Technology Management
2017-18 General Catalog
Baskin School of Engineering
(831) 459-2158
http://www.soe.ucsc.edu
Lower-Division Courses
20. Innovations and Entrepreneurship Seminar (2 credits). F,W,S
Helps students convert their ideas into a viable business. Students must provide their own idea for a new product or company. Local entrepreneurs provide advice and mentoring to each student team. (General Education Code(s): PR-E.) J. Skardon
21. Innovations and Entrepreneurship in Practice. *
The second of a two-part series in basic entrepreneurship, This course helps student entrepreneurs test and validate a marketing and customer business model for a new idea, and refine a working prototype or service. Prerequisite(s): course 20 or course 105 or by consent of the instructor. (General Education Code(s): PR-E.) J. Skardon
50. Business Information Systems. F,W,S
Addresses the use of information systems (IS) within a business enterprise. Subjects include computer hardware and software concepts, system design and implementation, telecommunications, data management, transaction-based systems, management information systems, and the use of IS to compete. Intended for technology and information management and business management economics majors. R. Akella, Y. Chen, J. Musacchio
58. Systems Analysis and Design. W
Students learn how information technology is used to deal with business requirements and/or solve business problems. Provides an understanding of structured computer systems analysis and design methodologies and techniques and their application to business information systems. Intended for technology and information management and business management economics majors. Prerequisite(s): course 50. Enrollment limited to 40. Y. Zhang
80C. Starting a New Technology Company. S
Focuses on the creation and management of technology start-ups and small companies, using case studies and team projects as the basis for learning and applying the course materials. D. Lee, S. Desa
94. Group Tutorial. F,W,S
A means for a small group of students to study a particular topic in consultation with a faculty sponsor. Students submit petition to sponsoring agency. May be repeated for credit. The Staff
94F. Group Tutorial (2 credits). F,W,S
A means for a small group of students to study a particular topic in consultation with a faculty sponsor. Students submit petition to sponsoring agency. May be repeated for credit. The Staff
99. Tutorial. F,W,S
Students submit petition to sponsoring agency. May be repeated for credit. The Staff
99F. Tutorial (2 credits). F,W,S
Students submit petition to sponsoring agency. May be repeated for credit. The Staff
Upper-Division Courses
101. Management of Technology Seminar (2 credits). F,W,S
Uses weekly talks by leading industry practitioners and university researchers to provide in-depth exposure to the management of technology. Topics covered include product development, operations, strategy, finance, and marketing for technologies such as software and information systems. May be repeated for credit. S. Desa
105. Introduction to Management of Technology I. F
An in-depth examination of technological, strategic, marketing, and financial methods and analytical tools for the management of technology to enable cost-effective and rapid development of profitable and high quality technologies. Includes case studies and a comprehensive project. (Formerly Management of Technology I.) Prerequisite(s): Mathematics 19B or 11B or Applied Mathematics and Statistics 11B or Economics 11B. S. Desa
115. Entrepreneurial Organization and Leadership. *
Provides a framework for analysis and practical insights into the issues associated with managing people, including motivation, team creation, and management and managing performance. Entrepreneurial leadership roles are emphasized. Enrollment restricted to juniors, seniors, and graduate students. Enrollment limited to 50. (General Education Code(s): PE-H.) D. Lee
125. Introduction to Management of Technology II. W
High-technology enterprises must understand and operate effectively within their technology-business value chains in order to maximize profitability. This course develops and applies methods and tools for the design, optimization, selection, and management of these value chain networks. (Formerly Management of Technology II.) Prerequisite(s): course 105. S. Desa
130. Financial Engineering and Management in High Technology Firms. S
Addresses methods and tools for financing technology development and projects. Includes approaches for coordinating finance and accounting with strategy and operations of firms; discounted cash-flow analysis; activity-based costing; financial planning; and elements of financial account and investment science. Prerequisite(s): Economics 113 or Applied Mathematics and Statistics 131 or Computer Engineering 107 or by instructor permission. Enrollment limited to 20. R. Akella
155. Water and Energy Management. *
Introduces water and energy management challenges, data sources, and analytical techniques. Topics include energy and water production and consumption; energy-water nexus; utilizing renewable resources; system sustainability; cost and cost allocation; risk; and system reliability. (Formerly Data Analytics for Water and Energy Management.) Prerequisite(s): a college-level calculus course. Enrollment restricted to juniors and seniors. (General Education Code(s): PE-E.) B. Haddad
158. Business Strategy and Information Systems. S
Analysis of effective use of information systems within a business enterprise, with emphasis on gaining a competitive advantage. Integration of information systems with business strategy, financial justification, personnel, and organizational considerations are highlighted. Intended for technology and information management majors or senior engineering majors who have a business interest. Prerequisite(s): satisfaction of the Entry Level Writing and Composition requirements; course 50 or permission of instructor. The Staff
165. Decision Analysis in Management. F
Presents decision tools/theory with a focus on investment, finance, management, technology, and policy. Often, irreversible decisions are made without enough information to analyze the possible consequences. Course uses systematic approaches to analyze these types of situations to enable rational decisions. Prerequisite(s): Mathematics 22, Economics 113, and Economics 100A or 100M. Enrollment restricted to juniors and seniors. Y. Chen
166A. Game Theory and Applications I. F
Introduces modern game theory, including applications in social science, biology, and engineering. Topics include extensive form, strategic form, mixed strategies, incomplete information, repeated games, evolutionary games, and simulation techniques. (Also offered as Computer Science 166A. Students cannot receive credit for both courses.) Prerequisite(s): Applied Math and Statistics 5 or 7 or Economics 113; and Economics 11B, Applied Math and Statistics 11B, or Mathematics 11B or 19B. Enrollment restricted to juniors and seniors. Enrollment limited to 100. J. Musacchio
193. Field Study. F,W,S
Provides individual programs of study with specific academic objectives carried out under direction of faculty member of Information Systems Management and a willing sponsor at field site. Uses resources not normally available on campus. Credit based on presentation of evidence of achieving objectives by submitting written and oral presentation. Students submit petition to sponsoring agency. May be repeated for credit. The Staff
193F. Field Study (2 credits). F,W,S
Provides individual programs of study with specific academic objectives carried out under direction of faculty member of Information Systems Management and a willing sponsor at field site. Uses resources not normally available on campus. Credit based on presentation of evidence of achieving objectives by submitting written and oral presentation. Cannot normally be repeated for credit. Students submit petition to sponsoring agency. May be repeated for credit. The Staff
194. Group Tutorial. F,W,S
A program of independent study arranged between a group of students and a faculty member. Students submit petition to sponsoring agency. May be repeated for credit. The Staff
194F. Group Tutorial (2 credits). F,W,S
A program of independent study arranged between a group of students and a faculty member. Students submit petition to sponsoring agency. May be repeated for credit. The Staff
195. Senior Thesis Research. F,W,S
Intended for majors. Students submit petition to sponsoring agency. The Staff
195F. Senior Thesis Research (2 credits). F,W,S
Intended for majors. Students submit petition to sponsoring agency. The Staff
198. Individual Study or Research. F,W,S
Intended for majors. Students submit petition to sponsoring agency. May be repeated for credit. The Staff
198F. Individual Study or Research (2 credits). F,W,S
Intended for majors. Students submit petition to sponsoring agency. May be repeated for credit. The Staff
199. Tutorial. F,W,S
Individual directed study for upper-division undergraduates. Students submit petition to sponsoring agency. Enrollment restricted to senior information systems management majors. May be repeated for credit. The Staff
Graduate Courses
204. Introduction to Optimization in Business. *
Covers optimization with emphasis on problems arising in management. Students become proficient at mathematical modeling of business decisions and familiar with a range of techniques and tools used to solve optimization problems. Enrollment restricted to graduate students. The Staff
205. Management of Technology I. F
Addresses technological, strategic, marketing, financial methods, and analytical tools for management of technology in an integrated manner that enables the cost-effective and rapid development of profitable and high quality technologies. Includes case studies and a comprehensive project. Enrollment restricted to juniors, seniors, and graduate students. S. Desa
206. Optimization Theory and Applications. W
A first graduate course in optimization with an emphasis on problems arising in management and engineering applications. Objectives are to become experts in problem formulation, comfortable with software for solving these problems, and familiar with analytical methods behind these solver technologies. Prerequisite(s): calculus and linear algebra. Enrollment restricted to graduate students. Y. Chen, J. Musacchio
207. Random Process Models in Engineering. *
A first graduate course in stochastic process modeling and analysis with an emphasis on applications in technology management, information systems design, and engineering. Enrollment restricted to graduate students. Prerequisite: Computer Engineering 107 or other undergraduate probability course recommended. J. Musacchio
209. Data Mining and Business Analytics in Knowledge Services. *
Provides students with systematic methodology and analytical tools in data and text mining and business analytics. Also provides an integrated perspective and examines use of these methods in the field of knowledge services, such as online marketing, sponsored search, health care, financial services, recommender systems, etc. Includes training in the basic elements of stochastic optimization and other algorithmic approaches, such as stochastic dynamic programming, statistics, constrained optimization, and machine learning with exposure to software tools. These methods enable firms to achieve rapid, effective, and profitable optimization of knowledge-services management. Enrollment restricted to graduate students. Students are expected to have undergraduate preparation in probability and statistics. Undergraduates may enroll with instructor approval. R. Akella
210. Marketing Analytics and Engineering. *
Provides students with a systematic methodology and the corresponding set of methods and analytical tools to address the analytic approaches to marketing in a real-world context. Trains students in the basic elements of statistics decision trees, stochastic optimization, and other algorithmic approaches. Students should have a solid background in the following: probability equivalent to statistics, stochastic methods, calculus, linear algebra, stochastic processes and optimization, and/or mathematical maturity. Recommended courses: course 207, course 250, Applied Mathematics and Statistics 203, Applied Mathematics and Statistics 205, Computer Engineering 230. Enrollment restricted to graduate students. Enrollment by permission of instructor. The Staff
211. E-Business Technology and Strategy. *
Surveys structure of modern information technology, the relation of that structure to structure of the industry that creates it, and the economic forces that drive the players in the industry. Building on these technological and economic concepts, studies how firms can craft a technology and business strategy to create and capture value in the information technology product and/or services sectors. Enrollment restricted to graduate students. J. Musacchio
215. Organizations and Leadership. *
Addresses organizational and managerial aspects of high-tech enterprises, providing an understanding of various corporate functions. Considers issues of human resources: motivation and rewards, group dynamics, communication, ethics, and leadership. Includes perspectives from behavioral theories and corporate practice/culture. Enrollment restricted to graduate students. The Staff
225. Management of Technology II. W
High technology enterprises must understand and operate effectively within their technology-business value chains in order to maximize profitability. Course develops and applies methods and tools for the design, optimization, selection, and management of these value chain networks. Prerequisite(s): course 205 or consent of instructor. Enrollment restricted to juniors, seniors, and graduate students. S. Desa
230. Financial Engineering and Management in High Technology Firms. *
Course provides students with a systematic methodology, and the corresponding set of methods and analytical tools, to address the field of financial engineering and its use in high-tech enterprises in an integrated manner. Covers basic concepts of stochastic optimization and other algorithmic approaches, such as stochastic dynamic programming; decision models and analysis; and binomial trees; and their application in financial engineering in the context of high-tech enterprises. Prerequisite(s): Computer Engineering 107 or Economics 113 or Applied Mathematics and Statistics 131, or instructor approval. Enrollment restricted to graduate students. R. Akella
240. Information Technology for Decision Support: An Introduction. *
Introduction to the information technologies useful to IT management. Reviews/surveys four major topics: 1) information systems: from computer technology—systems architecture (hardware and software), multiprocessors and cluster—to client-server, networking and distributed computing, data storage and data servers, file management, database systems, input/output technology, graphics and multimedia; 2) IT as a "service": commercial and open-source tools for information-system development and knowledge management; 3) managing, searching, and mining of structured and unstructured data; 4) decision-support systems that integrate knowledge with data mining and text mining tools to support decision-making in product development, supply-chain management, marketing, sales and logistics. Enrollment restricted to graduate students. The Staff
245. Data Mining. F
Covers the principles, algorithms, and applications of data mining, including mining sequential data, structured data, stream data, text data, spatiotemporal data, biomedical data, and other forms of complex data. Enrollment restricted to graduate students. Y. Zhang, (F) The Staff
250. Stochastic Optimization in Business Intelligence: Digital Advertising and Online Marketing. *
Trains students in stochastic optimization and other algorithmic approaches, such as stochastic dynamic programming, to achieve business intelligence (BI) optimization. Special emphasis on digital advertising, and online and computational marketing. Students should have solid background in: probability equivalent to statistics, stochastic methods, calculus, liner algebra, mathematical maturity, stochastic processes, and optimization. First of a sequence of courses in information systems and technology management (ISTM). Provides students with systematic methodology and corresponding set of methods and analytical tools to address the field of ISTM in an integrated manner. Enrollment restricted to graduate students;undergraduates who have completed Computer Engineering (CMPE) 107 or Applied Mathematics & Statistics (AMS) 131 may enroll by permission of instructor. AMS 205A, CMPE 230 recommended. The Staff
251. Large-Scale Web Analytics and Machine Learning. *
Provides a systematic methodology and corresponding set of methods and analytical tools in stochastic models; reinforcement learning; stochastic (neuro-)dynamic programming; Bayesian graphical models; inference; and social networks used for web analytics and machine learning to achieve business intelligence (BI) and support research and applications in computer science, computer engineering, and electrical engineering, applied mathematics and statistics, business, management, and economics. Includes exposure to Hadoop for large-scale computation. Students should have solid background in probability equivalent to statistics, stochastic, methods, calculus, (and preferably) stochastic processes and optimization, or mathematical maturity and exposure to business intelligence and algorithms. Prerequisite(s): Computer Engineering 107 or Applied Mathematics and Statistics 131 or permission of instructor. Enrollment restricted to graduate students. Course 230, 250 ,and Applied Mathematics and Statistics 205A or 205B recommended. The Staff
260. Information Retrieval. *
Course covers major topics of information retrieval, including statistical characteristics of text, several important retrieval models, text clustering, text classification, text filtering, web analysis, information extraction, peer to peer research, distributed search, personalized search, and other related topics. Enrollment restricted to graduate students. Undergraduates may enroll with permission of instructor. Y. Zhang
270. Service Engineering and Management. *
Introduction to service engineering and management, from the role of services in the global economy to analytical models in service operations management. This field is developing rapidly; the material covers the fundamental principles of services as well as recent research. Topics include designing efficient service networks, forecasting, resource allocation, and globalization. Enrollment restricted to graduate students. The Staff
275. Techology Management in Network Industries. S
Introduces analytical tools (optimization and simulation) for modeling firms' technology choices and market behavior for an industry with a network structure. Examples of industries with a network include electric power, airline, natural gas, water supply systems, and transportation sectors. These models are useful for planning investments in infrastructure, such as network expansion (transmission lines), supply capacity (power plants, storage), and demand-side management, and for analysis of public policies. Students are encouraged to apply those tools to analyze other sectors in a class project. Enrollment is restricted to graduate students. Enrollment limited to 20. Y. Chen
280A. Graduate Research Seminar (2 credits). W
Weekly seminar series in topics of current research in information systems and technology management. Enrollment by permission of instructor. Enrollment limited to 30. May be repeated for credit. Y. Chen, B. Haddad
280I. Seminar on Information Retrieval and Knowledge Management (2 credits). F,S
Seminar series discussing advanced topics in information retrieval and knowledge management. Current research and literature are presented during each meeting. Enrollment restricted to graduate students. Enrollment limited to 20. May be repeated for credit. The Staff
280M. Sales and Marketing for Technologists and Engineers (2 credits). *
Perspective on the theory, plus examples, and tools useful to technologists and engineers for successfully guiding and supporting sales and marketing endeavors and, thereby, ensuring funding, staffing, product appeal, positive customer relationships, and marketplace success. The Staff
280S. Seminar Topics (2 credits). F
Weekly seminar series of current research on a special topic in information systems and technology management. The theme of research presented throughout the course selected by the instructor. Topics may include, but are not limited to, knowledge planning, new product development and management of technology. Enrollment with permission of instructor. Enrollment limited to 30. May be repeated for credit. The Staff, Y. Chen, R. Akella
283. Special Topics in Technology and Information Management (3 credits). *
Graduate seminar on topics in technology and information management that varies with the particular instructor. Topics may include, but are not limited to: data analytics, information retrieval, recommender systems, technology management, and the economics of information and technology. Enrollment restricted to graduate students. B. Haddad
293. Advanced Topics in Technology and Information Management (TIM). *
Advanced research topics in TIM (as determined by instructor). Topics include, but are not limited to, approaches and solutions to complex business problems, and development of information-based technology and services. Enrollment restricted to graduate students. Enrollment limited to 25. May be repeated for credit. The Staff
296. Master Project. F,W,S
Master project conducted under faculty supervision. Petition on file with sponsor faculty. Enrollment is restricted to graduate students. May be repeated for credit. The Staff
297. Independent Study. F,W,S
Independent study under faculty supervision. Students submit petition to sponsoring agency. Enrollment restricted to graduate students. May be repeated for credit. The Staff
299. Thesis Research. F,W,S
Thesis research under faculty supervision. Students submit petition to sponsoring agency. Enrollment restricted to graduate students. May be repeated for credit. The Staff
Revised: 09/01/17
