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atmos:data_skills_pathway:home [2026/09/01 20:49] – [What you will do (in 4 stages)] marwaatmos:data_skills_pathway:home [2026/09/04 21:15] (current) – [Workspace Links] marwa
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 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**. 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]]+**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]] 
 +  * [[https://drive.google.com/file/d/121WGE89vhB0Va0-kAzyQsY9fnPO29bTj/view|WDAY TV Story Clip (January 24, 2026): Launch of Data Skills Pathway]]
  
 ===== Why is the Pathway unique? ===== ===== 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 start with a topic that interests you.** You work with mentors to turn your interest into a real problem that can be explored using data
-  * **You connect to live systems and real events.** You’ll interpret measurements and patterns tied to actual conditions (not made-up examples)+  * **You work with real data, not textbook-perfect data.** You learn how to check data quality, organize files, document your process, and make careful conclusions. 
-  * **You produce a portfolio-ready mini-project.** You finish the semester with deliverables you can show to an employer or internship mentor+  * **You learn the full workflow end-to-end.** From defining a question and finding data → to analysis and visualization → to clear communication. 
-  * **You can bridge into paid research internships.** Strong performance can lead to paid research work and future opportunities.+  * **You connect your work to real research and applications.** You may work with data related to weather, aviation, aerospace, sensors, engineering, cybersecurity, Artificial Intelligence, or other applied research areas. 
 +  * **You share progress during weekly meetings.** You present short updates, figures, papers, questions, challenges, or early results and learn from other students. 
 +  * **You learn useful tools from mentors.** Mentors may provide short sessions on Python, Excel/CSV files, data cleaning, visualization, reading papers, Artificial Intelligence, sensor data, or scientific communication
 +  * **You produce a portfolio-ready mini-project.** You finish the semester with something useful, such as a figure, table, script, notebook, dataset summary, short report, poster, or presentation
 +  * **You can bridge into paid research and internships.** Strong participation can help prepare you for paid research workfuture internships, and other research opportunities.
 ===== What You Will Do: Four Stages ===== ===== What You Will Do: Four Stages =====
  
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 This experience can help students prepare for undergraduate research, paid internships, graduate school, technical careers, and future work in data-driven fields. This experience can help students prepare for undergraduate research, paid internships, graduate school, technical careers, and future work in data-driven fields.
-===== 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. 
  
 +===== What Is Expected of Fellows? =====
 +
 +Data Skills Pathway Fellows are expected to participate actively, communicate clearly, and make steady progress on a data-based project.
 +
 +Fellows do not need to begin the pathway as experts. The goal is to learn by doing, with support from mentors, instructors, and other students.
 +
 +Fellows are expected to:
 +
 +  * Attend Data Skills Pathway meetings when possible.
 +  * Share their interests, project ideas, questions, and progress with the group.
 +  * Work with a mentor to turn an interest into a realistic data-based problem.
 +  * Complete or update their Student-Mentor Workspace.
 +  * Prepare a learning plan, work schedule, and short project brief.
 +  * Communicate with their mentor and ask questions early when they are stuck.
 +  * Bring evidence of progress to check-ins, such as a plot, table, script, notebook, paper summary, error message, or draft output.
 +  * Document their work regularly, including tasks completed, methods used, files created, results, quality checks, and next steps.
 +  * Keep project files organized using clear file names, approved storage locations, and good version-control habits.
 +  * Follow research integrity rules, including honesty with data and results, proper credit, and team rules for sharing project materials.
 +  * Participate in short tool sessions and apply those skills to their own project.
 +  * Prepare a final project update, presentation, poster, short report, figure, script, notebook, dataset summary, or other useful project output.
 +
 +Fellows should come to weekly meetings prepared to answer three simple questions:
 +
 +  * What did I complete this week?
 +  * What question, challenge, or blocker do I have?
 +  * What is my next step?
 +
 +By the end of the pathway, each Fellow should have made progress on a real project, learned practical data skills, and created something useful that can support future research, internships, graduate school, or technical career opportunities.
 ===== Interested? ===== ===== Interested? =====
   * [[atmos:data_skills_pathway:students|For Students]]   * [[atmos:data_skills_pathway:students|For Students]]
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 ===== On-boarding Documents ===== ===== On-boarding Documents =====
   * {{:atmos:data_skills_pathway:Undergraduate-Expectations-Guide.pdf|Expectations Guide 2026 (PDF)}}   * {{:atmos:data_skills_pathway:Undergraduate-Expectations-Guide.pdf|Expectations Guide 2026 (PDF)}}
-  * {{:atmos:data_skills_pathway:DataSkillsPathwayParticipantGuide.pdf|Participant Guide 2026 (PDF)}}+  *{{:atmos:data_skills_pathway:data_skillspathwayparticipantguide.pdf|Data Skills Pathway Participant Guide - Fall 2026}}
  
 ===== Pathway Fellows/Mentors ===== ===== Pathway Fellows/Mentors =====
 ==== Workspace Links ==== ==== Workspace Links ====
-  * [[atmos:dsp:workspace|The Student- Mentor Workspace Organization & Structure]]+  * [[atmos:dsp:workspace|The Student- Mentor Workspace]] 
   * [[atmos:data_skills_pathway:workspace:projects|Data Skills Pathway Projects]]   * [[atmos:data_skills_pathway:workspace:projects|Data Skills Pathway Projects]]
-  * [[atmos:dsp:Students Workspace|Data Skills Pathway Fellows (Students)]] +  * [[atmos:dsp:List of Data Skills Pathway Student Participants]] 
-  * [[atmos:dsp: Mentor Workspace |Data Skills Pathway Mentors]]+  
 ==== Other Links ==== ==== Other Links ====
   * [[atmos:home|Atmos Home]]   * [[atmos:home|Atmos Home]]
atmos/data_skills_pathway/home.1788295749.txt.gz · Last modified: 2026/09/01 20:49 by marwa