Table of Contents
The Data Skills Pathway Workspace
Project Overview
The Data Skills Pathway is a 15-week, hands-on experience where you learn how to turn real-world data into real-world decisions. You’ll build practical skills using raw datasets from instruments and models. The pathway is designed to build skills aligned with roles such as data analyst, meteorologist, operations analyst, and environmental/aviation data technician.
Media: UND Today press release: UND launches Data Skills Pathway to prepare students for AI-age careers
Why is the Pathway unique?
- You work with real data (not textbook-perfect data). You learn how to check data quality, document your process, and make defensible conclusions.
- You learn the full workflow end-to-end. From organizing files and logging metadata → to analysis → to clear communication.
- You connect to live systems and real events. You’ll interpret measurements and patterns tied to actual conditions (not made-up examples).
- You produce a portfolio-ready mini-project. You finish the semester with deliverables you can show to an employer or internship mentor.
- You can bridge into paid research + internships. Strong performance can lead to paid research work and future opportunities.
What you will do (in 4 stages)
- Weeks 1–2 | Orientation
- Learn what “data jobs” look like and how this pathway maps to real careers
- Set your goals and choose a project direction
- Weeks 3–4 | Tools + programming workshop
- Learn the core tools used across projects (data handling, plotting, basic scripting)
- Build good habits for clean, reproducible work
- Weeks 5–10 | Guided data work
- Work on a mentor-suggested project using real datasets (instruments and/or model output)
- Keep a clear data log + weekly progress log
- Get mentor feedback each week
- Weeks 11–15 | Capstone mini-project
- Answer a focused question with data
- Create your final deliverables (report + slides + reproducible workflow)
What is expected of Fellows?
- Commit weekly time and make steady progress.
- Meet with your mentor regularly and come prepared with updates + questions.
- Communicate early if you are stuck or your schedule changes.
- Document your work every week:
- Weekly progress log
- Data/model log (what data you used + what you changed)
- Reproducible scripts/notebooks + labeled figures
- Complete the pre- and post-surveys to help evaluate and improve the pathway.
- Finish the required deliverables: short report + short slides + a complete project folder that reproduces your results.