Lectures

Lecture 7-1: Communicating the Data Summary

Week 7 (M2 Data Summary): how to communicate a technical data summary in both the write-up and the poster session. We cover tailoring the same material to audiences at very different levels, the four things every data summary must convey (the data, the process, integrity, reproducibility), drawing data architecture diagrams with worked examples, write-up dos and don’ts, presenting at the poster session, and making your data pipeline knowledge stand out.

Jun 22, 2026

Lucas P. Cordova, Ph.D.

Week 6: Roadmap, Planning Rituals, and the Data Story

DATA 510: Data Science Capstone

Week 6, in the gap between the approved proposal (M1) and the Data Summary (M2). A 60-minute briefing in three parts. The Roadmap: where each milestone becomes a section of the final write-up, reviewed by me and your peer POs, and what the Data Summary requires. Planning Tonight: how iterations are sized to each milestone, how studios run at milestone boundaries, and how to run tonight’s first 20-minute planning session on the board and in the repo. The Data Story: told as a user story and built on a write-up skeleton you grow milestone by milestone.

Jun 15, 2026

Lucas P. Cordova, Ph.D.

Week 5: Technical Writing with Quarto

DATA 510: Data Science Capstone

Week 5: why Quarto for capstone technical writing, logistics from M1 proposal through M4/M5 write-ups, installation via VS Code and the command line, hands-on Quarto essentials for R users, and a teaser on portfolio sites. Includes a copy-paste write-up skeleton for deliverables/M4-writeup-draft/.

Jun 8, 2026

Lucas P. Cordova, Ph.D.

Week 5: Introduction to Using Git

DATA 510: Data Science Capstone

Week 5 companion session: Git for DS3 capstone repos. Deliverable formats (Quarto encouraged, PDF milestones always accepted), solo and team workflows, install on macOS and Windows, clone, commit, push, collaborating on shared files, merges, a brief intro to branches and pull requests, and a hands-on exercise: render the write-up skeleton to PDF, push to GitHub, and submit on Canvas.

Jun 8, 2026

Lucas P. Cordova, Ph.D.

Week 4: Proposal Critiquing

DATA 510: Data Science Capstone

Week 4: how to critique an M1 project proposal using the official rubric and required sections. In-class activity: solo read of a practice Oregon wildfire-smoke proposal, group critique and report-out, Canvas participation roster. Prepares you for your own proposal due this week.

Jun 1, 2026

Lucas P. Cordova, Ph.D.

Week 3: DS3 Framework

DATA 510: Data Science Capstone

Week 3 framework briefing. A guided tour of Data Science Studio Scrum (DS3): why it exists, how the studio and dual-role membership work, the six artifacts, the five-column Iterative Development board, the weekly Studio Session, the Brief / Critique loop and SLAs, and the operational tooling (GitHub repo, Projects board, Discord). Closes with a pre-flight for tonight’s Studio Charter activity so we can transition straight from this deck into chartering.

May 25, 2026

Lucas P. Cordova, Ph.D.

Week 2: Data Science Research Methods

DATA 510: Data Science Capstone

First in a recurring series on data science research methods and technical writing. Overview of how capstone-grade research is framed, the PRIDE problem-to-question workflow, criteria for strong research questions, and an in-class paper critique activity in eight groups.

May 18, 2026

Lucas P. Cordova, Ph.D.

Week 2: Project Forming

DATA 510: Data Science Capstone

Second block, week 2: capstone requirements and milestone placement, a second pass on project brainstorming and PRIDE-sharpened research questions with peer review, introduction to the Data-Driven Scrum operating model for solo and team work, and a Canvas snapshot of project domain, stakeholders, questions, and teaming intent.

May 18, 2026

Lucas P. Cordova, Ph.D.

Lecture 1-1: Course Overview

DATA 510: Data Science Capstone

Orienting lecture for DATA 510: catalog goals, grading components and weights, milestone and weekly deliverable schedule, Data-Driven Scrum methodology, meta-project clusters, late policy, attendance and integrity expectations, and workload norms aligned with the published syllabus.

May 11, 2026

Lucas P. Cordova, Ph.D.

Lecture 1-2: Research vs EDA

DATA 510: Data Science Capstone

Contrasts exploratory data analysis with formal research questions for capstone work: when to wander the data, when to commit to a testable claim, common research-question types, and how the two modes reinforce each other without p-hacking.

May 11, 2026

Lucas P. Cordova, Ph.D.

Lecture 1-3: Project topic and domain brainstorming

DATA 510: Data Science Capstone

In-class networking and writing activity: students anchor their own interests and definition of impact, hold structured conversations with several classmates, then reflect on feedback and possible teammates. Delivers a single submission document aligned with early capstone teaming and topic exploration.

May 11, 2026

Lucas P. Cordova, Ph.D.