This cohort holds bi-weekly meetings at 7pm EDT on Tuesdays. Optional code help & bird talk sessions will be schedule weekly.

Weekly meeting dates: Sep 22nd, Oct 6th, Oct 20th, Nov 3rd, Nov 17th. Meetings are recorded so missing out on one is OK!

Course registration price is now sliding scale. Use the codes TEN, TWENTY, THIRTY, FORTY, FIFTY or SIXTY for the corresponding percentage discount. These workshops support my art practice and pay my rent - but I don't want anyone to feel left out for financial reasons.

Birding and Data Viz, Together At Last!

I dreamt up Binoculars to Binomials as a hybrid site of learning. It's for coders who are interested in cultivating an observational practice, and for birders who want to dive into the rich pool of data that comes out of their hobby.

More broadly, it's for anyone who's interested in the overlap between nature, data and creativity.

In this 10-week 5 module cohort course, you'll join a group of curious learners to explore the opportunities that lie between birdwatching and creative coding.

Learn how to build a practice of noticing, understand the ways that observations become data, and explore creative pathways for telling bird-y stories with code.

We'll explore:

• How to access and use rich sources of birding data including the eBird API, XenoCanto, The Christmas Bird Count historical database, and more.
• Ways to cultivate and enrich an observational practice (birding!), and how to apply the techniques from this practice to other parts of your life
• Methods for creating dynamic data visualizations on the web (not just charts and graphs!), as well as more radical forms of data representation (sound, sculpture, performance, public engagement!)
• Histories and practices of counting and tracking birds, from banding to satellite tracking and AI modeling
• Methodologies for collecting our own bird-based data including observations of behavior and recording of nocturnal flight calls

Course Outline

Module 1: Fledge Week

Birdwatching is closely bound to the enumeration of birds and the keeping of lists. In this module we'll examine several bird counting projects (past and present) and will use discussions about feeder-watching to discuss what different methods of counting necessarily include and exclude. We'll also see and discuss a series of data visualizations and other artworks and interventions based on bird data.

Module 2: How Birds Become Data

On October 8th, 2015, a team in Ecuador identified 431 species of birds – the world record for number counted in a single day. Earlier that year in Myanmar, a scientist counted one Jerdon’s babbler, the first in nearly eight decades. In December of 2019, eBird announced that its database held over 737 million bird observations. This morning, in Brooklyn Bridge park, I counted 38 house sparrows, 4 black-and-white warblers and an ovenbird. In this module, we'll look at the myriad of ways birds become data. We'll look at a variety of publicly available datasets, and we'll examine the complications of turning the messy human act of observation into 'clean' data points.

Module 3: Tweets, Chirps & Chips

Birding is as much an auditory experience as it is a visual one. Indeed, some behaviours of birds can only be observed by listening. In this module we'll learn ways to describe bird calls, and we'll find out how to access huge databases of bird sounds. We'll take a deep-dive into Nocturnal Flight Calls - the sounds that birds make when migrating high in the air at night. We'll look at techniques for DIY 'nocmig' setups and see how we can record and analyze these unique calls from our very own rooftops / fire escapes / backyards.

Module 4: Satellites & Radar and Radio (oh my!)

Every day during the spring and fall migrations in North America, BirdCast provides real-time analysis maps showing intensities of actual nocturnal bird migration as detected by the US weather surveillance radar network between local sunset to sunrise. In addition, it provides advance forecasts for migration in regions across the country. These forecasts are the product of a machine learning system trained on 23 years of bird movements in the atmosphere as detected by the US NEXRAD weather surveillance radar network. BirdCast is just one example of how birds are being tracked and monitored. In this module we'll learn how radar and radio is used to locate birds in various contexts. We'll also look at sources for bird mobility data and learn techniques for visualizing position over time.

Module 5: Birding Backwards

Want to go birding at the museum? In this module we'll look at how historical records can provide glimpses of the biodiversity of the past, and how narratives of collection and exploration are often anchored in colonialism and exploitation. We'll find some historical datasets and learn how to visualize the data; we'll also look at possibilities for linking datasets together, past --> present!

Structure

Each Module's learning modules include a one hour video lesson (pre-recorded), one coding and one birding assignment, as well as code samples with video walkthroughs and a wealth of other resources.

Bi-weekly group discussions and open help sessions offer opportunities for collaborative learning, and the course platform is open for use throughout the cohort period.

Participants will be expected to go birding (self-directed) at least two times per week throughout the course. Binoculars are required.

If you have accessibility needs or concerns, please contact me directly.

Duration: 10 weeks

Cohort size: 18 people

Workload: 5-7 hours per two week module

Is this course right for you?

This course is open to beginner birders and beginner coders. Lessons about coding and birding are aimed toward the motivated newbie.

Code examples are designed so that beginners can tweak and play, whereas more advanced coders can use them as starting blocks for bigger things.

Similarly, birding assignments are aimed at people who are new to watching birds. But they also offer ways for experienced birders to rethink and reinvigorate their practice.

Still not sure? Get in touch.

About the Instructor

Jer Thorp is an artist, a writer, and a teacher. He was the first data artist in residence at The New York Times, he is a National Geographic Explorer, and he served as the innovator in residence at the Library of Congress in 2017 and 2018. He lives under the Manhattan Bridge with his family and his awesome dog, Sandwich. Since 2010 he has been an adjunct professor at NYU's ITP program, where he has taught a wide range of classes about data, archives, and public engagement. Previous to ITP he taught at Langara College and the University of British Columbia.

Jer's first book, Living in Data, was published by MCDxFSG in 2020. His next book, We Were Out Counting Birds, is out in 2025.