From Data Training to Research Experience: NCLab and EPSCoR HDRFS Strengthen Nevada’s Data Talent Pipeline

NCLab’s partnership with the NSF EPSCoR HDRFS (Harnessing the Data Revolution for Nevada Fire Science) project is helping Nevada students build practical data skills and apply them in research settings.

Through this partnership, students gain hands-on training in data analytics, SQL, Python, Spreadsheets, and related computational skills. The program is designed to help students from a range of academic backgrounds build confidence with data tools that are increasingly important across research, environmental science, engineering, computer science, and other data-driven fields.

The final cohort for this program is in progress right now, with learners approximately halfway through the program material. Students in this program have the opportunity at the end of the summer to apply for a research internship with various college professors across the Nevada System of Higher Education (NSHE) ecosystem.

With the skills they learn through NCLab, student feedback is clear that the NCLab training section has helped them both solidify their career goals and gain confidence in their ability to utilize data. In survey responses, students described increased confidence using data analytics tools to solve real-world problems, stronger familiarity with SQL and Python, and a clearer understanding of how data skills could support their future work.

One student shared that the program changed how they viewed data science:

“I always thought data science was kind of scary or boring or tedious, but this program showed me that it’s really just as interesting as everything else about computer science that I loved.”

Another student connected the training directly to research and graduate study:

“This program helped me learn how I can work with large data structures using PostgreSQL, where I hope to use this skill in my future research projects.”

The results of the program show strong training-to-internship pathway outcomes. Across the most recently completed TMCC EPSCoR cohorts, 80% of students completed NCLab training. In those same 2024 and 2025 cohorts, 85% of internship applicants received EPSCoR research internship placements, including a 100% internship placement rate among 2025 applicants.

Graduates of the training section also described the knowledge gained as useful even beyond direct internship application. One participant wrote:

“The data analytics training is not only useful to present meaningful skills to employers, but it also develops a new perspective on solving real-world problems through programming.”

Others connected the program to engineering coursework, lab research, data science, machine learning, actuarial work, and environmental research. One student noted that the program helped them feel more comfortable working with large datasets in a current internship. Another said they planned to use SQL to compile and clean data in the lab where they were working.

The program’s support structure also played an important role. Students highlighted the NCLab-provided coaching as a source of accountability, encouragement, and one-on-one support. Many balanced the self-paced, online training with school, work, research, family responsibilities, and other commitments. Several students described coaching check-ins as helpful for staying on track, getting feedback, and feeling supported while working through challenging material.

Aligned with the goals of NSF EPSCoR, this partnership helps broaden access to data education and applied research opportunities for students across Nevada. By combining hands-on technical training, coaching, and internship pathways, NCLab and EPSCoR HDRFS are helping students build the skills and confidence needed to contribute to Nevada’s growing data workforce.

NCLab is proud to have supported this partnership over the past 5 years and is open to partnership for similar opportunities that wish to connect students to practical data skills, applied research experiences, and future pathways in science, technology, and data-driven problem solving.