BUS 41 — Data Science Essentials for Business Managers
Quarter: Winter
Day(s): Wednesdays
Course Format: On-campus (About Formats)
Duration: 10 weeks
Date(s): Jan 17—Mar 20
Time: 7:00—8:50 pm (PT)
Refund Deadline: Jan 19
Units: 2
Tuition: $715
Instructor(s): Peter Lou
Limit: 50
Class Recording Available: No
Status: Open
Winter
On-campus
Wednesdays
7:00—8:50 pm (PT)
Date(s)
Jan 17—Mar 20
10 weeks
Refund Date
Jan 19
2 Units
Fees
$715
Instructor(s):
Peter Lou
Limit
50
Recording
No
Open
Customer insights, operational efficiency, and product innovation are all driven by one thing: data. As a result, every company today must be a data company to compete. The change sets a new precedent that data science skills are no longer a “nice to have” but a “must have.”
This course will familiarize business managers, small-business owners, and those interested in advancing their data analytics skills with essential data science concepts for data-related managerial roles. The course will teach students to leverage data insights to make informed decisions and drive business success for various scenarios, including predictive analytics, business forecasting, product profitability, risk profiling, etc. Students will learn these skills by analyzing data sets using data-related tools such as advanced Excel functionality, Python, and SQL. Upon completion, students will understand the basic concepts and techniques of data science, including data mining, data analysis, and statistical inference, the process of using a sample to infer the properties of a population. Students will also learn how to communicate data insights to stakeholders using data visualization techniques, transforming raw data into visual formats that are easier to understand and interpret. This course will allow students with nontechnical backgrounds to elevate their data proficiency and stand out in the competitive business world.
This course will familiarize business managers, small-business owners, and those interested in advancing their data analytics skills with essential data science concepts for data-related managerial roles. The course will teach students to leverage data insights to make informed decisions and drive business success for various scenarios, including predictive analytics, business forecasting, product profitability, risk profiling, etc. Students will learn these skills by analyzing data sets using data-related tools such as advanced Excel functionality, Python, and SQL. Upon completion, students will understand the basic concepts and techniques of data science, including data mining, data analysis, and statistical inference, the process of using a sample to infer the properties of a population. Students will also learn how to communicate data insights to stakeholders using data visualization techniques, transforming raw data into visual formats that are easier to understand and interpret. This course will allow students with nontechnical backgrounds to elevate their data proficiency and stand out in the competitive business world.
PETER LOU
Vice President of Advanced Analytics, Wells Fargo
Peter Lou has held positions in the Wells Fargo Management Science Division as well as the Wholesale Business Architecture and Wealth & Investment Management Groups. He previously worked as a senior analytics manager and senior management consultant at Union Bank’s Corporate Portfolio Analytics & Modeling Group and at Ernst & Young. He has been a chartered financial analyst (CFA) since 2000. He received an MBA from the University of Illinois Urbana-Champaign. Textbooks for this course:
(Required) James R. Evans, Business Analytics, Third Edition (ISBN 978-1292339061)