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====== The Data Skills Pathway Workspace ======

{{:atmos:data_skills_pathway:dataskillspathway_under2mb.jpg?680|}}

===== 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:** [[https://blogs.und.edu/und-today/2026/01/und-launches-data-skills-pathway-to-prepare-students-for-ai-age-careers/|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.

===== Interested? =====
  * [[atmos:data_skills_pathway:students|For Students]]
  * [[atmos:data_skills_pathway:mentors|For Mentors]]

===== On-boarding Documents =====
  * {{:atmos:data_skills_pathway:Undergraduate-Expectations-Guide.pdf|Expectations Guide 2026 (PDF)}}
  * {{:atmos:data_skills_pathway:DataSkillsPathwayParticipantGuide.pdf|Participant Guide 2026 (PDF)}}

===== Pathway Fellows/Mentors =====
==== Workspace Links ====
  * [[atmos:dsp:workspace|The Student- Mentor Workspace Organization & Structure]]
  * [[atmos:data_skills_pathway:workspace:projects|Data Skills Pathway Projects]]
  * [[atmos:dsp:Students Workspace|Data Skills Pathway Fellows (Students)]]
  * [[atmos:dsp: Mentor Workspace |Data Skills Pathway Mentors]]
==== Other Links ====
  * [[atmos:home|Atmos Home]]
  * [[wiki:syntax|DokuWiki Syntax]]
  * [[https://blogs.und.edu/und-today/2026/01/und-launches-data-skills-pathway-to-prepare-students-for-ai-age-careers/?utm_source_platform=mailpoet|UND launches Data Skills Pathway to prepare students for AI-age careers]]
  * [[http://www.openscienceassociates.com/delene/|David Delene's Home Page]]
  * [[http://www.openscienceassociates.com/delene/AtSc494_Spring2026/index.html|AtSc 494 - Spring 2026]]