Artificial Intelligence/Machine Learning (AI/ML) in Space Biology Training (free, open, asynchronous)

As the field of space biology continues to generate vast amounts of data, the ability to effectively analyze and interpret this information is becoming increasingly essential. To meet this growing need, the “Artificial Intelligence/Machine Learning (AI/ML) in Space Biology Training” course has been developed to provide researchers with the skills needed to apply artificial intelligence and machine learning techniques to complex biological data. Designed as a self-paced, comprehensive online program, the course combines foundational knowledge in space biology with hands-on experience in data processing, machine learning model development, and bioinformatics.

Through the NASA TOPS-T ScienceCore grant awarded to the staff of OSDR and Space Biology, “AI/ML in Space Biology Training” is a comprehensive course designed to equip researchers with foundational skills in data analysis and machine learning tailored specifically for space biology. The course includes pre-recorded lectures, Python notebooks, and quizzes, and is offered as a self-paced online curriculum. In Module 1, participants will be introduced to the fundamental concepts of space biology, gain familiarity with Google Colab, and explore the basics of machine learning and space biology data. Module 2 focuses on practical data processing techniques, including working with tabular and image data, and visualizing datasets to uncover insights. Module 3 delves into building essential machine learning models, covering clustering, regression, and classification techniques. Participants will learn how to apply these models to analyze and interpret complex biological data. Finally, Module 4 emphasizes the importance of result interpretation through bioinformatic tools, explainable AI, and the principles of open science, ensuring that findings are transparent and accessible.

By the end of this course, learners will have a robust understanding of how to leverage AI and ML methodologies to advance space biology research, enhancing their ability to tackle complex biological questions in space environments. Enroll here:
https://canvas.instructure.com/enroll/8JYKD7

Special thanks to @james.casaletto for designing and leading the course! @AIMLawg @ALSDAawg @MultiOmicsAWG @MicrobesAWG @PlantAWG @AnimalAWG

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Just got myself enrolled. Thank you for sharing this! I know this will prove to be extremely helpful.

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Does it require basic bioinformatic skills to pursue this course?

I’ve started the course a couple of days ago. I think that is feasible also for students and entry-level researchers. It starts by explaining fundamental concepts of space biology and the basics of machine learning and space biology data.
Enroll and you’ll learn how to analyze and interpret complex biological data😊

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@james.casaletto or @lauren.sanders care to elaborate to the question from @anuiris ?

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Thank you @jessicadurbano for providing the course description and enrollment link. The course does not make any assumptions about previous background or experience beyond high school math. We taught this class over the summer to a cohort of 70 high school students and their background was sufficient. Please let us know @anuiris and @alavia if you disagree after taking the class.

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Thank you very much for your answer!

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Sure, thank you for your response.

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@FemaleReproAWG notification

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Re-highlighting this opportunity.

Here is an open, free, asynchronous course to learn AI/ML for space biology. It takes the user from math to models, with quizzes, lectures, and uses Google co-lab notebooks.

Info: Using AI/ML for Space Biology Research - NASA

Canvas registration: تسجيل في NASA TOPS-T ScienceCore AI/ML in Space Biology Training

Anyone finish the course @AIMLawg @ALSDAawg @anuiris @jessicadurbano — and have feedback on it for @james.casaletto ?

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Hi @rtscott2001 , how does one get a free teacher pass?

Dave

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The course is free? Though, I do believe the next step is to do a thing with teachers on how to teach this course

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Yep, the course is clear, friendly, and well-organized. However, I’m not sure if high school students have enough background to understand the fundamentals (programming and biology). I think the math (statistics and calculus) might be sufficient, though.

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Totally agree with Angel about the course.

As regards high school students, I think it depends on the personal background they have. For some of them could be more difficult to understand every section of the course.

Also, I believe that a second part, specifically focused on how to teach the matter, would be great for a lot of teachers/scientific leaders!

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Registered but Canvas didn’t give me access. Shall try again.

Hello! I think this course doesn’t work like the NASA TOPS 101 that grants badges after every module and provides one with an instant certificate. Let me know if you guys are planning to provide certificates.

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I think it could be nice to get badges, or at least one at the end. @james.casaletto what do you think?

Hi @jessicadurbano and @alavia – we agree! We are currently issuing certs manually but are looking into ways to generate them automatically upon completion of the course.

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It seems that they use Badgr, but I’m not sure if there is an additional cost for institutions. If you need it, I can help by programming something at no cost on my server. We could create a simple platform that, based on a CSV exported from Canvas or an API, generates badges for quizzes and certificates upon completion. Additionally, the platform could generate an optional verification link. Alternatively, I can develop something exclusively for you, and even if it’s done manually, it would be considerably faster. We could also provide instructions within the course itself to avoid sending things by email and reduce the chances of being marked as spam.

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Thank you for sharing! The course is pretty clear, and the structure of the notebooks really helped make the concepts easy to follow. I was also wondering if anyone knows if there are similar (preferably free) courses focused on human space physiology? Thank you in advance for any recommendations! :blush:

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