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1 - 10 of 16 results for: OIT

OIT 256: Electronic Business (Accelerated)

This course focuses on the way information technology affects the structure of business models. It considers the impact of information technology on industries ranging from retail to logistics and from healthcare to smartphones. It considers how you can take advantage of new technology opportunities and how they change the structure of firms, industries and value chains, with an emphasis on business issues. Classes combine lecture and case study discussions and the workload is above the GSB average. The course is designed to help you make a transition into technology-related fields.
Terms: Win | Units: 2

OIT 265: Data and Decisions

This is the base version of D&D. This course introduces the fundamental concepts and techniques for analyzing risk and formulating sound decisions in uncertain environments. Approximately half of the course focuses on probability and its application. The remainder of the course examines statistical methods for interpreting and analyzing data including sampling concepts, regression analysis, and hypothesis testing. Applications include inventory management, demand analysis, portfolio analysis, surveys and opinion polls, A/B testing, environmental contamination, online advertising and the role of analytics in business settings more generally. The course emphasizes analytical techniques and concepts that are broadly applicable to business problems.
Terms: Win, Spr | Units: 3

OIT 267: Data and Decisions - Accelerated

Data and Decisions - Accelerated is a first-year MBA course in probability, statistics, multiple regression analysis, and decision trees for students with strong quantitative backgrounds. Probability provides the foundation for modeling uncertainties. Statistics provides techniques for interpreting data, permitting managers to use small amounts of information to answer larger questions. Regression analysis provides a method for determining the relationship between a dependent variable and predictor variables. Decision tree analysis consists of quantitative approaches to decision making under uncertainty. Students taking this course need to be comfortable with mathematical notation, algebra, and some calculus. If you are not confident with your quantitative abilities, then you should enroll in OIT 265. Accelerated D&D will cover material covered in OIT 265 plus some additional topics such as discrete dependent variable models. While OIT 267 focuses on real world applicability, we will explore the mathematical underpinnings of these topics in more depth than OIT 265 as an avenue for deeper understanding. The group regression project is a key component of the course.
Terms: Win | Units: 3

OIT 273: Value Chain Innovations in Developing Economies

This course is about how to use entrepreneurship and innovations in the value chains to create values in developing economies. The course will cover important principles and ways in which the value chains can be re-engineered or new business models can be designed to create values. In addition to materials covering a diversity of industries and geographical regions, the course will also enable students to be exposed to some of the interventions that the Stanford Institute of Innovation in Developing Economies (SEED) is working on in West Africa. Work and exam requirements: Students are expected to develop a project report on either portfolio companies related to SEED or other enterprises to show how value chain innovations can be advanced.
Terms: Win | Units: 2
Instructors: Lee, H. (PI)

OIT 333: Design for Extreme Affordability

This course is a Bass Seminar. Project course jointly offered by School of Engineering and Graduate School of Business. Students apply engineering and business skills to design product or service prototypes, distribution systems, and business plans for entrepreneurial ventures that meet that challenges faced by the world's poor. Topics include user empathy, appropriate technology design, rapid prototype engineering and testing, social technology entrepreneurship, business modeling, and project management. Weekly design reviews; final course presentation. Industry and adviser interaction. Limited enrollment via application; see http://extreme.stanford.edu/index.html for details.
Terms: Win | Units: 4

OIT 356: Electronic Business

This course focuses on the way information technology affects the structure of firms, industries and business models. It considers the impact of information technology on multiple industries and how you can take advantage of new opportunities that are enabled by new technologies. The course is a compressed 2-unit course, where each session comprises a lecture followed by the application of the concepts to specific companies or industries. The workload is above the GSB average. The course assumes a good understanding of business applications of information technology. Topics include: Electronic platforms, business models for online retail, electronic commerce logistics, disruptive technologies, value chain coordination in healthcare, and mobile value chains.
Terms: Win | Units: 2

OIT 367: Business Intelligence from Big Data

The objective of this course is to analyze real-world situations where significant competitive advantage can be obtained through large-scale data analysis, with special attention to what can be done with the data and where the potential pitfalls lie. Students will be challenged to develop business-relevant questions and then solve for them by manipulating large data sets. Problems from advertising, eCommerce, finance, healthcare, marketing, and revenue management are presented. Students learn to apply software (such as R and SQL) to data sets to create knowledge that will inform decisions. The course covers fundamentals of statistical modeling, machine learning, and data-driven decision making. Students are expected to layer these topics over an existing facility with mathematical notation, algebra, calculus, probability, and basic statistics.
Terms: Win | Units: 3
Instructors: Bayati, M. (PI)

OIT 384: Biodesign Innovation: Needs Finding and Concept Creation

This is the first quarter of a two-quarter course series. In this two-quarter course ( BIOE 374A/B, MED 272A/B, ME 368A/B, OIT 384/5), multidisciplinary student teams identify real-world unmet healthcare needs, invent new medtech products to address them, and plan for their development into patient care. During the first quarter (winter 2016), students select and characterize an important unmet healthcare problem, validate it through primary interviews and secondary research, and then brainstorm and screen initial technology-based solutions. In the second quarter (spring 2016), teams select a lead solution and move it toward the market through prototyping, technical re-risking, strategies to address healthcare-specific requirements (regulation, reimbursement), and business planning. Final presentations in winter and spring are made to a panel of prominent medtech experts and investors. Class sessions include faculty-led instruction and case demonstrations, coaching sessions by industry specialists, expert guest lecturers, and interactive team meetings. Enrollment is by application only, and students are expected to participate in both quarters of the course. Visit http://biodesign.stanford.edu/bdn/courses/bioe374.jsp to access the application, examples of past projects, and student testimonials. More information about the Biodesign program, which has led to the creation of more than 30 venture-backed healthcare companies and has helped hundreds of student launch medtech careers, can be found at http://biodesign.stanford.edu/.
Terms: Win | Units: 4

OIT 536: Data for Action: From Insights to Applications

Data for Action is an MBA compressed course dedicated to identifying value in and creating value from data. It deals with the technical, legal, regulatory and business strategic decisions that must be considered when delivering solutions to customers.
Terms: Win | Units: 2

OIT 554: Seminar on IT for Business

This course offers an overview of information technologies for enterprises and supply chain management. The course has two key components - a series of guest speakers and a set of readings. Students are expected to have read the assigned note on related technologies before class, and prepare to discuss technologies with the guest speaker in class. We will not discuss the technology per se in class, so students who enroll are expected to have some exposure to technologies in order to digest the materials on their own. The main topics of technologies are: DBMS (Database Management System), ERP (Enterprise Resource Planning), EAI (Enterprise Application Interface), data mining, Big Data, cloud computing, RFID/NFC, mobile technologies, and mobile payment. In particular, students are encouraged to think hard about potential new businesses around the technology and discuss them in class.
Terms: Win | Units: 2
Instructors: Whang, S. (PI)
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