Forecasting the World and Your Business

MGMT X 477.88

This course illustrates the underlying trends and cycles of global economies and covers the forecasting methods and tools for analyzing the data that impacts company revenues, expenses, strategies, and competitive positions.

READ MORE ABOUT THIS COURSE

What you can learn.

  • Explore regional and international economies, stock markets, interest rates, housing markets, and employment rates
  • Understand the state and prospects of the economy, key business sectors, and "best practices" skillsets of the Anderson Forecast to analyze your own company's data

About this course:

This course, originally designed by UCLA Anderson Forecast, provides the practical knowledge of the underlying trends and cycles of global economies, U.S. businesses, global and U.S. industries, and their outlooks. It introduces to you useful and powerful methods and tools of analyzing marketplace data that impacts company revenues, expenses, growth strategies, and competitive positions. Topics include regional and international economies, stock markets, interest rates, housing markets, employment/unemployment, and additional macro-economic trends/considerations. Participants leave the course with an understanding of the state and prospects of the economy, key business sectors and--importantly--the "best practice" skillsets of the Anderson Forecast to analyze your own company's data as well as new investments risks.

Contact Us

Speak to a program representative. Hours: Mon-Fri, 8am-5pm.

This course applies towards the following certificates & specializations…

Ready to start
your future?
By signing up, you agree to UCLA Extension’s Privacy Policy.

vector icon of building

Corporate Education

Learn how we can help your organization meet its professional development goals and corporate training needs.

Learn More

vector icon of building

Donate to UCLA Extension

Support our many efforts to reach communities in need.

Innovation Programs

Student Scholarships

Coding Boot Camp

Lifelong Learning