Learn In-Demand Skills with Earth Data Science Workshops

The University of Colorado, Earth Lab offers earth data science workshops for students and professionals of all skill levels and backgrounds. In our workshops you will learn core programming and open reproducible science skills that will support your ability to work with environmental and earth systems data in collaborative team environments.

All skills taught in University of Colorado earth and environmental data science workshops are guided by industry research to ensure that you learn skills that are in-demand in the job market.

Our Workshops Are For You

Workshops are appropriate for anyone interested in improving their earth and environmental data science skills, from beginners to experts. Past attendees have come from government, academic, and corporate organizations. We present the concepts using real-world data and workflows common in the industry.

How You Will Learn

We teach our workshops using a cloud-based Jupyter Hub. This means that you do not need to have software installed on your computer to take our workshops. You just need a computer with internet access! However, if you do wish to setup your computer with the tools necessary to complete our workshops, you can do that as well.

Costs & Logistics

All workshops will be held in the Earth Analytics Visualization Studio located on east campus at the University of Colorado - Boulder. Rates range from $400-600 per day depending upon the content topic and level. Please contact us for specific rates. 

Get in Touch about Earth Lab Workshops

Workshop Topics

Introduction to Programming & Data Science

Time: 1-2 days

Level: Beginner. No experience necessary.

Skills Covered: In this workshop, you will learn to:

  • Use command line tools (e.g., Bash) to programmatically access and manipulate directories and files.
  • Write Python code to work with data (e.g., read files, analyze and plot data).
  • Use Jupyter Notebooks to organize and execute Python code.

Introduction to Version Control and Git for Data Science

Time: ½ day

Level: Beginner. No experience necessary.

Skills Covered: In this workshop, you will learn:

  • The basics of version control.
  • How to install and configure git on your computer.
  • Git and GitHub collaborative workflows (e.g. forking, cloning, committing, pushing, pull requests, and more).

Introduction to Clean Coding and the tidyverse in R

Time: ½ day

Level: Beginner/Intermediate. You should have some basic working knowledge of R to get the most out of this workshop.

Skills Covered: In this workshop, you will learn to:

  • Structure workflows with R projects.
  • Write expressive, well-organized code, and plan complex workflows using pseudo code.
  • Effectively design and manage workflows with many input and output files.
  • Use tidyverse to “munge” (e.g. sort, clean, group and summarize) tabular data.
  • Visualize data using ggplot2.

Introduction to Spatial Data Science Using Open Source Python

Time: 2 days

Level: Intermediate. You will get the most out of this workshop if you have some experience using Python. Specifically, you should know how to load packages and work with a numpy array. Experience with pandas is also helpful but not required.

Skills Covered: In this workshop, you will learn to:

  • Open, plot and manipulate vector data in Python using Geopandas.
  • Open, plot and manipulate raster data in Python using Rasterio.
  • Use Jupyter Notebooks to write code in Python.

Data Science Toolkit Workshop

Time: 4 days

Level: Beginner

Be ready to go for our Earth Analytics Data Science Bootcamp course (GEOG 4463/5463) with our Data Science Toolkit workshop, where you’ll learn how to get started with Google Colab and GitHub, download data, and get set up with the “earth analytics python” environment, Jupyter notebook and extensions, and more! This workshop is modeled off of The Carpentries Software Carpentry workshop and will feature similar content.

Skills Covered:

  • Getting started with Python
  • Intro to Google Colab
  • Installing GitBash, miniconda, Jupyter extension
  • Setting up Github & earth analytics python environment

Who We Are

We are a group of professionals with expertise in teaching and applying earth and environmental data science approaches to a variety of data types and formats. You will learn at a workshop built by professionals for professionals. All instructors have geospatial industry experience and know the skills necessary to succeed firsthand. Our focus areas include: Data Science, Education, Statistics, Machine Learning, Remote Sensing, Scientific Programming, Databases, Cloud Computing & more.

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