This material is based upon work supported by the National Science Foundation under NSF EHR DRL. 1839656/PI Lauren Birney. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
- Staff & Speakers directory
- Dr. Parisi, Dr. Scharff, Prof. Kaleema Lnu, Prof. Krishna Bathula
- Thanks to our wonderful mentors: Sunanda Singareddy, Yadhavi Rao, Yashraj Bhandare, Shubbham Trivedi
- Be more knowledgeable about the Billion Oyster Project
- Be more knowledgeale about maritime science
- Be more knowledgeable about what Data Science is
- Be introduced to data science algorithms
- Be introduced to basic statistics
- Be familiar with the Python language fundamentals
- Be familiar with the most common Python data structures and libraries for Data Science
- Be able to create visualizations with Python
- Be able to use Python to carry out basic statistical modeling and analysis
- Be familiar with Design Thinking
- Have developed teamwork and communication skills
- Have applied knowledge on a project based on real data
- Discover studies and careers in tech
- Instruction - Zoom
- Communication - Slack
- Documentation - GitHub
- Exploration of the data - Excel, Python
- Code - Python, Google Colab, GitHub
- Design thinking - Miro
- Presentations - Google Docs
Please note that the slides are in a Google Colab notebook.
- Slides
- Linear regression
- Practicing Python
- Ice breaker
- Data Visualization
- Design Thinking
- Storytelling
- Agata Poniatowski, Education Outreach Coordinator at the Billion Oyster Project.
- Dr. Stephen Gosnell, Assistant Professor, Department of Natural Sciences, Baruch College & Graduate Center, CUNY. Slides
- Panel with AppFigures - Ariel Michaeli, Co-Founder, Oz Michaeli, Co-Founder & Head of Product, Alex Quick, Head of Engineering, Joshua Vernazza, Head of Data Science
- Google - Josh Gordon, Developer Advocate, will show fun examples of deep learning applications
- Seidenberg students' panel - Angela Bonsol (2021), Vivian Ng (2020), Vicente Gomez (2021)
- Keynotes - James McCabe, Google Customer Success Manager and Keithe Bennet, Google Technical Operations Manager
- The data that will be used are: bop_data.csv and bop_date2.csv.
- A description of the data is in the data dictionary.
- What is BOP?
- Learning resources
- Oyster Ecology
- Data
- Field Science Manual: Oyster Restoration Station (how data are collected)
- Access the data. BOP Platform (not currrently possible)
- Data How-to Guide
- Digital Platform User Guide Table of Contents
- BOP ORS, BOP Oyster Reefs, BOP Oyster Nurseries - all oyster data (heights, live/dead in some cases)
- Billion Oyster Project’s Water Quality Data
- Dissolved Oxygen 2017-2018
- Salinity 2017-2019
- Temperature 2017-2019
- Sample research questions
- Quiz
Presentations, code, murals etc.
Please note that some of the links require access.
- Team 1
- Team 2
- Team 3
- Team 4
- Team 5
- Team 6
- Team 7
- Team 8