Archive

Foundational residential intensive for the IDBT program — team practices, critique culture, and integration across disciplines.

Foundational business concepts for designers and technologists — accounting, finance, strategy, and organizational structure.

Research methods, design processes, and critical perspectives — the course that produced the CRISPR bioethics essays.

Creative technology foundations — web development, HTML/CSS/JS, design tools, and the "Aurora" animated landing project.

Product opportunity framing under uncertainty — customer discovery, prototyping, and the Lunchbox + Discord studio projects.

Python fundamentals and applied machine learning with Prof. Michael Crowley — the original MI course site is preserved at /archive/machine-intelligence/.

Community design and applied workshop practice — producing a playbook meant to be run by others.

Machine learning fellowship and ML Innovators certification (Jan 2022) — deep-learning foundations and applied ML project work.

USC Marshall marketing analytics — customer segmentation, k-means clustering, and decision-support analysis for marketing problems.

Warehousing architectures, BI tooling, and data mining patterns — the bridge between raw data pipelines and business decisions.

USC HIPAA Privacy Education Program certification (5/31/2022) — healthcare information privacy and compliance fundamentals.

IP law foundations — patent, copyright, trademark, and right-of-publicity issues relevant to designers, founders, and technologists.

Second residential intensive — professional practices, portfolio critique, and cross-disciplinary integration.

Multi-course integrative research project — the SYZYGY JMP statistical analysis work emerged from this course.

Independent research with faculty supervision — the Peloton customer-behavior and pandemic-data-patterns essay came from this term.

Stanford Online course covering descriptive statistics, probability, inference, regression, ANOVA, and categorical analysis.

Culminating M.S. IDBT capstone project — synthesizing design, business, and technology into an integrative final deliverable.

Large-scale data engineering and analysis — distributed processing, scalability, and production-grade data workflows.

Project-management methods, scoping, risk, and delivery discipline across operational contexts.

Programming foundations for data science — produced the Peloton Customer Churn Analysis project.

Cloud infrastructure, operations architecture, and advanced operational topics.

Computational thinking for data science — produced the USDA Food Access Research Atlas project on North County San Diego food deserts.

Applied business analytics — optimization, simulation, and data-driven decision frameworks for operations.