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Presented By: Michigan Institute for Data Science

Environmental Data Science Summer Academy 2023

MIDAS Summer Academies 2023

Treetops seen from the ground Treetops seen from the ground
Treetops seen from the ground
 ANGELA BENITO on Unsplash
Registration is now closed.

Monday July 31 – Friday, August 4
For faculty, postdocs, and staff; in-person at U-M Ann Arbor campus

For more information, please visit our event page here:

Our summer academies equip researchers with the essential skills required to apply advanced data science techniques to their respective fields of study and integrate these methodologies into their grant proposals. The overarching objective of these academies is to foster a research community that can drive the advancement of data science applications in a wide range of research fields.


Strategies for integrating data science into grant applications
Basics of Machine Learning
Encompasses environmental, climate, earth sciences, and ecology


Certificate of completion
Ability to communicate a breadth of data science topics with experts
Skills to abstractly consider data science solutions and apply them to environmental problems

Tuition cost:
We will send payment instructions along with acceptance decisions.

$3,000 for external participants (30% discount for U-M Alums)
Thanks to support from the University, we are able to offer a reduced price of $100 for U-M personnel and students

Registration Timeline:
Registration closes on June 8. Later registrants will be accepted only if spots are available.

Cancellation Policy:
>14 days before the first day: full refund minus $50 processing fee
Cancellation between 7 and 14 days of the first day: 50% refund
Less than 7 days: no refund

Who should attend:
This academy workshop is open to all U-M and external environmental scientists, but the content is geared towards junior faculty members and those from the public and private sector who are interested in learning about incorporating data science into their research.

College-level math or statistics. No previous coding experience is required. Students are expected to bring a laptop for programming components of the workshop.

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