ADVANCED TOPICS IN IEOR
Advanced Combinatorial Op
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.
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Instructor:
Yuri Faenza
h-index: 11 Info - 3 points
ADVANCED TOPICS IN IEOR
Computational Methods RL
Selected topics in IEOR. Content varies from year to year. May be repeated for credit.
- Department: Industrial Engineering and Operations Research
- T 10:10 a.m.-12:40 p.m.
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Instructor:
Anran Hu
Info - 3 points
ADVANCED TOPICS IN IEOR
Topics in Network Games
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.
- 3 points
ADVANCED TOPICS IN IEOR
Fast Algorithms Linear Pr
Selected topics in IEOR. Content varies from year to year. May be repeated for credit.
- Department: Industrial Engineering and Operations Research
- MW 1:10 p.m.-2:25 p.m.
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Instructor:
Bento Natura
Info - 3 points
ADVANCED TOPICS IN IEOR
GenAI: Model Alignment
Selected topics in IEOR. Content varies from year to year. May be repeated for credit.
- Department: Industrial Engineering and Operations Research
- MW 2:40 p.m.-3:55 p.m.
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Instructor:
Wenpin Tang
h-index: 6 Info - 3 points
ADVANCED TOPICS IN IEOR
Simulation & Monte Carlo
Selected topics in IEOR. Content varies from year to year. May be repeated for credit.
- Department: Industrial Engineering and Operations Research
- MW 4:10 p.m.-5:25 p.m.
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Instructor:
Antonius B Dieker
CULPA: 10 h-index: 19 Info - 3 points
FICTION THESIS WORKSHOP
- Department: Writing
- W 2 p.m.-5 p.m.
- R 1:10 p.m.-4:10 p.m.
- T 4:15 p.m.-7:15 p.m.
- W 2 p.m.-5 p.m.
- M 1:10 p.m.-4:10 p.m.
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Instructor:
Paul Beatty
Wikipedia Info -
Instructor:
Anelise I Chen
Info -
Instructor:
Joshua Furst
Wikipedia Info -
Instructor:
Heidi S Julavits
CULPA: 1 Wikipedia Info -
Instructor:
Victor D Lavalle
CULPA: 2 Wikipedia Info -
Instructor:
Samuel Lipsyte
CULPA: 5
Info
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Instructor:
Benjamin Marcus
Info - 9 points
Introduction to Health Data Science
Intro to Health Data Scie
This course will introduce students to core data science skills and concepts through the exploration of applied biostatistics. The course will begin with an introduction to the R programming language and the RStudio IDE, focusing on contemporary tidyverse functions and reproducible programming methods. Then, the course will instruct students in contemporary data manipulation and visualization tools while systematically covering core applied biostatistics topics, including confidence intervals, hypothesis testing, permutation tests, and logistic and linear regression. Finally, the semester will end with an introduction to machine learning concepts, including terminology, best practices in test/training sets, cross-validation, and a survey of contemporary classification and regression algorithms.
- Department: Biostatistics
- MW 4 p.m.-5:20 p.m.
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Instructor:
Cale N Basaraba
Info - 3 points
SEM-HISTORCL MUSICLGY-MID AGES
- Department: Music
- F 10 a.m.-1 p.m.
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Instructor:
Susan Boynton
CULPA: 18 Info - 3 points
TOPICS IN APPLIED STATISTICS
Design & Analysis of Comp
.
- Department: Statistics
- M 10:10 a.m.-noon
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Instructor:
Christopher Harshaw
Info - 3 points
Process Improvement and Growth
This class brings business operations and management science classes to the field with real-world experience. Through experiential learning, we will bridge the gap between theory and practice with international case discussions, conversations with guest speakers and hands-on company sponsored projects. Different to most classes in the school, in this class students will be exposed to a series of international cases and examples based on medium-sized, fast-growing entrepreneurial ventures. Each session will also include a guest speaker, often times the protagonist of the case studied, giving the students the opportunity to learn directly from successful entrepreneurs and senior executives.
Additionally, students will put into practice the concept of process improvement by working on a company-sponsored applied project. Teams of 4-5 people, 3-4 MBA/EMBA students and 1-2 engineering (SEAS) students, will work hand in hand with the instructors and company representatives to achieve company goals. For example, teams may be tasked with re-designing the logistical strategy of distribution of the company to get rid of inefficiencies, or identify and find strategies to eliminate areas of waste within the companies’ processes, or analyze customer feedback and design operational solutions to increase customer satisfaction, etc.
Enrollment in this course is by application only. To apply, please follow this link: https://forms.gle/EG6buNZqQYEgN2EH9
- Department: Decision, Risk and Operations
- T 6 p.m.-9:15 p.m.
- 3 points
ANTICOLONIAL AND POSTCOLONIAL POLITICAL
ANTICOL & POSTCOL POL THO
This seminar explores key texts of twentieth-century anticolonial political thought and its postcolonial interpretation. It is an advanced course in political theory for graduate students. Over the last twenty years, postcolonial approaches to political theory have challenged many of the traditional categories and assumptions of western political thought. Some contend that theories inherited from Western social and political thought cannot adequately speak to the political experiences of the non-Western world. Others have been sharply critical of the complicity of Western political thought and modern practices of imperialism, slavery, and global inequality. This seminar aims to investigate the various challenges that postcolonial theorists pose to political theory and to offer critical assessments of the possibilities and limitations of this perspective. We will do so by reading key anticolonial texts alongside major postcolonial interpretations of these texts. We will compare how anticolonial texts and their postcolonial interpreters engage with questions of political theory – such as the relationship between universality and freedom, revolution and history, violence and power, progress and emancipation – in light of the legacy of colonialism and the promise of decolonization.
- Department: Political Science
- R 10:10 a.m.-noon
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Instructor:
Karuna Mantena
CULPA: 3
Info
- 4 points
VISUAL ART LAB, SPRING
VISUAL ART LAB SPRING
Students meet with the professor and pave the transition from graduate students to seeing themselves as artists with a long term working creative perspective beyond academia. The professor will work to contextualize the students body of work in the arena of an international art conversation. VISUAL ART LAB will be led by Sarah Sze in the Spring.
Schedule:
Priority will be given to all second-year students who submit a short presentation of their work. Should there be remaining room for first year students they will be admitted upon review. To apply please submit a brief description of work, current research and interest in taking the seminar, along with 5 - 10 images. There will be one half hour meeting for each student with professor Sze throughout the Spring Semester.
Requirements:
Rigorous development of students' own body of work.
- Department: Visual Arts
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Instructor:
Sarah M Sze
CULPA: 1 Wikipedia Info - 3 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.
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Instructor:
Marisa N Spann
Info - 0.5 points
Business Analytics II: Foundations of AI
Business Analytics II: 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
- M 2:20 p.m.-5:35 p.m.
- T 9 a.m.-12:15 p.m.
- T 2:20 p.m.-5:35 p.m.
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Instructor:
Hongseok Namkoong
h-index: 11 Info - 1.5 points
Neuroscience
This intensive 16-week course during the second term of the DPT curriculum provides students with detailed coverage of neuroscience. The focus of the course is on the integral relationship between structure and function, as it relates to the neural basis for perception, movement, behavior, and cognition. A comprehensive understanding of normal structure and function provides the foundation for understanding abnormal structure and function.
This course uses a primarily systems approach to study neuroscience. The first part of the course covers essential concepts, such as neurobiology, neurohistology, neurophysiology, neurodevelopment, and neuroanatomy. The second part of the course covers perception. The third part of the course covers movement. The fourth part of the course covers homeostasis, behavior, cognition, and alterations (i.e. healing and aging). Functional consequences of lesions to various parts of the nervous system will be discussed.
- Department: Physical Therapy
- 4 points
Data Science II
DATA SCIENCE II
With the explosion of “Big Data” problems, statistical learning has become a very hot field in many scientific areas. The goal of this course is to provide the training in practical statistical learning. It is targeted to MS students with some data analysis experience.
- Department: Biostatistics
- TR 4 p.m.-5:20 p.m.
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Instructor:
Yifei Sun
h-index: 7 Info - 3 points
Operations Strategy
A firm's operations encompass all the activities that are performed in order to produce and deliver a product or a service. An operations strategy refers to a set of operational decisions that a firm makes to achieve a long-term competitive advantage. These decisions may be about the firms facilities, its technology/process choices, its relationships with both upstream and downstream business partners etc. The goal of this course is to provide students with an understanding of how and why operational decisions are integral to a firms success. The course builds on concepts from the core Operations Management course and the core Strategy Formulation course. It is highly relevant to anyone whose work requires the strategic analysis of a firms operations, including those interested in consulting, entrepreneurship, mergers and acquisitions, private equity, investment analysis, and general management. The course consists of four modules. The first module, Strategic Alignment," explores the question of how a firms operations should be structured so as to be consistent with the firms chosen way to compete. The second module, "Firm Boundaries," considers the question of what operational activities should remain in house and what should be done by a business partner and the long-term implications of these decisions on competitive advantage. This module also addresses the issue of managing the business relationships with supply chain partners. The third module, "Internal Operations," considers key decision categories in operations, e.g., capacity decisions, process choices, IT implementation, and managing networks, and shows how these decisions can lead to distinctive capabilities. The final module, "New Challenges," is set aside to address new topics that reflect the current trends in the business environment."
- Department: Decision, Risk and Operations
- M 2:20 p.m.-5:35 p.m.
- T 9 a.m.-12:15 p.m.
- T 2:20 p.m.-5:35 p.m.
- 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.
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Instructor:
Medini Singh
Info - 3 points
Case Based Application
- Department: Rehabilitation Medicine (RMED)
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Instructor:
Colleen M Maher
Info -
Instructor:
Phyllis R Simon
Info -
Instructor:
Razan Hamed
h-index: 8 Info -
Instructor:
Tyra M Banks
Info -
Instructor:
Katherine Dimitropoulou
Info -
Instructor:
Michael Urban
Info -
Instructor:
Julia Guzman
Info -
Instructor:
Daniel L Geller
Info -
Instructor:
Glen Gillen
Info - 1 points
SEM-HISTORCL MUSICLGY-CLASSIC
SEM IN HIST MUSIC:OPERATIC DEC
Topic to be announced.
- Department: Music
- R 12:10 p.m.-2 p.m.
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Instructor:
Elaine Sisman
CULPA: 13
Wikipedia
Info
- 3 points
Statistical Inference
STATISTICAL INFERENCE
This course covers a review of mathematical statistics and probability theory at the Masters level. Students will be exposed to theory of estimation and hypothesis testing, confidence intervals and Bayesian inference. Topics include population parameters, sufficient statistics, basic distribution theory, point and interval estimation, introduction to the theory of hypothesis testing, and nonparametric procedures.
- Department: Biostatistics
- M 1 p.m.-3:50 p.m.
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Instructor:
Prakash Gorroochurn
Info - 3 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.
Game-Theoretic Business Strategy
GAME-THEORETIC BUSINESS S
This course is an introductory business-strategy course designed for analytically-oriented graduate students, particularly students in the joint Business School-IEOR programs. The course has three objectives.:
1 - Provide you with the economic theory to understand why a given company is (or is not) profitable. (For potential entrepreneurs, this theory becomes a tool to assess whether your proposed venture will be profitable in a competitive environment.)
2 - Provide you with perspectives for assessing the sustainability of a given company’s profitability. We will place special emphasis on understanding and evaluating the key assumptions and judgments underpinning your assessments. The course includes historical cases of managing a changing business environment.
3 - Enable you to identify the substantive issues behind the trends and frameworks in the strategy field.
- Department: Decision, Risk and Operations
- R 9 a.m.-12:15 p.m.
- R 2:20 p.m.-5:35 p.m.
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Instructor:
Harborne Stuart
h-index: 10 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.
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Instructor:
Alice O'Neill
Info -
Instructor:
Blair Singer
Info - 3 points
SCENE STUDY
SELF TO PERFORMANCE
- Department: Theatre Arts
- F 10 a.m.-12:50 p.m.
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Instructor:
Peter Fernandez
Wikipedia Info - 3 points
Medical Screening I
Pathology continues the scientific foundation thread in the PT curriculum. The course is designed to assist students in understanding how a disease or conditions, especially changes in body tissues and organs that cause disease, might affect an individual’s functional abilities and limitations.
Pathology is a detailed study of select systemic and tissue-specific diseases and disorders. The epidemiology, etiology, pathogenesis, clinical manifestations, and management of each condition are explored. Implications for physical therapists are highlighted throughout the course specific to the medical screening process.
- Department: Physical Therapy
- 2 points
WRITING FOR PUBLICATION
- Department: Rehabilitation Medicine (RMED)
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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
- T 9 a.m.-12:15 p.m.
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Instructor:
David Juran
Info - 1.5 points
Leading Sustainable Supply Chains and Op
Leading Sust Supply Chain
The importance of designing, building, and leading sustainable organizations is indisputable. Sustainability encompasses not only the environmental footprint of an organization but also the way in which firms treat workers and customers both within their firm and supply chain network. Understanding the role of operational excellence and strategic supply chain management in achieving sustainability is critical for effective leadership.
This course examines a variety of approaches to designing sustainability into an organization’s operations and how to measure and reduce a firm’s operational environmental impact. We also explore themes of risk, accountability, and sustainability within global supply chains. What challenges do firms face in being socially responsible when managing globally distributed supply chains? Three themes comprise this course: (1) designing sustainable operations, (2) drivers and consequences of sustainability, and (3) global sourcing and social responsibility.
• Designing Sustainable Operations. Sample cases include – REI Rentals, All Birds, IndigoAg, Supply Chain Hubs in Humanitarian Logistics.
• Drivers and Consequences of Sustainability. Sample cases include – Fiji Water, Aspen Ski Company.
• Global Sourcing & Social Responsibility. Sample cases include – IKEA, Ready Made Garment Industry, Roche & Tamiflu.
- Department: Decision, Risk and Operations
- M 9 a.m.-12:15 p.m.
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Instructor:
Nicole Dehoratius
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
- T 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
- T 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
- T 6:20 p.m.-9:10 p.m.
- 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
Risk Management
- Department: Decision, Risk and Operations
- MW 6 p.m.-7:30 p.m.
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Instructor:
Evan C Picoult
Info - 3 points
S ADV NEGIATION WORKSHOP
course decription
- Department: Law
- W 6:20 p.m.-9:10 p.m.
- 3 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
- F 1 p.m.-3:50 p.m.
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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
- MR 4 p.m.-5:20 p.m.
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Instructor:
Kay See Tan
Info - 3 points
Accounting for Consultants
This elective course covers accounting tools useful to consultants, as well as for students with an interest in a firm’s finance function, general management, or private equity.
There will be a particular focus on performance measurement and management.
Performance measurement is a key determinant of success for today’s companies that sell a wide range of products and services to a wide range of customers differentiated in their needs. While financial accounting (GAAP) information is a useful shortcut toward gaining some understanding of a firm’s financial health, consultants and managers need a more solid understanding of the firm’s strategy and mission, as well as disaggregated information that helps assess how the firm is performing along its strategic objectives.
There is overlap between this course and the half-semester course “Financial Planning & Analysis (FP&A)” course. This course expands on many of the concepts taught in FP&A and supplements them with industry insights and guest speakers. For this reason, this course is mutually exclusive with the elective course “B8007 – Financial Planning & Analysis”. If you have taken FP&A, you will not be able to enroll in this course for credit. Please contact me immediately in case of such a conflict.
The following specific topics will be addressed:
• Profitability analysis to assess individual products
• Customer relationship management using customer lifetime value (CLV)
• Budgeting and variances
• Performance evaluation for profit centers and investment centers
• Performance-based pay: team incentives, relative performance evaluation, etc.
• Corporate governance: the C-suite and the role of compensation consultants
• The “War of Metrics”: Cash Flow, EVA, Balanced Scorecards, etc.
• Innovative ways to deviate from GAAP rules to better measure value creation
• Issues specific to multinational enterprises (MNEs), e.g., taxation
• Industry-specific insights: performance measurement in key industries
- Department: Accounting (ACCT)
- MW 9 a.m.-12:15 p.m.
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Instructor:
Tim Baldenius
Info - 3 points
S. Latino/as and Civil Rights Law
S. Latino/as & Civ Rights
- Department: Law
- W 4:20 p.m.-6:10 p.m.
- 2 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.
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Instructor:
Marco A Morales Barba
Info - 1.5 points
Programming Generative AI Applications
Generative Artificial Intelligence is a type of AI that learns patterns from data to create new content in various types of media (text, images, audio, video). At its heart a generative AI system has a large language model (LLM) that is essentially a large (trillions of parameters) neural network that has been trained on a mix of vast amounts of data as well as human input. Applying generative AI to actual problems in business often requires that the LLM underlying the AI be customized to the business problem, either by attaching a data source (e.g., operating procedures, 10k reports, marketing plans, balance sheets, etc.) to the LLM (a process known as Retrieval-Augmented Generation or RAG) or by retraining the neural net with additional data (a process known as fine tuning). adjusting the parameters of the underlying LLM. Embedding generative AI into organizational processes requires
that we gather appropriate data and reprogram the LLM to use the data either through RAG or fine tuning.
The focus of this course is to give you a working knowledge of what it takes to customize and assemble a customized generative AI application. We will use OpenAI’s GPT as our base model and learn how to build a RAG and how to customize using simple fine tuning. About 50% of the class time will be devoted to a group project where you will, in small groups, build your own customized AI application. All programming will be in Python and we will use libraries like tensorflow, langchain and faiss.
STUDENTS WILL NEED TO COMPLETE AN INTRODUCTORY PYTHON CLASS (https://courseworks2.columbia.edu/courses/152704) OR PASS THE BASIC PYTHON QUALIFICATION EXAM (https://cbs-python.com/) BEFORE THE FIRST DAY OF CLASS. SEE https://academics.gsb.columbia.edu/python FOR DETAILS
- Department: Decision, Risk and Operations
- TWRFS 9 a.m.-5 p.m.
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Instructor:
Hardeep Johar
Info - 3 points
Kinesiology & Biomechanics II
This 16-week course during the second term of the DPT curriculum is the second in a series of Kinesiology and Biomechanics courses. The study of human motion is continued in greater depth with not only biomechanics but also pathomechanics and introductory gait analysis. Although this course is part of the foundational sciences, students will begin to integrate the course materials with clinical cases scenarios.
This course is the second in a series of two Kinesiology and Biomechanics courses. The two courses are offered in the first two semesters of the Doctor of Physical Therapy program. This course has three portions. The first portion covers biomechanical principles, movement analysis, as well as biomechanics and pathomechanics of body movements and functional activities. The second portion introduces normal gait including its kinematics and kinetics. The third portion emphasizes on observational gait analysis and introduces students to pathological gait. The introductory gait analysis this course offers will serve as a foundation for continued gait analysis activities in courses such as Movement Science, Prosthetics, Orthotics, Orthopedics, Pediatrics, Geriatrics and Neurology. An in-depth study of pathological gait is beyond the scope of this course.
- Department: Physical Therapy
- 3 points
Healthcare Venture Capital And Private E
Healthcare Venture Cap &
This course analyzes the unique characteristics and strategies of investing in the healthcare sector from the perspectives of venture capital firms investing in early-stage healthcare enterprises, entrepreneurs creating and managing such business entities, and private equity firms seeking to build value-creating health care platforms. The course is focused on innovative business models of early to mid-stage healthcare services companies (payers, providers, HCIT firms) that improve quality of patient care, lower costs, and facilitate access to such services, as well as the opportunities and challenges of early-stage biotechnology companies discovering and developing novel compounds. It considers how investors and entrepreneurs can assess, value and manage the inherent risks to succeed in this large, complex, and dynamic sector. This course will address these issues through a mixture of lectures, case studies, and guest speakers (investors and entrepreneurs) from the healthcare sector. Note: Some understanding and prior experience in the healthcare/pharma industry will be highly useful. Students need to attend the first class session to understand material covered later in the course. Evaluation is 25% class participation, 25% mid-term assignment (short paper on questions or case study), and 50% final (individual) paper. "
- Department: Decision, Risk and Operations
- M 2:20 p.m.-5:35 p.m.
- 1.5 points
Movement Science
This course adds to the basic science curriculum while beginning the process of translation to clinical practice. Psychological literature of skill acquisition is integrated with neuroscience and biomechanics literature of motor control. Beginning application to clinical practice is emphasized.
Conceptual framework of movement science, including normal motor control, and skill acquisition will be formulated. Principles of motor control, including neurophysiological, biomechanical and behavioral levels of analysis are discussed. An analysis of postural control, basic mobility tasks (bed mobility, transfers & locomotion) and reach and grasp will be conducted. Principles of motor learning, including learning and practice variables are analyzed.
- Department: Physical Therapy
- 2 points
Biostatistical Methods II
BIOSTATISTICAL METHODS II
Regression analysis is widely used in biomedical research. Non-continuous (e.g., binary or count-valued) responses, correlated observations, and censored data are frequently encountered in regression analysis. This course will introduce advanced statistical methods to address these practical problems. Topics include generalized linear models (GLM) for non-Gaussian response, mixed-effects models and generalized estimating equations (GEE) for correlated observations, and Cox proportional hazards models for survival data analysis. Examples are drawn from biomedical sciences.
- Department: Biostatistics
- TR 10 a.m.-11:20 a.m.
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Instructor:
Wenpin Hou
Info - 3 points
Sumerian Sculpture
This seminar introduces the sculpture of ancient Sumer (south Iraq), with a focus on ancient practices and ontologies of art, the related processes of making and technological innovations, as well as image rituals and the visual manifestation of the divine. Seminar topics include historical monuments, statues of the gods, architectural sculpture and foundation images placed in the ground, and votive portrait statues dedicated in temples. In the fourth millennium BC new technologies of metallurgy, casting, the mechanical reproduction of images, and seal carvings emerged alongside the invention of writing, a technology first documented in the city-state of Uruk, Iraq. Sculpted images and monuments were inscribed with texts that reveal a great deal about the ontological and agentive, the aesthetic and the order of the divine. The seminar will study the genres of Sumerian sculpture alongside their ancient texts. It also explores an important era in the historiography of ancient art and archaeology in the first half of the twentieth century. At the time when Sumerian sculpture was first unearthed and collected, antiquity and ethnography, ruins and ancient statues became subjects of interest for Modern artists and art movements, not only for their aesthetic forms but also as areas of scholarly investigation. Archaeologies of ritual and the sacred, Sumerian and Pre- Columbian antiquity, were topics of great interest in the first half of the twentieth century, among European artists and art movements, but also for Iraqi Modernist groups such as the Baghdad Group of Modern Art and the Ruwad.
Prerequisites: Students will be expected to have previous coursework in art history, archaeology or anthropology. Reading knowledge of French preferred. Applications required. Permission of the instructor is needed for registration.
- Department: Art History and Archaeology
- R 4:10 p.m.-6 p.m.
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Instructor:
Zainab Bahrani
CULPA: 11
Wikipedia
Info
- 4 points
Industryscapes: Socio-natural Sites of R
Industryscapes - Preindus
From about 1400, Europe saw very rapid expansion of industries such as shipbuilding, mining, wood extraction and transport. These industries have mainly been studied by economic and technology historians along a short timeline of boom, outputs, and decline. In contrast, this course aims to introduce and investigate natural, social, cultural, and material ecologies of these industries over the long term to track change over time in relationships between humans and the environment. The course will introduce students to the concepts and methods of describing and analyzing socio-natural sites, to recent research and conceptualization of “extraction,” “resource,” and consider attitudes to the natural world foreclosed by European colonial extraction.
- Department: History
- W 10:10 a.m.-noon
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Instructor:
Pamela Smith
CULPA: 4 Info - 4 points
Intro to Databases for Busines
We don’t think about databases much, right? At least not when they’re working right. But they’re all around us. They’re in every product we use. And when they don’t work (think about the iCloud, LinkedIn, or Ashley Madison data breaches in which hundreds of millions of emails and passwords were exposed) the consequences can be extreme.
Every modern company stores their data in a database (it’s like a really big version of Excel), and if you want to analyze the data, you may be expected to know how to access it yourself. In fact, at many companies are requiring even their business leaders to have an understanding of databases. At the very least, knowing how to set up and interact with databases will improve your ability to GSD (get stuff done), strengthen your understanding of how technology works, and make you less of a pain for developers to work with.
In this class, we’ll explore basic SQL (the most common database language) for business analytics. At the end of the course, students should have a deeper understanding of how databases work, how they fit into the general technology stack, how to connect to databases, and know how to browse and exporting data from databases.
- Department: Decision, Risk and Operations
- R 6 p.m.-7:30 p.m.
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Instructor:
Mattan Griffel
Info - 1.5 points
Statistical Genetic Modeling
STATISTICAL GENETIC MODEL
This course explores the theoretical foundations underlying the models and techniques used in mathematical genetics and genetic epidemiology. Topics include use and interpretation of likelihood methods, formulation of mathematical models, segregation analysis, ascertainment bias, linkage analysis, genetic heterogeneity, and complex genetic models. The course includes lectures, discussions, homework problems, and a final exam. My single most important objective for this course is for students to be able to break down any mathematical modeling problem logically into all its component parts, to express each part" accurately, and to know how to "add" all the pieces back up and to check the accuracy of their result."
- Department: Biostatistics
- T 1 p.m.-3:50 p.m.
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Instructor:
Shuang Wang
Info - 3 points
Data Analytics in Python
The collection, interpretation, and analysis of data has always been a central pillar of business decision making. Historically, this has followed a two step process, statisticians gather data, organize it, run analytics and prepare reports. At some future point, a decision maker examines these reports, interprets the results and makes decisions. However, with the advent of powerful and inexpensive computing platforms, the collection and analysis of data has moved into the continuous decision making cycle itself, with decisions being constantly updated as new data is instantly analyzed and acted upon. Consequently, decision makers can no longer isolate themselves from the grungy side of data and they need to know where the data originated, how it was transformed, what is the nature, the strengths and the limitations of the analytical techniques used. Today, to be effective, decision makers need an intuitive understanding of the statistics, the math, and the programming that underlie this “live” analytical and decision making process.
The objective of this course is to give you an understanding of the analytical side of the decision making cycle, focusing on programming as the element that “glues” the collection, transformation, visualization, and analysis of data. We will see how to get data from common sources (APIs, web scraping), examine the rudiments of data visualization (charts, maps), and get an intuitive understanding of the types of analytical tools in use today (machine learning, deep learning, analysis of networks, analyzing natural language texts).
With its extensive collection of libraries, Python is fast becoming the platform of choice for data analytics so Python will be our language for this course. The course is very hands on, and you should expect a lot of programming work, all of it fairly intense. A basic understanding of how to write programs in Python is therefore a must for this class. But, the primary takeaway from the course is not the programming but rather an understanding of the mechanics, the vocabulary, and the techniques in data analytics. Even if you find programming a frustrating and head banging exercise, you can get a lot out of the class (if you’re willing to suffer a bit!).
STUDENTS WILL NEED TO EITHER HAVE PASSED B8154 (PYTHON FOR MBAS) OR THE ADVANCED PYTHON QUALIFICATION EXAM (https://www8.gsb.columbia.edu/courses/python#advanced_qual) BEFORE THE FIRST DAY OF CLASS
- Department: Decision, Risk and Operations
- W 2:20 p.m.-5:35 p.m.
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Instructor:
Hardeep Johar
Info - 3 points
Introduction to Randomized Clinical Tria
INTRO TO RAND CLINICAL TR
Students in this course will learn and practice the fundamental methods and concepts of the randomized clinical trial: protocol development, randomization, blindedness, patient recruitment, informed consent, compliance, sample size determination, crossovers, collaborative trials. Each student prepares and submits the protocol for a real or hypothetical clinical trial.
- Department: Biostatistics
- W 1 p.m.-3:50 p.m.
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Instructor:
John L Thompson
h-index: 61 Info - 3 points
ACTING IV
TBD
- Department: Theatre Arts
- MT 2:10 p.m.-5 p.m.
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Instructor:
Peter Fernandez
Wikipedia Info - 3 points
Foundations of AI for Business
- Department: Decision, Risk and Operations
- M 9 a.m.-12:15 p.m.
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Instructor:
Hongseok Namkoong
h-index: 11 Info - 1.5 points
Pharmaceutical Statistics
PHARMACEUTICAL STATISTICS
The drug development from compound discovery to marketing and commercialization registration is a lengthy and complex process in which statisticians play an important role from the beginning to the end. The main objective of this course is to provide students with working knowledge of methodological and operational issues that arise in different stages of the drug development that involve statistical contributions.
Topics include: Introduction of drug development; design and analysis of non-clinical studies (toxicology, pharmacokinetics and pharmacodynamics) and Phase I/II/III studies; issues in clinical studies including non-inferiority, meta-analysis, and endpoint selection; overview of safety reporting systems such as MedDRA (Medical Dictionary for Regulatory Activities), CTC version 3 (Common Terminology Criteria for Adverse Events), and preparation for the FDA advisory committee drug approval process. In addition, the views and positions of different regulatory bodies, such as the FDA or EMEA, on design and analysis issues will be discussed.
- Department: Biostatistics
- T 2:30 p.m.-5:20 p.m.
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Instructor:
Naitee Ting
Info - 3 points
Applying Healthcare IT and Digital Healt
Apply Healthcare IT & Dig
- Department: Decision, Risk and Operations
- W 2:20 p.m.-5:35 p.m.
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Instructor:
Raymond G Falci
Info - 1.5 points
Advanced Economic Development for Intern
This is an advanced course in development economics, designed for SIPA students interested in rigorous, applied training. Coursework includes extensive empirical exercises, requiring programming in Stata. The treatment of theoretical models presumes knowledge of calculus. Topics include: the economics of growth; the relationship between growth and poverty and inequality; rural-urban migration; the interaction between agrarian institutions in land, labor, credit, and insurance markets; prisoner’s dilemmas and the environment; and policy debates around development strategies. Recurrent themes: Are markets efficient, and if not, in what specific ways are they inefficient? What are the forces driving development and underdevelopment? What are the causal links between poverty and inequality and economic performance? What is the role of interventions by states or civil organizations in bringing about development? The course will integrate theoretical ideas and empirical analysis, with an emphasis on questions relevant for economic policy.
- Department: International and Public Affairs
- R 9 a.m.-10:50 a.m.
- R 2:10 p.m.-4 p.m.
- M 2:10 p.m.-4 p.m.
- M 9 a.m.-10:50 a.m.
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Instructor:
Nicolas de Roux
Info - 3 points
Complex Care Practicum I
This clinical course is designed to further develop the role of the student to provide care to individuals with complex, comorbid, advanced, or terminal illness and their families.
- Department: Nursing
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Instructor:
Aluem Tark
Info - 3 points