Masters level independent project involving theoretical, computational, experimental or engineering design work. May be repeated, subject to Masters Program guidelines.
Only for masters students in the Department of Applied Physics and Applied Mathematics who may need relevant work experience a part of their program of study. Final report required. This course may not be taken for pass/fail or audited.
Prerequisites: Obtained internship and approval from faculty advisor. BMEN graduate students only. Only for BMEN graduate students who need relevant work experience as part of their program of study. Final reports required. May not be taken for pass/fail credit or audited.
Instructors written approval. May be repeated for credit, but no more than 3 total points may be used for degree credit. Only for Civil Engineering and Engineering Mechanics graduate students who include relevant off-campus work experience as part of their approved program of study. Final report and letter of evaluation required. May not be taken for pass/fail credit or audited.
Prerequisites: Instructors written permission. Only EAEE graduate students who need relevant off-campus work experience as part of their program of study as determined by the instructor. Written application must be made prior to registration outlining proposed study program. Final reports required. This course may not be taken for pass/ fail credit or audited. International students must also consult with the International Students and Scholars Office.
Prerequisites: Obtained internship and approval from faculty advisor. Only for IEOR graduate students who need relevant work experience as part of their program of study. Final reports required. This course may not be taken for pass/fail credit or audited.
Prerequisites: Instructors written approval. Only for ME graduate students who need relevant off-campus work experience as part of their program of study as determined by the instructor. Written application must be made prior to registration outlining proposed study program. Final reports required. May not be taken for pass/fail credit or audited. International students must consult with the International Students and Scholars Office.
Prerequisites: Internship and approval from advisor must be obtained in advance. Only for masters students in the Department of Applied Physics and Applied Mathematics who may need relevant work experience as part of their program of study. Final report required. This course may not be taken for pass/fail or audited.
This course is a no-credit class designed to start providing critical material to incoming QMSS students overthe summer to help prepare them for the coding demands of the program. We will post links, exercises andresources for students to work on before they start their classes in the Fall of 2018.
This course is a no-credit class designed to start providing critical material to incoming QMSS students overthe summer to help prepare them for the coding demands of the program. We will post links, exercises andresources for students to work on before they start their classes in the Fall of 2018.
Students will be introduced to the fundamental financial issues of the modern corporation. By the end of this course, students will understand the basic concepts of financial planning, managing growth; debt and equity sources of financing and valuation; capital budgeting methods; and risk analysis, cost of capital, and the process of securities issuance.
Students will be introduced to the fundamental financial issues of the modern corporation. By the end of this course, students will understand the basic concepts of financial planning, managing growth; debt and equity sources of financing and valuation; capital budgeting methods; and risk analysis, cost of capital, and the process of securities issuance.
Students will be introduced to the fundamental financial issues of the modern corporation. By the end of this course, students will understand the basic concepts of financial planning, managing growth; debt and equity sources of financing and valuation; capital budgeting methods; and risk analysis, cost of capital, and the process of securities issuance.
Prerequisites: BUSI PS5001 Introduction to Finance/or Professor Approval is required Students will learn the critical corporate finance concepts including financial statement analysis; performance metrics; valuation of stocks and bonds; project and firm valuation; cost of capital; capital investment strategies and sources of capital, and firm growth strategies. At the end of this course students will understand how to apply these concepts to current business problems.
Prerequisites: BUSI PS5001 Introduction to Finance/or Professor Approval is required Students will learn the critical corporate finance concepts including financial statement analysis; performance metrics; valuation of stocks and bonds; project and firm valuation; cost of capital; capital investment strategies and sources of capital, and firm growth strategies. At the end of this course students will understand how to apply these concepts to current business problems.
Students will examine the generally accepted account principles (GAAP) underlying financial statements and their implementation in practice. The perspective and main focus of the course is from the users of the information contained in the statements, including investors, financial analysts, creditors and, management. By the end of this class students will be able to construct a cash flow statement, balance sheet and decipher a 10K report.
Students will examine the generally accepted account principles (GAAP) underlying financial statements and their implementation in practice. The perspective and main focus of the course is from the users of the information contained in the statements, including investors, financial analysts, creditors and, management. By the end of this class students will be able to construct a cash flow statement, balance sheet and decipher a 10K report.
Students will gain an overview of major concepts of management and organization theory, concentrating on understanding human behavior in organizational contexts, with heavy emphasis on the application of concepts to solve managerial problems. By the end of this course students will have developed the skills to motivate employees, establish professional interpersonal relationships, take a leadership role, and conduct performance appraisal.
Students will gain an overview of major concepts of management and organization theory, concentrating on understanding human behavior in organizational contexts, with heavy emphasis on the application of concepts to solve managerial problems. By the end of this course students will have developed the skills to motivate employees, establish professional interpersonal relationships, take a leadership role, and conduct performance appraisal.
Students will gain an overview of major concepts of management and organization theory, concentrating on understanding human behavior in organizational contexts, with heavy emphasis on the application of concepts to solve managerial problems. By the end of this course students will have developed the skills to motivate employees, establish professional interpersonal relationships, take a leadership role, and conduct performance appraisal.
This course is meant to provide an introduction to regression and applied statistics for the social sciences, with a strong emphasis on utilizing the Python software language to perform the key tasks in the data analysis workflow. Topics to be covered include various data structures, basic descriptive statistics, regression models, multiple regression analysis, interactions, polynomials, Gauss-Markov assumptions and asymptotics, heteroskedasticity and diagnostics, data visualization, models for binary outcomes, models for ordered data, first difference analysis, factor analysis, and cluster analysis. Through a variety of lab assignments, students will be able to generate and interpret quantitative data in helpful and provocative ways. Only relatively basic mathematics skills are assumed, but some more advanced math will be introduced as needed. A previous introductory statistics course that includes linear regression is helpful, but not required.
Students will learn fundamental marketing concepts and their application. By the end of this class you will know: the elements of a market, company strategy, how to identify customers and competition, the fundamental elements of the marketing mix (product, price, placement and promotion) how to research consumer behavior, and pricing strategies. Students will have extensive use of case study projects. Please note that tuition is the same for online and on-campus courses, there is an additional $85 course fee for online courses.
Students will learn fundamental marketing concepts and their application. By the end of this class you will know: the elements of a market, company strategy, how to identify customers and competition, the fundamental elements of the marketing mix (product, price, placement and promotion) how to research consumer behavior, and pricing strategies. Students will have extensive use of case study projects. Please note that tuition is the same for online and on-campus courses, there is an additional $85 course fee for online courses.
Prerequisites: BUSI PS5020 Introduction to Marketing/or Professor Approval is required Students will develop analytical skills used to formulate and implement marketing driven strategies for an organization. Students will develop a deeper understanding of marketing strategies and how to implement tactics to achieve desired goals. Students will work on case study projects in both individual and a team based projects. By the end of this course you will be able to develop a marketing strategy based market assessments and company needs.
Prerequisites: BUSI PS5020 Introduction to Marketing/or Professor Approval is required Students will develop analytical skills used to formulate and implement marketing driven strategies for an organization. Students will develop a deeper understanding of marketing strategies and how to implement tactics to achieve desired goals. Students will work on case study projects in both individual and a team based projects. By the end of this course you will be able to develop a marketing strategy based market assessments and company needs.
Interested in starting your own company? Do you have an idea for a new product or service? Have you come up with a way to improve something that already exists? This course tackles the central business concept of how one creates, builds and leads companies. It looks at aspects of entrepreneurship and leadership for both individuals and teams in the face of complex situations. Using the case study method as taught in business school, also known as participant-centered learning, this course puts students in the role of an entrepreneur facing critical business decisions. A selection of guest speakers will offer firsthand experience on innovation and entrepreneurship.
Interested in starting your own company? Do you have an idea for a new product or service? Have you come up with a way to improve something that already exists? This course tackles the central business concept of how one creates, builds and leads companies. It looks at aspects of entrepreneurship and leadership for both individuals and teams in the face of complex situations. Using the case study method as taught in business school, also known as participant-centered learning, this course puts students in the role of an entrepreneur facing critical business decisions. A selection of guest speakers will offer firsthand experience on innovation and entrepreneurship.
Prerequisites: BUSI PS5001 Intro to Finance and BUSI PS5003 Corporate Finance or Professor Approval required. If you have not taken PS5001 or PS5003 at Columbia University, please contact phb2120@columbia.edu for professor approval. Students will learn about the valuation of publicly traded equity securities. By the end of the semester students will be able to perform fundamental analysis (bottoms-up, firm-level, business and financial analysis), prepare pro forma financial statements, estimate free cash flows and apply valuation models.
Prerequisites: BUSI PS5001 Intro to Finance and BUSI PS5003 Corporate Finance or Professor Approval required. If you have not taken PS5001 or PS5003 at Columbia University, please contact phb2120@columbia.edu for professor approval. Students will learn about the valuation of publicly traded equity securities. By the end of the semester students will be able to perform fundamental analysis (bottoms-up, firm-level, business and financial analysis), prepare pro forma financial statements, estimate free cash flows and apply valuation models.
TBA
TBA
Social scientists need to engage with natural language processing (NLP) approaches that are found in computer science, engineering, AI, tech and in industry. This course will provide an overview of natural language processing as it is applied in a number of domains. The goal is to gain familiarity with a number of critical topics and techniques that use text as data, and then to see how those NLP techniques can be used to produce social science research and insights. This course will be hands-on, with several large-scale exercises. The course will start with an introduction to Python and associated key NLP packages and github. The course will then cover topics like language modeling; part of speech tagging; parsing; information extraction; tokenizing; topic modeling; machine translation; sentiment analysis; summarization; supervised machine learning; and hidden Markov models. Prerequisites are basic probability and statistics, basic linear algebra and calculus. The course will use Python, and so if students have programmed in at least one software language, that will make it easier to keep up with the course.
Prerequisites: basic probability and statistics, basic linear algebra, and calculus This course will provide a comprehensive overview of machine learning as it is applied in a number of domains. Comparisons and contrasts will be drawn between this machine learning approach and more traditional regression-based approaches used in the social sciences. Emphasis will also be placed on opportunities to synthesize these two approaches. The course will start with an introduction to Python, the scikit-learn package and GitHub. After that, there will be some discussion of data exploration, visualization in matplotlib, preprocessing, feature engineering, variable imputation, and feature selection. Supervised learning methods will be considered, including OLS models, linear models for classification, support vector machines, decision trees and random forests, and gradient boosting. Calibration, model evaluation and strategies for dealing with imbalanced datasets, n on-negative matrix factorization, and outlier detection will be considered next. This will be followed by unsupervised techniques: PCA, discriminant analysis, manifold learning, clustering, mixture models, cluster evaluation. Lastly, we will consider neural networks, convolutional neural networks for image classification and recurrent neural networks. This course will primarily us Python. Previous programming experience will be helpful but not requisite. Prerequisites: basic probability and statistics, basic linear algebra, and calculus.
This course provides an opportunity for students in the Economics Master of Arts Program to engage in off-campus internships for academic credit that will count towards their requirements for the degree. The internships will facilitate the application of economic skills that students have developed in the program and prepare them for future work in the field.
This course is designed to provide the pre-licensure student with an overview of current issues confronting professional nursing. Emphasis will be placed on the history of nursing, interrelated theories, current trends, and policy issues that shape the profession and the health care delivery system. The role of the nurse as a patient advocate, designer, manager, and coordinator of care will be discussed.
An in-depth study of the intricacies of managing technical personnel and management teams in a fast paced and evolving business environment. Emphasis is placed on key challenges including the management of multiple technology projects, software development processes, and communications among technology managers and senior managers, developers, programmers, and customers.
This course explores key knowledge management and organizational learning concepts and techniques that are critical to business, individual, and organizational performance. As technology and the network economy drive businesses to compete under continuously accelerating rates of change in technology, business leaders must incorporate knowledge management and learning into their organization’s activities in ways that support and propel their business goals. They must also be proactive in recognizing and responding to the influence of technology on these goals and environment(s) in which they are accomplished. Class sessions encompass a set of topics including purpose, planning, success measurement, and implementation of knowledge management initiatives and organizational learning techniques. Through lectures and individual and collaborative work, students explore how they can use these techniques to improve business performance and strengthen their leadership and management capabilities.
An in-depth understanding of how to market a business plan and raise capital to launch new ventures. Topics include capital alternatives, confidentiality, meeting analysis, finalizing agreements, and shareholder alternatives. The course requires the design of a venture that contains multiple approaches for investment. Workshop exercises cover methods of negotiating initial investment, management control, and forecasted return-on-investment.
Competition, espionage, theft, sabotage, and warfare, traditionally carried out “in the field” have erupted online. State-sponsored cyber-attacks target critical infrastructure, financial systems, government agencies, political adversaries, retail, and consumer databases, and the intellectual property of technology firms. This course covers the defensive techniques that address perimeter and data security. Business model relationships to security architecture are examined, in particular managing vulnerability introduced through mergers and acquisitions, and Active Directory migrations. Service and Administrative account management and other aspects of network design will be analyzed. Students will investigate recent newsworthy cases and devise countermeasures aimed at both incident prevention and effective CIRT (Cyber Incident Response) management.
This course examines how to develop realistic market plans, forecast schedules, and build effective sales teams for new and ongoing business operations, covering the basic rules of pricing, the positioning of technology products and services for market, how to determine life cycles of new products, and the sales management of complex technology-based teams.
The idea of a “multiverse” is derived from Big Bang and Black Hole cosmology. It posits an infinite set of alternative universes in the space/time continuum — in other words, what we identify as reality. Scientific theory aside, this is precisely what has occurred in the entertainment sphere as a result of advances in entertainment technology. We see how technology has obfuscated the demarcation and delineation lines between entertainment media. Rather than perceiving this as a problem or challenge, this course approaches such an evolution from the point-of-view of infinite possibilities. The breadth of content covered in this course ranges from Creative Commons licenses to the various interactive entertainment development technology platforms used to create games, virtual worlds, social media arenas, and cross-disciplinary initiatives as diverse as online gaming, media, branding, enterprise, government, military, and educational solutions.
This course provides students with the knowledge and techniques needed to lead major re-engineering projects, including reassessment of legacy systems and changing existing business processes. Understanding the differences between reengineering and continuous improvements and benchmarking is covered up-front together with common obstacles to business reengineering success (e.g., resistance to change, etc.) in an effort to drive towards a specific reengineering model. Legacy architectures from de-composable to non-decomposable are covered, and the role of gateways as well. The principles of distributed computing, i.e., object orientation, standards and the enterprise information architecture are covered as well as distributed systems designs and the level of performance testing needed to support them. Case studies are used to reinforce topics.