BUS 36 — Data-Driven Leadership: Managing and Guiding Data Teams
Quarter: Spring
Instructor(s): Jeremy Gu
Date(s): Apr 16—Jun 4
Class Recording Available: Yes
Class Meeting Day: Wednesdays
Class Meeting Time: 7:00—8:30 pm (PT)
Tuition: $555
Refund Deadline: Apr 18
Unit(s): 1
Enrollment Limit: 50
Status: Registration opens Feb 24, 8:30 am (PT)
Quarter: Spring
Day: Wednesdays
Duration: 8 weeks
Time: 7:00—8:30 pm (PT)
Date(s): Apr 16—Jun 4
Unit(s): 1
Tuition: $555
Refund Deadline: Apr 18
Instructor(s): Jeremy Gu
Enrollment Limit: 50
Recording Available: Yes
Status: Registration opens Feb 24, 8:30 am (PT)
This course is designed to empower decision-makers to effectively lead and manage data teams, regardless of prior data science experience. Whether you’re a marketing manager optimizing campaigns, a finance controller focused on forecasting, or a product leader building strategies, you will gain essential skills to make impactful decisions while enhancing your leadership capabilities through a deeper understanding of data and analytics.
You’ll learn to coach teams and collaborate with cross-functional stakeholders, leveraging data more effectively. By clarifying which types of data to collect and analyze, you will be equipped to ask insightful questions and craft compelling narratives that drive informed decision-making.
The practical modules cover the entire data lifecycle—collection, processing, analysis, reporting, and deployment. Key areas include identifying critical metrics in large advertising data sets, extracting insights from limited investment data, and analyzing online experiments. Additionally, students will learn to interpret and adapt data strategies in compliance with regulatory requirements, ensuring practices align with industry standards and organizational values.
You’ll learn to coach teams and collaborate with cross-functional stakeholders, leveraging data more effectively. By clarifying which types of data to collect and analyze, you will be equipped to ask insightful questions and craft compelling narratives that drive informed decision-making.
The practical modules cover the entire data lifecycle—collection, processing, analysis, reporting, and deployment. Key areas include identifying critical metrics in large advertising data sets, extracting insights from limited investment data, and analyzing online experiments. Additionally, students will learn to interpret and adapt data strategies in compliance with regulatory requirements, ensuring practices align with industry standards and organizational values.
This is a project-based course featuring real-world business cases. It focuses on applying analytical thinking to enhance the data skills essential for managers, rather than delving into mathematics or coding.
JEREMY GU
CEO and Founder, AI Strategy and Education
Jeremy Gu is an adjunct professor at the University of San Francisco and the CEO and founder of AI Strategy and Education. He is the former director of data science at Shipt, and he has worked at Uber, Amazon, and Stitch Fix. He has overseen teams in risk assessment, supply chain optimization, logistics, personalized ads, financial modeling, sales operations, and online experimentation platforms. At Uber, he was part of the strategic finance team and participated in the company's pre-IPO process, and he was one of the first data scientists at Amazon Web Services. He received an MS in statistics from the University of Washington. Textbooks for this course:
(Recommended) Harvard Business Review, HBR Guide to Data Analytics Basics for Managers (ISBN 978-1633694286)
(Recommended) Russell Dawson, Fundamentals of Data Analytics: Learn Essential Skills, Embrace the Future, and Catapult Your Career in the Data-Driven World (ISBN 979-8868358555)
(Recommended) Russell Dawson, Fundamentals of Data Analytics: Learn Essential Skills, Embrace the Future, and Catapult Your Career in the Data-Driven World (ISBN 979-8868358555)