Edsc course

_posts/courses/earth-data-science-corps/01-week-1-intro-to-python/2020-6-29-week-1-intro-to-python.md

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+---
+layout: single
+category: courses
+title: "Earth Data Science Corps - Week One"
+permalink: /courses/earth-data-science-corps/intro-to-python/
+week-landing: 1
+modified: 2020-08-06
+week: 1
+sidebar:
+  nav:
+comments: false
+author_profile: false
+course: "earth-data-science-corps"
+module-type: 'session'
+---
+{% include toc title="This Week" icon="file-text" %}
+
+<div class="notice--info" markdown="1">
+
+## <i class="fa fa-ship" aria-hidden="true"></i> Welcome to Week One!
+
+Welcome to the first week the Earth Data Science Corps! This week you will be introduced to the Python programming language. 
+
+</div>
+
+## <i class="fa fa-pencil"></i> Homework 1: Due Next Week - Thurs, June 11 (9am MT /10am CT)
+
+For this assignment, you will work through self-paced exercises that introduce core concepts in Python programming including:
+* defining variables to store information (data values).
+* creating lists (or collections) of data values.
+* manipulating variables and lists to update and reorganize data.
+
+### Readings
+
+* Read all lessons in:
+    * <a href="{{ site.url }}/courses/intro-to-earth-data-science/python-code-fundamentals/get-started-using-python/">Chapter 10: Get Started with Python Variables and Lists</a> in the Introduction to Earth Data Science online textbook. 
+    * <a href="{{ site.url }}/courses/intro-to-earth-data-science/open-reproducible-science/jupyter-python/">Chapter 3: Jupyter for Python</a> in the Introduction to Earth Data Science online textbook. 
+
+## Assignment and Submission
+
+###  Assignment Part 1
+
+To complete these exercises, we can encourage you to use the Jupyter Hub environment which is accessible via a web browser with an active internet connection. You can then work on setting up your local computer once you have completed the lessons.
+
+To access these exercises on the JupyterHub:
+1. Create a free GitHub account and add your name and GitHub username be granted JupyterHub access.  
+2. Watch the <a href="https://earthlab.earthdatascience.org/t/how-to-log-into-jupyterhub-cloud-computing-environment/51">Intro to JupyterHub video</a> to learn how to login and access the Jupyter Notebooks.  
+    * Notebooks for this assignment (and all future assignments) are accessible in the directory (folder) called course-lessons. 
+    * Additional resources: 
+       * <a href="{{ site.url }}/courses/intro-to-earth-data-science/open-reproducible-science/jupyter-python/">Introduction to Jupyter Notebooks</a> 
+
+
+###  Assignment Part 2
+
+* Post your bio to the <a href="https://earthlab.earthdatascience.org/t/meet-the-earth-data-science-corps-post-your-bio-and-meet-your-peers/20 ">Meet the Earth Data Science Corps</a> topic on Discourse.
+    * After you have posted your bio, respond to three posts by <a href="https://meta.discourse.org/t/what-are-likes/30803">liking the post and replying with a comment</a> (e.g. you share similar project interests or hobbies). 
+* <a href="{{ site.url }}/workshops/setup-earth-analytics-python/">Set-up the Earth Analytics Python environment on your local computer</a> 
+     * Note that you can use JupyterHub (which is already set up with the tools you need) for all of your summer activities (e.g. assignments, project).
+     * However, we encourage you to set up your local environment if you are able (instructions below), as this ensures that you will always have access to these tools!
+
+### How to Submit Your Assignment
+Please post a response to this <a href="https://earthlab.earthdatascience.org/t/about-the-edsc-week-01-category/75">Discourse discussion for Week 1</a>. 
+
+### Optional: If You Want to Set Things Up Locally on your Computer
+Once you have completed these exercises, you have the option to complete the <a href="https://earthlab.earthdatascience.org/t/about-the-edsc-week-01-category/75">Set-up the Earth Analytics Python environment exercise</a> (lessons 1-4) to set up the necessary tools on your local computer (Bash, git, Miniconda with Python).
+
+After you have set-up your local environment, you can access the same Jupyter Notebooks by downloading them to your computer with the following steps:
+
+* Fork and clone the GitHub Repository for the Earth Data Science Corps Summer program to your computer - https://github.com/earthlab/edsc-summer-2020/
+    * Additional Resources:
+        * <a href="{{ site.url }}/courses/intro-to-earth-data-science/open-reproducible-science/bash/">Introduction to Bash in the Terminal</a> 
+        * <a href="{{ site.url }}/courses/intro-to-earth-data-science/open-reproducible-science/bash/">Copy (Fork) and Download (Clone) GitHub Repositories</a>
+* Open a terminal (Git Bash on Windows or Terminal on Mac/Linux):
+    * Change directories to the clone of the GitHub repository using the command *cd earth-analytics/edsc-summer-2020*
+    * Activate the Earth Analytics Python environment using the command *conda activate earth-analytics-python*
+    * Launch Jupyter Notebook using the command *jupyter notebook*
+* Once Jupyter Notebook has launched, you can navigate to the directory (folder) called course-lessons to access the Jupyter Notebooks for this assignment. 
+    * Additional resources: 
+        * <a href="{{ site.url }}/courses/intro-to-earth-data-science/open-reproducible-science/jupyter-python/">Introduction to Jupyter Notebooks</a> 
+
+
+## <i class="fa fa-book"></i> Workshop Agenda
+
+### Welcome to the Earth Data Science Corps
+* **12:30-1:20pm MT / 1:30-2:20pm CT**: Welcome to the NSF Earth Data Science Corps (EDSC)
+    * Intro to Earth Lab Education Team & School PI's
+    * Intro to Slack, useful for group chat
+    * Review <a href="{{ site.url }}/courses/earth-data-science-corps/earth-data-science-corps-syllabus/">syllabus, expectations, and timeline document</a>      
+    * Overview of tools: 
+        * <a href="https://earthlab.earthdatascience.org/">Discourse </a> - useful for posting questions for everyone to see and answer
+        * <a href="{{ site.url }}/courses/intro-to-earth-data-science/open-reproducible-science/jupyter-python/">JupyterHub - cloud computing environment for Python</a> (you can use this for summer activities, in addition to installing the tools on your local computer)
+    * Mentimeter survey
+
+### Breakout Sessions (2 sessions) - Students Only
+* **1:20-1:35pm MT / 2:20-2:35pm CT**: Breakout Groups - Meet Your Peers
+    * Split into Zoom breakout rooms with groups of three
+    * Introduce yourselves (~5 mins for each student): answer the following questions:
+        * Which year are you in your college/university? (e.g. junior)
+        * What is your major? 
+        * What led you to the EDSC program? (e.g. skills you hope to develop)
+        * What kinds of projects are you interested in working on through EDSC? (e.g. water, air quality)
+        * What do you like to do for fun?
+* **1:35-1:50pm MT / 2:30-2:45pm CT**: Breakout Groups - Meet More Peers
+    * Same as above
+
+### Breakout Session (1 session) - Instructors Only 
+* **1:20-1:50pm MT / 2:15-2:45pm CT**: Faculty break-out session led by Nate Q
+    * Challenges and Opportunities for Teaching Data Skills
+
+### Wrap Up
+* **1:50-2pm MT / 2:50-3pm CT**: Reconvene in main Zoom session
+     * Questions
+
+
+

_posts/courses/earth-data-science-corps/02-week-2-data-types/2020-6-29-week-2-python-101-data-101.md

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+---
+layout: single
+category: courses
+title: "Earth Data Science Corps - Week Two"
+permalink: /courses/earth-data-science-corps/intro-to-data-types/
+week-landing: 2
+modified: 2020-08-06
+week: 2
+sidebar:
+  nav:
+comments: false
+author_profile: false
+course: "earth-data-science-corps"
+module-type: 'session'
+---
+{% include toc title="This Week" icon="file-text" %}
+
+<div class="notice--info" markdown="1">
+
+## <i class="fa fa-ship" aria-hidden="true"></i> Welcome to Week 2! 
+
+Welcome to week 2 of the Earth Data Science Corps! This week you will be introduced to different data types that are commonly used in earth data science. 
+
+</div>
+
+## <i class="fa fa-pencil"></i> Homework 2: Due Next Week - Thurs, June 18 (9am MT / 10am CT)
+
+For this assignment, you will:
+* Complete the readings below which review how you can use tabular data in Python to complete scientific analyses with the Pandas package.
+* Complete a data scavenger hunt that will help you find and explore data related to a proposed EDSC summer project.  
+
+### Readings
+
+To begin, read the following chapters in the Online Textbooks - this will prepare you for next week.
+
+* Read all lessons in:
+    * <a href="{{ site.url }}/courses/intro-to-earth-data-science/scientific-data-structures-python/pandas-dataframes/">Introduction to Pandas Dataframes (Tabular Data):</a> Chapter 15 in the Introduction to Earth Data Science online textbook.  
+    * <a href="{{ site.url }}/courses/use-data-open-source-python/use-time-series-data-in-python/date-time-types-in-pandas-python/">Introduction to Time Series with Pandas Dataframes:</a> Chapter 1 in the Intermediate Earth Data Science online textbook. 
+* Watch these videos by Corey Schafer:
+    * <a href="https://www.youtube.com/watch?v=ZyhVh-qRZPA&feature=youtu.be&t=178">Introduction to Pandas </a> (note that video link begins after the installation of Jupyter, which you already have)
+    * <a href="https://www.youtube.com/watch?v=UFuo7EHI8zc">Introduction to Time Series with Pandas </a> (note that video link begins after the installation of Jupyter, which you already have)
+
+If you would like to follow the code in the readings, you can use the JupyterHub environment which is accessible via a web browser with an active internet connection. Recall that you need to use your GitHub account to login.  You can also use your local computer if you have successfully <a href="{{ site.url }}/workshops/setup-earth-analytics-python/">set-up your local computing environment</a>. 
+
+## Assignment and Submission
+### Complete all Four Notebooks In the data-types Directory on the JupyterHub
+To begin the assignment, be sure that you have fully worked through all four jupyter notebooks that are on the JupyterHub. The four notebooks are the ones that you began in the workshop on June 11. The fourth notebook is an activity notebook that will ask you to apply the skills that you have learned so far to complete an activity.
+
+Once you have completed the notebooks complete the two submissions below. Both submissions below will be completed using discourse.
+
+### Assignment Part 1 - Coding Activity
+For this submission, complete notebook 04 -  04-FIXED-data-types-exercise - on the JupyterHub. Then go to the <a href="https://earthlab.earthdatascience.org/t/about-the-edsc-week-02-coding-activity-category/106">Week 2 Python Coding Assignment on Discourse</a>  and follow the instructions which ask you to post your map code and comment on other submissions. 
+
+### Assignment Part 2 - Project Data Exploration
+For this submission you will complete the Project Data Scavenger Hunt posted to the Discourse discussion for Week 2.  You can choose to work in small groups (2-3 students) if you prefer. Once you have completed the activity, please post your findings in the discussion for the <a href="https://earthlab.earthdatascience.org/t/about-the-edsc-week-02-data-scavenger-hunt-category/88">Week 2 Project Data Scavenger Hunt Category on Discourse</a>.
+
+## <i class="fa fa-book"></i> Workshop Agenda
+
+* **9:00-9:15am MT / 10:00-10:15am CT**: Checking in with NSF Earth Data Science Corps (EDSC)
+    * Meet the Earth Data Science Corps team
+    * Review of weekly submission process on Discourse
+
+* **9:15-9:50am MT / 10:15-10:50am CT**: Questions
+    * Check-in about assignments, exercises, access to various resources, etc
+
+* **9:50-10:00am MT / 10:50-11:00am CT**: Break
+
+* **10:00-11:00am MT / 11:00-12:00am CT**: <a href="{{ site.url }}/courses/intro-to-earth-data-science/file-formats/use-text-files/use-tabular-data/">Tabular Data</a>
+    * Work through <a href="{{ site.url }}/courses/intro-to-earth-data-science/file-formats/use-spatial-data/file-formats-exercise/">Jupyter Notebook exercises</a> to learn how tabular data formats are used to store data (e.g. using rows and columns) and explore common tabular data file formats. 
+
+* **11:00-11:10am MT / 12:00-12:10pm CT**: Break
+
+* **11:10am-12:10pm MT / 12:10-1:10pm CT**: <a href="{{ site.url }}/courses/intro-to-earth-data-science/file-formats/use-spatial-data/">Spatial Vector Data</a> 
+    * Work through <a href="{{ site.url }}/courses/intro-to-earth-data-science/file-formats/use-spatial-data/file-formats-exercise/">Jupyter Notebook exercises</a> to learn about spatial vector data types (e.g. points, lines, polygons of geographic locations) and explore common file formats that are used to store spatial vector data. 
+
+* **12:10-12:20pm MT / 1:10-1:20pm CT**: Break
+
+* **12:20-1:00pm MT / 1:20-2:00pm CT**: <a href="{{ site.url }}/courses/intro-to-earth-data-science/file-formats/use-spatial-data/use-raster-data/">Raster Data</a>
+    * Work through <a href="{{ site.url }}/courses/intro-to-earth-data-science/file-formats/use-spatial-data/file-formats-exercise/">Jupyter Notebook exercises</a> to learn about raster data (e.g. elevation, imagery) and explore common raster file formats that are used to store raster data.
+

_posts/courses/earth-data-science-corps/03-week-3-tabular-data/2020-6-29-week-3-tabular-data.md

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+---
+layout: single
+category: courses
+title: "Earth Data Science Corps - Week Three"
+permalink: /courses/earth-data-science-corps/intro-to-tabular-data-python/
+week-landing: 3
+modified: 2020-08-06
+week: 3
+sidebar:
+  nav:
+comments: false
+author_profile: false
+course: "earth-data-science-corps"
+module-type: 'session'
+---
+{% include toc title="This Week" icon="file-text" %}
+
+<div class="notice--info" markdown="1">
+
+## <i class="fa fa-ship" aria-hidden="true"></i> Welcome to Week 3
+
+Welcome to week 3 of the Earth Data Science Corps! This week you will learn to work with tabular data in Python.
+
+</div>
+
+## <i class="fa fa-pencil"></i> Homework 3: Due Next Week - Thurs, June 25 (9am MT / 10am CT)
+
+For this assignment, you will work through self-paced exercises that introduce core concepts in Python programming including:
+* Complete the readings below which review common spatial data types and formats that you can use in Python to complete scientific analyses, including spatial vector data and raster data.
+* Complete Jupyter Notebooks that review the various data types
+
+
+### Readings
+
+* Read all lessons in: 
+    * <a href="{{ site.url }}/courses/use-data-open-source-python/intro-vector-data-python/spatial-data-vector-shapefiles/">Chapter 2: Spatial Data in Python</a> in the Introduction to Earth Data Science online textbook.  
+
+    * <a href="{{ site.url }}/courses/use-data-open-source-python/intro-vector-data-python/vector-data-processing/">Chapter 3: Processing Spatial Vector Data in Python</a> in the Introduction to Earth Data Science online textbook. 
+
+    * <a href="{{ site.url }}/courses/use-data-open-source-python/intro-raster-data-python/fundamentals-raster-data/">Chapter 4: Introduction to Raster Data in Python</a> in the Introduction to Earth Data Science online textbook. 
+
+    * <a href="{{ site.url }}/courses/use-data-open-source-python/intro-raster-data-python/raster-data-processing/">Chapter 5: Processing Raster Data in Python</a> in the Introduction to Earth Data Science online textbook. 
+
+If you would like to follow the code in the readings, you can use the JupyterHub environment which is accessible via a web browser with an active internet connection. Recall that you need to use your GitHub account to login.  You can also use your local computer if you have successfully <a href="{{ site.url }}/workshops/setup-earth-analytics-python/">set-up your local computing environment</a>.
+
+###  Assignment Submission
+
+Please post a response to this <a href="https://earthlab.earthdatascience.org/c/edsc-assignments/edsc-week-03-coding-activity/20">Discourse discussion for week 3</a>.
+
+
+## <i class="fa fa-book"></i> Workshop Agenda
+
+* **9:00-9:30am MT / 10:00-10:30am CT**: Welcome to Workshop 3! (EDSC)
+    * Survey, Questions
+
+* **9:30-10:05am MT / 10:30-11:05am CT**: Intro to <a href="{{ site.url }}/courses/use-data-open-source-python/use-time-series-data-in-python/introduction-to-time-series-in-pandas-python/">time series data in Python</a>
+    * Review and questions
+
+* **10:05-10:15am MT / 11:05-11:15am CT** -- quick break
+
+* **10:15-11:00am MT / 11:15-12:00pm CT**: Break-out Session 1
+    * Work through <a href="{{ site.url }}/courses/intro-to-earth-data-science/file-formats/use-spatial-data/file-formats-exercise/">Jupyter Notebook exercises</a> to review how tabular data formats are used to store scientific data (e.g. using rows and columns). 
+
+* **11:00-11:40am MT / 12:00-12:40pm CT**: Lunch Break
+
+* **11:40am-12:00pm MT / 12:40-1:00pm CT**: Question / Answer Session
+
+* **12:00-12:50pm MT / 1:00-1:50pm CT**: Break-out Session 2
+    * Work on challenges
+
+* **12:50-1:00pm MT / 1:50-2:00pm CT**: 
+    * Wrap up / Feedback / Next Steps
+
+