Full-Time MBA Class Visits
We encourage prospective MBA candidates to visit to the School to discover first-hand the special qualities of the UC Davis MBA program and our community. Experience the dynamic learning environment by attending one of our upcoming classes led by our highly accomplished faculty. After the class, you will be paired with a first- or second-year MBA Ambassador for an informal conversation about our program as well as introduction to our MBA Admissions Team.
Space is limited and pre-registration is required.
Register for a Full-Time MBA Class Visit
Wednesday from 12:10 p.m. to 3:00 p.m.
Join Professor Greta Hsu and current students for the Individual & Group Dynamics course.
Examines basic psychological and social psychological processes shaping human behavior and applies knowledge of these processes to the problem of working with and managing others in organizations. Topics include: motivation, job design, commitment, socialization, culture, individual and group decision making and team building.
Thursday from 9:00 a.m. to 11:50 a.m.
Join Professor Sanjay Saigal and current students for the Decision Making and Management Science course.
Considers management science for decision makers. Topics include an introduction to modeling and decision analysis, an introduction to optimization and linear programming, modeling and solving linear programming problems in a spread sheet, sensitivity analysis and the simplex method, networks, integer linear programming, project management and decision analysis.
- April 10, 2014
- April 17, 2014
- April 24, 2014
- May 1, 2014
- May 8 , 2014
- May 15, 2014
- May 22, 2014
- May 29, 2014
Mondays from 12:10 p.m. to 3:00 p.m.
Join Professor David Bunch and current students for the Marketing Research course.
Course addresses the managerial issues and problems of systematically gathering and analyzing information for making private and public marketing decisions. Covers the cost and value of information, research design, information collection, measuring instruments, data analysis, and marketing research applications.
Join Professor Rachel Chen and current students for the Managing for Operational Excellence course.
Tuesdays from 9:00 a.m. to 11:50 a.m.
Explores operations in manufacturing and service sectors from both inside and outside a company. Quantitative methods and their organizational implications are also examined.
Join Professor Ayako Yasuda and current students for the Venture Capital and the Finance of Innovation course.
Thursdays from 12:10 p.m. to 3:00 p.m.
This course examines VC finance and the related practice of R&D finance. The goal of the course is to apply finance tools and framework to the world of venture capital and financing of projects in high-growth industries.
Join Executive in Residence Jim Olson and current students for the Teams and Technology course.
Wednesdays from 6:30 p.m. to 9:30 p.m.
This course teaches the theory and processes of group and team behavior so that you can successfully manage groups and work effectively in a variety of group settings. The first goal of the course is to provide conceptual guidelines for analyzing and diagnosing group dynamics and determining one’s strategic options as a manager. The second goal is to understand how technological change affects team processes in organizations. Finally, this course will impart practical interpersonal skills for implementing effective strategies for group situations. The course is intended for students who seek greater understanding of teams and who wish to increase their competence in managing and working effectively in these contexts. Enrollment Prioity given to second year students.
Join Professor Chih_Ling Tsai and current students for the Time Series Analysis and Forecasting course.
Wednesdays from 9:00 a.m. to 11:50 a.m.
Helps managers face problems of forecasting the future value of external and internal factors such as product demand, input prices, inventory levels, interest rates, advertising budgets, etc. Covers techniques to aid in this task, including time series analysis, which is the statistical analysis of past data series to produce forecasts for future values of the series. Covers methods such as exponential smoothing, Box-Jenkins modeling, seasonal adjustment, decomposition, curve fitting and multiple regression. Both the statistical principles and the practical details of these methods will be addressed. In addition, business studies homework and a project are assigned to enhance the abilities of empirical data analysis.