National Center for Ecological Analysis and Synthesis

About Us

Vision & Mission

LH logoWe aim to create a culture in which all researchers are empowered to solve the pressing environmental issues of our time using inclusive, collaborative, open, and reproducible data science tools. To achieve this, we teach essential data science skills to a diverse array of environmental researchers through hands-on trainings.

Teaching Philosophy & Instructors

  • Halina Do-Lihn delivers a training to coreR participants at NCEAS, April 2023.

    Our Approach

    We’re committed to building a welcoming learning environment that makes stepping into the world of data science accessible and less intimidating. Our approach breaks down step-by-step reproducible and collaborative best practices using tools like R and GitHub. We believe that anyone working with data can benefit from these tools.

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    Hands-On Learning

    Our courses blend technical and non-technical sessions with hands-on practice, covering the essential principles of data management, reproducible workflows, and open data science. In our technical lessons, we primarily teach through live coding, where participants code along with the instructor in real time. We find that live coding helps participants build "coding muscle memory" that can be invaluable as they develop their programming skills.

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    Self-Paced Sessions

    We also include dedicated practice sessions, allowing participants to work at their own pace to solve guided questions. These sessions offer the chance to integrate and apply the various concepts taught throughout the course, reinforcing a holistic understanding.

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    Our Instructors

    Our courses are taught by experienced NCEAS residents who regularly use the tools we teach to explore, clean, analyze, and visualize data.

A Community of Data Science Educators

We collaborate with different initiatives within NCEAS that teach data science to researchers. 

Data Science Communities & Initiatives

Data Science can be intimidating to go through by yourself. Fortunately, there are great data science communities out there that aim to make this journey welcoming and feel supported.

Here are some groups we follow: