Selected topics in Natural Language Processing (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check the "topics courses" webpage on the department website for more information on each section.
Selected topics in Natural Language Processing (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check the "topics courses" webpage on the department website for more information on each section.
Provides students the opportunity to present work in progress or final drafts to other students and relevant faculty to receive guidance and feedback.
MRST Directed Readings, Independent study. Students should meet with the Program Director and Program Manager before registering for this course.
Illuminated, exposed, projected, magnified—the cinematic face is at once spectacular and mysterious, commanding and vulnerable, an inexhaustible object of wonder. The seminar will explore the workings of the human face as privileged object of representation, as figure of subjectivity, as mode and ethic of address through film theory and practice. How has the technological, mass-circulating art of the moving image mediated this singular entity—this visual incarnation of the
person
? How did it confront its mythic and iconic resonance, its charge of identity and identification, its revelatory and masking play of expression, its social, racial, and affective registers? Among filmmakers and writers who inform our discussion: Roland Barthes, Mary Ann Doane, Carl-Theodor Dreyer, Jean Epstein, Buster Keaton, Alfred Hitchcock, Emmanuel Levinas, Claude Lévi-Strauss, James Baldwin, Andy Warhol, Gilles Deleuze, and others.
CLEN 6998 GR is a twin listings of an undergraduate Comparative Literature lecture provided to graduate students for graduate credit. If a graduate student enrolls, she/he/they attends the same class as the undergraduate students (unless otherwise directed by the instructor). Each instructor determines additional work for graduate students to complete in order to receive graduate credit for the course. Please refer to the notes section in SSOL for the corresponding (twin) undergraduate 1000 or 2000 level course and follow that course's meeting day & time and assigned classroom. Instructor permission is required to join.
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
ENGL 6998 GR is a twin listings of an undergraduate English lecture provided to graduate students for graduate credit. If a graduate student enrolls, she/he/they attends the same class as the undergraduate students (unless otherwise directed by the instructor). Each instructor determines additional work for graduate students to complete in order to receive graduate credit for the course. Please refer to the notes section in SSOL for the corresponding (twin) undergraduate 1000 or 2000 level course and follow that course's meeting day & time and assigned classroom. Instructor permission is required to join.
ENGL 6998 GR is a twin listings of an undergraduate English lecture provided to graduate students for graduate credit. If a graduate student enrolls, she/he/they attends the same class as the undergraduate students (unless otherwise directed by the instructor). Each instructor determines additional work for graduate students to complete in order to receive graduate credit for the course. Please refer to the notes section in SSOL for the corresponding (twin) undergraduate 1000 or 2000 level course and follow that course's meeting day & time and assigned classroom. Instructor permission is required to join.
ENGL 6998 GR is a twin listings of an undergraduate English lecture provided to graduate students for graduate credit. If a graduate student enrolls, she/he/they attends the same class as the undergraduate students (unless otherwise directed by the instructor). Each instructor determines additional work for graduate students to complete in order to receive graduate credit for the course. Please refer to the notes section in SSOL for the corresponding (twin) undergraduate 1000 or 2000 level course and follow that course's meeting day & time and assigned classroom. Instructor permission is required to join.
First part of two-term MA Thesis sequence for MRST MA Students.
M.A. Thesis Course for MARS-REERS program.
Second part of two-term MA Thesis sequence for MRST MA Students.
M.A. Thesis Course for MARS-REERS program.
English communication proficiency is important for academic achievement and career success. Columbia Engineering provides English communication instruction for students who would like to improve their communication skills in English. In a small group setting (15-20 students), enrollees will obtain opportunities to interact with the instructor and fellow classmates to improve communication skills.
Until recently, due to their laissez faire underpinnings, market economies eschewed significant and overt government planning of sector-specific incentives and investment guidance. Nevertheless, in recent years many countries with quite different economic systems have embraced programs of targeted investment in specific industries as an integral part of a long term strategy of economic development. While the rationale for fostering innovation in strategic industries has a long and venerable tradition, there are also many current and historical examples of the potential for misallocation, malinvestment and rent-seeking protectionism in the actual record of centrally planned economies.
Recent Chinese advances in fostering the world’s largest investments in renewable energy, battery technology, electrified mobility, ultra-high voltage transmission and a supply chain ecosystem for automation and artificial intelligence both in deployments and manufacturing capacity may represent an extensive and illuminating example of the sustainable development potential of industrial policy. The field course will combine 5 weeks of preparatory in-person on-campus instruction followed by a 9-day field tour of instruction and visits to government agencies and companies in the renewable energy, battery technology, and electric vehicle manufacturing companies in China.
This elective course will provide training for those wishing to investigate the rationale, methods, limitations and examples of targeted government intervention to encourage investment in sustainability-related industries. The syllabus will include the logic of green industrial policy, the strengths and limitations of the policy toolkit, China’s experience with 5-year plans and the details of its directed growth in key green industrial sectors, as well as lessons for other countries. The content is designed to be of interest to Sustainability Management students whose career goals will lead them to strategy & planning positions in either private corporations, government agencies or international organizations. The course will be open to a maximum of 20 students, with priority given to SUMA and MoSSS students. An intermediate course in economics at the undergraduate level is a highly recommended prerequisite.
This course explores the use of financial information for internal planning, analysis, and decision-making. The main objective of the course is to equip you with the knowledge to understand, evaluate, and act upon the many financial and non-financial reports used in managing modern firms.
Managing any modern firm requires information about the firm’s products, processes, assets, and customers. This information is a key input into a wide range of decisions: analyzing profitability of various products, managing product-line portfolios, setting prices, measuring and managing profitability of customers, making operational and strategic decisions, evaluating investments, guiding improvement efforts, and so on.
The focus of this course is on modern internal-reporting systems. We will discover that many firms do not provide their managers with useful information; we will see numerous examples of value destruction and bankruptcies caused by this. We will also investigate some modern ideas in how an organization’s internal information system should be designed to enhance value creation; and we will see how world-class firms take advantage of their competitors’ internal-reporting mistakes.
To attain the right level of understanding, we will briefly explore the mechanics of the many techniques used to prepare internal reports. But the emphasis in this course is very much on interpretation, evaluation, and decision-making.
We will examine the following key topics:
? Designing managerial information systems to support an organization’s strategy.
? Determining which financial and non-financial metrics are necessary for success in various competitive environments.
? Evaluating profitability of products, services, assets, and customers.
? The capabilities and the limitations of various reporting systems in guiding value-maximization, cost-control, and improvement efforts.
? The limitations of traditional cost-estimation systems.
? Activity-based costing and activity-based management.
? Estimating and managing the costs of capacity resources.
? Relevant costs and relevant revenues in business decisions.
? The information necessary to evaluate long-term business decisions.
? The incentives created by various performance-evaluation techniques.
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.
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.
Business analytics refers to the methods enterprises—such as businesses, non-profits, and governments—use to analyze data to gain insights and make better decisions. This discipline is applied across various functions including operations, marketing, finance, and strategic planning. The advent of modern data collection methods in fields like bioinformatics, mobile platforms, and previously unanalyzable data (such as text and images) has led to an explosive growth in the volume of data available for decision-making. Utilizing data effectively to drive rapid, precise, and profitable decisions has become a critical strategic advantage for diverse companies including Walmart, Google, Capital One, and Disney. Moreover, many startups are emerging based on the application of AI and analytics to large databases. With the increasing availability of broad and deep sources of information—often referred to as "Big Data"—business analytics is becoming an even more essential capability for enterprises of all types and sizes.
AI is starting to influence every dimension of business and society. In many industries, being literate in AI is becoming a prerequisite for successful business leadership. The Business Analytics sequence is designed to prepare you to take an active role in shaping the future of AI and business. You will develop a critical understanding of modern analytics methodologies, exploring their foundations, potential applications, and—perhaps most importantly—their limitations.