California State University: East Bay
MS in Business Analytics (2023 - ???)
Status: Dropped out to focus on learning the latest AI skills.
Why this decision?: It felt wrong working towards a credential, with class schedules that conflicted with my job, when I would rather focus my time on AI related bootcamps and meet ups, building skills to develop an enablement program at Cribl, taking product classes at Stanford, and doing some art projects. I followed my heart on this one and focused on analytics for MELT (Metric, Events, Logs, and Traces) at Cribl.
What’s next?: I am eyeing a few programs, when the time is right I’ll return to formal education.
Golden Gate University
B.S. Business Administration | Data Analytics (2019 - 2021)
Why so late ?: My entire career I’ve always taken classes, bootcamps, certification courses, and attended conventions. Everywhere I’ve lived I’ve signed up for Community College on day 0. Unfortunately, focusing on the skills you need to excel professionally sometimes means taking the path less credentialed. GGU had an excellent program for working adults that prepared me for a MS in Data Analytics - and it was a block from the ThousandEyes office.
Stanford Continuing Studies
Why this path?: Accomplished professionals dilute their experience, resource, and connections into a 6 week course that provides insights that are immediately applicable.
2025
Transforming Customer Experience with AI (BUS 129)
Generative AI for Product Managers (BUS 25)
Inception Workshop: Rapid Conceptualization of World-Class Products (BUS 194)
2021
Fundamentals of Monetization and Pricing Strategies (BUS 72)
Building and Scaling Subscription Businesses (BUS 78)
Corporate Strategy at Scale: How Companies and Economies Evolve (BUS 93)
Principles of Product/Market Fit (BUS 213)
2020
Fundamentals of Product Management (BUS 62 W)
The Alchemy of Leadership: Turning Stories into Gold (COM 49)
Design Research: Creating New Products and Market Success (DSN 106 W)
Building Innovative Teams (DSN 310 W)
Using Artificial Intelligence and Design Thinking in Product Development (SCI 66)
Design Thinking and Rapid Experimentation for Sustainable Innovation (BUS 99)
2019
An Introduction to UXDesign in Product Leadership and Management (BUS 57 W)
After the Insight: Mapping the Path from Idea to Product (BUS 255)
Data Analysis with Python (CS 65 W)
Coursera
Why this path?: I can audit courses during my commute on BART, while waiting at the dentist, or on a quiet morning before everyone else wakes up. Sometimes I actually finish the certification (see below) but I’ve left a trail of audited courses in my wake.
2025
AI Product Management | Duke University (working)
2021
Budgeting and Scheduling Projects
Managing Projects Risks and Changes
Initiating and Planning Projects
Analyzing and Visualizing Data in Looker
Innovating with Data and Google Cloud
Developing Data Models with LookML
2020
Using python to Access Web Data
2019
ABL - Always Be Learning
To improve my technical sales with ILECs / CLECs, I attended years of Cisco Academy training with Dallas College (El Centro), completing both the CCNA and CCNP programs. I also deployed Triple Play (IPTV, VoIP, Data) networks at VisionNet using KVM, IGMP compliant Cisco equipment, and open source solutions.
When I wanted to transition from ISP hardware to SaaS I studied Linux, virtualization, containerization, and SaaS architecture through personal projects (e.g. UI & web development), developer conferences (e.g. OpenStack), meetups (e.g. AWS Loft bootcamps).
When I wanted to learn graphic design, I started doing projects
When I wanted to learn about data analytics, I took courses on R, Python, Tableau, and visual communications (e.g. GGU, UC Berkeley Extension, Edward Tufte, Information is Beautiful).
When I wanted to learn about cybersecurity, I attended Defcon and other conventions as starting points.
When I wanted to learn about product development & service design, I took courses from Stanford continuing studies.
When I wanted to start my AI journey, I attended bootcamps (e.g. Anyscale + Pinecone), meetups, Stanford Continuing studies, and read everything I could find on O’Reilly and Arvix.
When I join a company I immediately start building test labs that I can use to better understand my customer’s challenges.
If you work with me, be prepared for annoying recaps of whatever I’m learning at the time as I will want to find ways to put that learning into practice :)