analysis is a method for analyzing survival data or failure (death) time data, that is time-to-event data, which arises in a number of applied fields, such as medicine, biology, public health, epidemiology, engineering, economics, and demography. A special course of difficulty in the analysis of survival data is the possibility that some individual may not be observed for the full time to failure. Instead of knowing the failure time t, all we know about these individuals is that their time-to-failure exceeds some value y where y is the follow-up time of these individuals in the study. Students in this class will learn how to make inference for the event times with censored. Topics to be covered include survivor functions and hazard rates, parametric inference, life-table analysis, the Kaplan-Meier estimator, k-sample nonparametric test for the equality of survivor distributions, the proportional hazards regression model, analysis of competing risks and bivariate failure-time data.

• Department: Biostatistics
• F 1 p.m.-3:50 p.m.
• Instructor: Xiao Wu
  Info
• 3 points

Supply Chain Management

Supply chain management entails managing the flow of goods and information through a production or distribution network to ensure that the right goods are delivered to the right place in the right quantity at the right time. Two primary objectives are to gain competitive edge via superior customer service and to reduce costs through efficient procurement, production and delivery systems. Supply chain management encompasses a wide range of activities — from strategic activities, such as capacity expansion or consolidation, make/buy decisions and initiation of supplier contracts, to tactical activities, such as production, procurement and logistics planning, to, finally, operational activities, such as operations scheduling and release decisions, batch sizing and issuing of purchase orders.

• Department: Decision, Risk and Operations
• R 2:20 p.m.-5:35 p.m.
• R 6 p.m.-9:15 p.m.
• Instructor: Will Ma
  Info
• 1.5 points

Applied Regression II

APPLIED REGRESSION II

This course will introduce the statistical methods for analyzing censored data, non-normally distributed response data, and repeated measurements data that are commonly encountered in medical and public health research. Topics include estimation and comparison of survival curves, regression models for survival data, logit models, log-linear models, and generalized estimating equations. Examples are drawn from the health sciences.

• Department: Biostatistics
• R 1 p.m.-3:50 p.m.
• Instructor: Xin Ma
  Info
• 3 points

TV PILOT: COMEDY & DRAMA

With the pilot as a focal point, this course explores the opportunities and challenges of telling and sustaining a serialized story over a protracted period of time with an emphasis on the creation, borne out of character, of the quintessential premise and the ongoing conflict, be it thematic or literal, behind a successful series.

Early in the semester, students may be required to present/pitch their series idea. During the subsequent weeks, students will learn the process of pitching, outlining, and writing a television pilot, that may include story breaking, beat-sheets or story outline, full outlines, and the execution of either a thirty-minute or hour-long teleplay. This seminar may include reading pages and giving notes based on the instructor but may also solely focus on the individual process of the writer.  


Students may only enroll in one TV Writing workshop per semester.

• Department: Film
• M 10 a.m.-1 p.m.
• Instructor: David Klass
  Info
• Instructor: Alice O'Neill
  Info
• Instructor: Carter Bays
  Info
• Instructor: Matthew R Fennell
  Info
• 3 points

SCENE STUDY

SCENE STUDY: DIRECTORS

• Department: Theatre Arts
• F 2:10 p.m.-5 p.m.
• Instructor: Brian Kulick
  Info
• 3 points

Pharmacology for Anesthesia and Critical

PHARM FOR ANES & CRITICAL

This course provides an overview of anesthetics, adjuvants and critical care medications commonly used in anesthesia practice with an emphasis on the application of theoretical foundations as it applies to the patient. Cultural humility will be incorporated when developing medication management individualized to patient identities and cultures while including an emphasis on social and cultural health disparities. The course will also provide a systems approach to pathophysiology and the pharmacotherapeutic agents used to treat specific disease states with an emphasis on their impact in anesthesia practice.

• Department: Nursing
• Instructor: Christian Cansino
  Info
• 4 points

WRITING FOR PUBLICATION

• Department: Rehabilitation Medicine (RMED)
• Instructor: Phyllis R Simon
  Info
• Instructor: Danielle J Mahoney
  Info
• Instructor: Rochelle Mendonca
  Info
• 1 points

Applied Regression Analysis

The goal of this course is to provide students with practical experience in building and analyzing regression models to address business problems.
The course picks up where the core course in Managerial Statistics left off. We will begin with a brief review of regression analysis as covered in the core and then move on to new topics, including model selection, interaction effects, nonlinear effects, classification problems, and forecasting.
All material will be covered through examples, exercises, and cases. In addition, students will work in groups on a final project of their choosing. The goal of the project is to address a specific business problem through statistical analysis.

• Department: Decision, Risk and Operations
• TR 4:10 p.m.-5:40 p.m.
• T 9 a.m.-12:15 p.m.
• Instructor: Paul Glasserman
  Info
• Instructor: David Juran
  Info
• 1.5 points

SEM-NEGOTIATION WORKSHOP

This is a Law School course. For more detailed course information, please go to the Law School Curriculum Guide at: http://www.law.columbia.edu/courses/search

• Department: Law
• R 6:20 p.m.-9:10 p.m.
• 3 points

SEM-NEGOTIATION WORKSHOP

This is a Law School course. For more detailed course information, please go to the Law School Curriculum Guide at: http://www.law.columbia.edu/courses/search

• Department: Law
• R 6:20 p.m.-9:10 p.m.
• F 10 a.m.-1 p.m.
• 3 points

SEM-NEGOTIATION WORKSHOP

This is a Law School course. For more detailed course information, please go to the Law School Curriculum Guide at: http://www.law.columbia.edu/courses/search

• Department: Law
• F 10 a.m.-1 p.m.
• 3 points

SEM-NEGOTIATION WORKSHOP

This is a Law School course. For more detailed course information, please go to the Law School Curriculum Guide at: http://www.law.columbia.edu/courses/search

• Department: Law
• F 10 a.m.-1 p.m.
• 3 points

Applied Exercise Physiology

Applied Physiology

This 13-week course during the first term of the DPT curriculum provides students with a theoretical basis for understanding the body's physiological responses to exercise. Emphasis will be placed upon the practical application of exercise physiology principles in physical therapy practice.

This course is designed to provide an integrative view of human exercise physiology. This class will cover the acute and chronic adaptations to exercise including the cardiovascular, respiratory, neuromuscular and metabolic systems in relation to acute and chronic exercise.

• Department: Physical Therapy
• 2 points

Design of Medical Experiments

DESIGN OF MEDICAL EXPERIM

This course covers the fundamental principles and techniques of experimental designs in clinical studies. This is a required course for MS, DrPH and Ph.D. in Biostatistics. Topics include reliability of measurement, linear regression analysis, parallel groups design, analysis of variance (ANOVA), multiple comparison, blocking, stratification, analysis of covariance (ANCOVA), repeated measures studies; Latin squares design, crossover study, randomized incomplete block design, and factorial design.

• Department: Biostatistics
• M 4 p.m.-6:50 p.m.
• Instructor: Helen Li
  Info
• 3 points

Business Analytics III: Modern AI, Deep

Business Analytics III: A

Business analytics refers to the ways in which enterprises such as businesses, non-profits, and
governments use data to gain insights and make better decisions. Business analytics is applied
in operations, marketing, finance, and strategic planning among other functions. Modern data
collection methods – arising in bioinformatics, mobile platforms, and previously unanalyzable
data like text and images – are leading an explosive growth in the volume of data available for
decision making. The ability to use data effectively to drive rapid, precise, and profitable
decisions has been a critical strategic advantage for companies as diverse as Walmart, Google,
Capital One, and Disney. Many startups are based on the application of AI & analytics to large
databases. With the increasing availability of broad and deep sources of information – so-called
“Big Data” – business analytics are becoming an even more critical capability for enterprises of
all types and all sizes.

• Department: Decision, Risk and Operations
• W 2:20 p.m.-5:35 p.m.
• Instructor: Charles R Guetta
  Info
• 1.5 points

Advanced Statistical and Computational M

ADV STAT/COMPUT MTHD-GEN/

This course introduces students to advanced computational and statistical methods used in the design and analysis of high-dimensional genetic data, an area of critical importance in the current era of BIG DATA. The course starts with a brief background in genetics, followed by in depth discussion of topics in genome-wide linkage and association studies, and next-generation sequencing studies. Additional topics such as network genetics will also be covered. Examples from recent and ongoing applications to complex traits will be used to illustrate methods and concepts. Students are required to read relevant papers as assigned by the instructor, and each student is required to present a paper during class. Students are also required to work on a project related to the course material, with midterm evaluation of the progress.
We will use one main textbook: The fundamentals of Modern Statistical Genetics by Laird and Lange (Springer, 2012). For further reading, an excellent book is also Handbook of Statistical Genetics, Volume 1 (Wiley, 2007). Another good book is Mathematical and Statistical Methods for Genetic Analysis by Ken Lange (Springer 2002).

• Department: Biostatistics
• Instructor: Iuliana Ionita-Laza
  h-index: 31 Info
• 3 points

Analysis of Categorical Data

ANALYSIS OF CATEGORICAL D

A comprehensive overview of methods of analysis for binary and other discrete response data, with applications to epidemiological and clinical studies. It is a second level course that presumes some knowledge of applied statistics and epidemiology. Topics discussed include 2 × 2 tables, m × 2 tables, tests of independence, measures of association, power and sample size determination, stratification and matching in design and analysis, interrater agreement, logistic regression analysis.

• Department: Biostatistics
• TR 6 p.m.-7:20 p.m.
• Instructor: Dacheng Liu
  Info
• 3 points

DIALECTS & ACCENTS

This course continues the actor’s work of experiencing voice and text in a free body as a means to develop versatile and transformative speech.  Students will deepen and refine their knowledge of the phonemes of the International Phonetic Alphabet (IPA), as well as the ability to categorize and utilize Lexical Sets in pursuit of a dialect/accent.  Students will demonstrate their ability to notate texts and transcribe dialects and accents into both IPA and practically apply the framework of the Four Pillars and the Voice Recipe.

The student will use these tools, supplemented by handouts, video & audio resources and independent research, to study several accents/dialects in class as well as at least one additional independently researched accent/dialect. The goal of the class is to expand upon the actor’s choices of speech and vocal expression and to acquaint her/him with the resources necessary to truthfully portray an individual utilizing a dialect/accent on stage or screen.

Students will develop their own unique process for learning accents and dialects
, as well as efficiently and effectively applying their progression to texts via a combination of practice sentences, scene work, conversation, improvisation, cold readings, and a prepared monologue.  Students will complete the course having created a personal, in-depth method for researching and performing a role in which an accent or dialect is required.

Students will do self-directed and supported research as part of their study.  They will consciously and intelligently assimilate this contextual research into their embodiment choices.  The final project is a presentation of their research and the sharing of a monologue that is ideally
written in the student’s selected dialect or accent
.

• Department: Theatre Arts
• W 9 a.m.-12:20 p.m.
• Instructor: Elizabeth Hayes
  Info
• 2 points

PROSEMINAR-GERMAN LITERATURE

PROSEM: DRAMA DER GOETHEZEIT

Proseminar for Graduate Students only.

• Department: Germanic Languages
• M 4:10 p.m.-6 p.m.
• Instructor: Dorothea von Muecke
  Info
• 4 points

Statistical Methods for Causal Inference

Stat Mthds for Causal Inf

Substantive questions in empirical scientific and policy research are often causal. This class will introduce students to both statistical theory and practice of causal inference. As theoretical frameworks, we will discuss potential outcomes, causal graphs, randomization and model-based inference, causal mediation, and sufficient component causes. We will cover various methodological tools including randomized experiments, matching, inverse probability weighting, instrumental variable approaches, dynamic causal models, sensitivity analysis, statistical methods for mediation and interaction. We will analyze the strengths and weaknesses of these methods. The course will draw upon examples from social sciences, public health, and other disciplines. The instructor will illustrate application of the approaches using R/SAS/STATA software. Students will be evaluated and will deepen the understanding of the statistical principles underlying the approaches as well as their application in homework assignments, a take home midterm, and final take home practicum.

• Department: Biostatistics
• TR 10 a.m.-11:20 a.m.
• Instructor: Linda Valeri
  h-index: 24 Info
• 3 points

Analysis of Health Surveys

ANALYSIS OF HLTH SURVEYS

This is an applied statistical methods course. The course will introduce main techniques used in sampling practice, including simple random sampling, stratification, systematic sampling, cluster sampling, probability proportional to size sampling, and multistage sampling. Using national health surveys as examples, the course will introduce and demonstrate the application of statistical methods in analysing across-sectional surveys and repeated and longitudinal surveys, and conducting multiple imputation for missing data in large surveys. Other topics will include methods for variance estimation, weighting, post-stratification, and non-sampling errors. If time allows, new developments in small area estimation and in the era of data science will also be discussed.

• Department: Biostatistics
• W 1 p.m.-3:50 p.m.
• Instructor: Qixuan Chen
  h-index: 27 Info
• 3 points

S. Advising Complex Corporations

S ADVISING COMPLEX CORP

• Department: Law
• T 6:20 p.m.-8:10 p.m.
• 2 points

Intro to Biology Course (T3ST)

test

Test Course for Vergil Launch Demonstration

• Department: OFFC OF THE REGISTRAR
• TR 5 p.m.-6:16 p.m.
• Instructor: Faculty
  h-index: 37 Info
• 0 points

Graphical Models for Complex Health Data

GRAPHICAL MODELS COMPLEX

This is a course at the intersection of statistics and machine learning, focusing on graphical models. In complex systems with many (perhaps hundreds or thousands) of variables, the formalism of graphical models can make representation more compact, inference more tractable, and intelligent data-driven decision-making more feasible. We will focus on representational schemes based on directed and undirected graphical models and discuss statistical inference, prediction, and structure learning. We will emphasize applications of graph-based methods in areas relevant to health: genetics, neuroscience, epidemiology, image analysis, clinical support systems, and more. We will draw connections in lecture between theory and these application areas. The final project will be entirely “hands on,” where students will apply techniques discussed in class to real data and write up the results.

• Department: Biostatistics
• TR 4 p.m.-5:20 p.m.
• Instructor: Daniel S Malinsky
  Info
• 3 points

DIGITAL LITERACY-DECISION MKRS

COURSE DESCRIPTION
Unrelenting technological progress demands entrepreneurs, executives, and managers to continually upgrade their skills in the pursuit of emerging opportunities. As “software eats the world”, executives from all industries are increasingly called upon to be “Full Stack”: capable of making competent decisions across domains as diverse as digital technology, design, product, and marketing.
In this course, we begin with primers on code, design, and product management. Once the foundation is laid, we examine the best practices for building great products and exceptional teams. We conclude with an overview of how technology is changing the way products are marketed, distributed, and monetized. Our goal is to equip “non-technical” executives with the terminology, tools, and context required to effect change in a software­ and internet-driven world.
COURSE LEARNING OBJECTIVES
To provide an understanding of the technologies that we encounter everyday, and how history can inform the technology decisions executives face today.
To become familiar the concepts that underpin modern computer programming, empowering managers to engage with engineers credibly and confidently.
To shed light on the processes and tools designers use to solve user-facing design and architecture challenges.
To clarify what product managers do, walk through the nitty-gritty of managing software development, and equip executives with the best practices for evaluating and improving their products.
To prepare managers to identify, recruit, and nurture the technical talent they will need to succeed in today’s highly competitive labor market.
To familiarize students with the dynamic context in which technology products live, ensuring the profitable and widespread delivery of those products.

• Department: Decision, Risk and Operations
• T 9 a.m.-12:15 p.m.
• Instructor: Marco A Morales Barba
  Info
• 1.5 points

Kinesiology & Biomechanics I

This 16-week course during the first term of the DPT curriculum is the first of a 2-part series. This is a comprehensive lecture/laboratory course in the first semester of the DPT curriculum, which establishes foundational knowledge of normal human movement and an introduction to aberrant human movement. Fundamental biomechanical and kinesiological principles, including kinematics and kinetics, of human movement are integrated with knowledge of anatomical structures under normal and pathological conditions. Each joint complex of the human body is scrutinized and integrated with a regional interdependence approach to human movement.

This course begins with an introduction to the biomechanical properties of connective tissue and muscle mechanics, followed by a discussion of the integral principles of biomechanics (i.e., gravity, friction, leverage, composition, and resolution of internal and external forces in producing movement). These topics are integrated throughout the kinesiology analyses of the human body, organized by anatomical region. Specific attention will be given to the relationship between anatomical structure and kinesiological function, joint classification, osteokinematics, arthrokinematics, muscle and ligament function, kinematic chains, and alignment. There is an emphasis on kinematics and muscle function in normal functional movements, while pathological movement is introduced. The laboratory component highlights surface anatomy palpation with emphasis on structure identification, positioning, body mechanics and hand placement. Additionally, the laboratory component will emphasize the identification of osteokinematics, arthrokinematics, and muscle actions during simple and multiple-joint movement assessments. Both lecture and laboratory incorporate observation and analysis of normal movement of the limbs and trunk, utilizing patient-specific case studies and selected examples. Optional open lab and lecture review sessions are small group review sessions and/or case discussions, organized by 3rd year DPT teaching practicum students. First year DPT students, who wish to attend, may utilize this time to review their lab/lecture material with their peers and 3rd year DPT students, while asking questions pertaining to the course material.

• Department: Physical Therapy
• 4 points

Introduction to Psychedelics in Clinical

INTRO TO PSYCHEDELICS IN

Though psychedelic plants and compounds have been used in a wide-spectrum of healing practices throughout human history, they have quickly been gaining recognition and acceptance in conventional western healthcare in recent years, along with a growing interest in underground, international, and ceremonial plant medicine work. This course is designed to provide foundational knowledge of contemporary psychedelic healing and integration practices, as is relevant to medical management of patients seeking psychedelic treatment, in order to prepare students for prescription of legal medications into their practices.

• Department: Nursing
• M 5:30 p.m.-8:20 p.m.
• Instructor: Ronica Mukerjee
  Info
• 3 points

Biostatistical Methods I

BIOSTATISTICAL METHODS I

This one-semester course introduces basic applied descriptive and inferential statistics. The first part of the course includes elementary probability theory, an introduction to statistical distributions, principles of estimation and hypothesis testing, methods for comparison of discrete and continuous data including chi-squared test of independence, t-test, analysis of variance (ANOVA), and their non-parametric equivalents. The second part of the course focuses on linear models (regression) theory and their practical implementation.

• Department: Biostatistics
• F 1 p.m.-3:50 p.m.
• Instructor: Molei Liu
  Info
• 3 points

Acute and Critical Care Pharmacology

ACUTE & CRIT CARE PHARMAC

The purpose of this course is to provide a comprehensive and in-depth background in acute and critical care pharmacotherapy. This course will address the pharmacology and appropriate clinical use of agents used in the treatment of selected acute disorders found in acutely/critically ill patients. Recent advances in pharmacotherapy, personalized management strategies, and controversial issues will be included and emphasized.

• Department: Nursing
• M 5 p.m.-6:50 p.m.
• Instructor: Jenny Shah
  Info
• 3 points

ACTING III

MFA acting students will tackle verse drama and heightened language. We will spend much of our time investigating Shakespeare’s writing, with a focus on King Lear and Much Ado about Nothing, and will weave in contemporary heightened language texts throughout the semester. 

Goals



To develop students into keen interpreters of heightened theatrical language, both classical and contemporary



To enable students to express their instinctive emotional responses to the rhythms, sounds and the mysteries contained in great language texts



To bring character and the specific imaginative world of each play alive thru the language



To foster each actor’s unique voice

• Department: Theatre Arts
• F 9:30 a.m.-12:20 p.m.
• Instructor: Peter Fernandez
  Wikipedia Info
• 3 points

Sports Analytics

Sports analytics refers to the use of data and quantitative methods to measure performance and make decisions to gain advantage in the competitive sports arena. This course builds on the Business Analytics core course and is designed to help students to develop and apply analytical skills that are useful in business, using sports as the application area. These skills include critical thinking, mathematical modeling, statistical analysis, predictive analytics, game theory, optimization and simulation. These skills will be applied to sports in this course, but are equally useful in many areas of business.There will be three main topics in the course: (1) measuring and predicting player and team performance, (2) decision-making and strategy in sports, and (3) fantasy sports and sports betting. Typical questions addressed in sports analytics include: How to rank players or teams? How to predict future performance of players or teams? How much is a player on a team worth? How likely are extreme performances, i.e., streaks? Are there hot-hands in sports performances? Which decision is more likely to lead to a win (e.g., attempt a stolen base or not in baseball, punt or go for it on fourth down in football, dump and chase or not in hockey, pull the goalie or not in hockey)? How to form lineups in daily fantasy sports? How to manage money in sports betting? How to analyze various ``prop'' bets?The main sports discussed in the course will be baseball, football, basketball, hockey, and golf. Soccer, tennis, and other sports will be briefly discussed.
Students are welcome to pursue any sport in more detail (e.g., cricket, rugby, auto racing, horse racing, Australian rules football, skiiing, track and field, or even card games such as blackjack, poker, etc.) in a project. Class sessions will involve a mixture of current events, lecture, discussion, and hands-on analysis with computers in class. Each session will typically address a question from a sport using an important analytical idea (e.g., mean reversion) together with a mathematical technique (e.g., regression). Because of the "laboratory" nature of part of the sessions, students should bring their laptops to each class.

• Department: Decision, Risk and Operations
• T 2:20 p.m.-5:35 p.m.
• Instructor: Mark N Broadie
  Info
• 3 points