+
+### Step Three: Post on Discourse
+
+You will work together in your group to complete this assignment.
+* As a group, submit your workflow diagram to the 
+
+2. **OPTION 2**: Alternatively - you can submit your blog post as a Word Document. This format will be less reproducible but will get the job done! Please do not hesitate to use this option.
+ * **The image below shows you how to export a Google Document as a Word Document. You can use file → Download → Microsoft Word**
+
+
+**IMPORTANT:**
+ * **You will only submit one of the two formats listed above. You can decide as a group which format you wish to use for your final blog post.**
+ * **Please be sure to include the names of ALL members of your group in your blog post as authors.**
+ * **Each group will only submit 1 blog post in either a Jupyter Notebook or Word Document format. You do not need to submit anything individually.**
+
+## About Your Blog Post’s Structure
+
+Your project blog post will be posted on our edsc page on the Earth Lab website. It should be structured as an informative online write up that describes:
+
+1. Why your topic is important and why someone should care about it.
+2. What other work has been done in this area.
+3. What your methods are. Note that your code should be expressive to provide a good overview of your workflow so you do not need to get into the nitty gritty details of the Python steps that you applied.
+4. Summary / Conclusions: What you discovered about your topic or research question.
+
+Your blog should also:
+
+1. Reference other efforts on this topic area (this could be presented as links given that it is a blog).
+2. Be at least 2-3 pages of text in length (~700 words). We won't be counting words; we simply want you to create a robust blog post that describes what you did and what you found.
+3. Highlight your study area using a map.
+ * OPTIONAL: Contextily could be used to create a nice basemap! You could also create a nice interactive map using Leaflet.
+4. Provide a descriptive overview of the data used with sources referenced. Note that the data sources should be described in your text. If it does not fit into your blog post you can cite the data in a short references section at the end of your blog post.
+5. Provide a high level overview of the methods used to process the data. Because this is a blog post, your overview should not be technical.
+6. Present results including at least 2 data plots (graphics created using data) that answer the question that you decided to address or the phenomenon that you decided to explore using data.
+
+IMPORTANT: Be sure to cite the data that you used in your project using the organizations preferred citation style. This citation could happen at the bottom of your post or in a figure caption!
+
+Examples of good blog posts written by previous interns:
+
+* Machine Learning and Underwater Biomass Characterization
+* Calibrating Low-Cost Air Pollution Sensors Using Machine Learning
+* July 8, 2016 - The Day Hayden Pass Burned
+
+
+## Code Submission Requirements
+
+**Before you submit your code, please be sure that it meets the requirements below:**
+
+* Include the code that you used to create maps and process any data used. Be sure to use expressive, efficient, modular coding. Please document your code as we have been discussing in class all summer!
+* Be sure all plots / maps have clearly labeled x and y axes (as appropriate) and legends.
+* All plots / maps should also include a caption that describes what the data show. You can add the caption in whatever way you'd like to (e.g. plot caption or in the Markdown).
+* All code should be formatted following pep8 guidelines.
+* Spell check / grammar check your blog post BEFORE YOU SUBMIT.
+* Where you can, write clean, efficient expressive code. Following what we've been discussing all semester, you will be graded on the quality of your code.
+* Your notebook should run from beginning to end. Be sure to run it in its entirety before submitting and that the first cell begins at [1].
+
+## How to Submit Your Work
+
+To submit your final project, upload the following to Google Drive:
+
+1. Your final presentation to this final-presentation folder on Google Drive as a PowerPoint, Google Slides, PDF, or any other presentation format.
+2. Your final project blog to this final-blog folder on Google Drive as a Word Document or JupyterNotebook/HTML file.
+3. The code that you used to develop your workflow to this final-code folder on Google Drive as a Jupyter Notebook.
+
+Please be sure to include the title of your project in each file name. **This assignment is due on Friday August 14th at 10pm.**
+
+
diff --git a/_posts/courses/earth-data-science-corps/course-overview/2020-6-29-edsc-course-home.md b/_posts/courses/earth-data-science-corps/course-overview/2020-6-29-edsc-course-home.md
new file mode 100644
index 000000000..d7375c562
--- /dev/null
+++ b/_posts/courses/earth-data-science-corps/course-overview/2020-6-29-edsc-course-home.md
@@ -0,0 +1,52 @@
+---
+layout: single
+category: courses
+title: "Earth Data Science Corps | Earth Lab CU Boulder"
+authors: ['Leah Wasser', 'Nathan Korinek','Jenny Palomino', 'Lauren Herwehe', 'Nate Quarderer', 'Elsa Culler']
+nav-title: "Earth Data Science Corps Home"
+permalink: /courses/earth-data-science-corps/
+course: "earth-data-science-corps"
+modified: 2022-06-16
+module-type: 'overview'
+module-title: "Earth Data Science Corps"
+week-landing: 0
+week: 0
+estimated-time: "11 weeks"
+difficulty: "beginner"
+sidebar:
+ nav:
+comments: false
+author_profile: false
+overview-order: 1
+---
+
+{% include toc title="This course" icon="file-text" %}
+
+{% assign course_posts = site.posts | course: page.course %}
+{% assign sorted_posts = course_posts | sort:'overview-order' %}
+
+{% assign modules = sorted_posts | where:"module-type", 'overview' %}
+{% assign modules_course = modules | where:"course", page.course %}
+
+
+
+## Welcome to the Earth Data Science Corps!
+
+## Key course materials
+
+{% for post in modules_course %}
+ * {{ post.title }}
+{% endfor %}
+
+
+
+
+
+## About This Textbook
+This is a collection of readings with interactive exercise for participants in the Earth Data Science Corps program. You will learn how to write scientific Python workflows and work with common Earth Science data types like spatial and time-series data.
+
+For the best results, you should try out the code as you are learning! You can run the code on Google Collaboratory (Colab) or install the Earth Analytics Python environment on your computer.
+
+## About the Earth Data Science Corps
+The NSF-funded Earth Data Science Corps program is aimed at undergraduate students who are new to data science and interested in applying it to earth and environmental science. Participants are trained through workshops, the Earth Analytics Bootcamp (GEOG 4463/5463) course materials, and a faculty mentor from their institution.
+
diff --git a/_posts/courses/earth-data-science-corps/course-overview/2020-6-29-edsc-syllabus.md b/_posts/courses/earth-data-science-corps/course-overview/2020-6-29-edsc-syllabus.md
new file mode 100644
index 000000000..5a9ef963d
--- /dev/null
+++ b/_posts/courses/earth-data-science-corps/course-overview/2020-6-29-edsc-syllabus.md
@@ -0,0 +1,108 @@
+---
+layout: single
+title: 'Earth Data Science Corps: Summer 2020 Syllabus'
+authors: ['Leah Wasser', 'Nathan Korinek','Jenny Palomino', 'Lauren Herwehe', 'Nate Quarderer']
+category: courses
+excerpt:
+nav-title: Course Syllabus
+modified: 2020-08-06
+comments: no
+permalink: /courses/earth-data-science-corps/earth-data-science-corps-syllabus/
+author_profile: no
+overview-order: 2
+module-type: 'overview'
+course: "earth-data-science-corps"
+sidebar:
+ nav:
+---
+{% include toc title="In This Lesson" icon="file-text" %}
+
+
+
+
+## Getting Help
+
+There are several ways that you can get help when you get stuck in this program:
+
+1. Attend office hours (see schedule below).
+2. Post your question on the Discourse Forum: https://earthlab.earthdatascience.org/
+3. Post your question on the EDSC Slack Channel
+
+## Course Requirements
+
+All students will need a working laptop with internet to complete this program.
+
+## Program Components
+
+### Workshops, Webinars, & Office Hours
+
+All program activities will occur via Zoom on the schedule outlined in the calendar below. You will receive Zoom links for events through email and calendar invites.
+
+### Homework Assignments
+
+Each week there will be a homework assignment. Use the materials on the website including readings, tutorials and links to other resources in addition to skills and concepts that you learn in workshops to complete the assignment.
+
+You can use JupyterHub (which is already set up with the tools you need) for all of your summer activities (e.g. assignments, project).
+
+### Weekly Readings
+
+Readings are posted every week along with the homework assignment for that week.
+
+### Final Internship Project
+
+EDSC assignments will provide you with the skills and resources needed to complete a final project. This project will teach you how to tackle a real-world data problem and, in the process, gain applied skills that will make you marketable on the job market. For this project, you will work in small groups under the guidance of a mentor at your home institution, Earth Lab, or a public or private industry partner. In some cases, you may also choose to define your own project. The final submission will consist of a group presentation and report that you submit in `Jupyter Notebook` and `.html` or `.pdf` format.
+
+**Important:** Please note that the course schedule and content as discussed above
+is subject to change. This course content schedule is not designed as a
+contract. Rather, it is
+an overview guide to the materials that you will review during the semester.
+{: .notice--success}
+
+## Weekly Schedule
+
+| Week | Event | Date & Time |
+|---|:---|---|
+| 1 | Earth Data Science Corps Kickoff Meeting | Fri, June 5th, 12:30-2pm MT |
+| 2 | Workshop: Python 101 and Data Formats 101 | Thurs, June 11th, 9am-1pm MT |
+| 2 | Office Hours | Fri, June 12th, 10-11:30am MT |
+| 3 | Workshop: Introduction to Tabular Data in Python | Thurs, June 18th, 9am-1pm MT |
+| 3 | Office Hours | Fri, June 19th, 10-11:30am MT |
+| 3 | Webinar: Careers in Earth Data Science | Fri, June 19th 12-1pm MT |
+| 4 | Workshop: Introduction to Vector Spatial Data in Python | Thurs, June 25th, 9am-1pm MT |
+| 4 | Workshop: Introduction to Raster Spatial Data in Python | Thurs, June 26th, 9am-1pm MT |
+| 5 | July 4th Holiday | |
+| 6 | Workshop: Science Communication | Fri, July 10th, 10am-12pm MT |
+| 10 | Practice Project Presentations and Peer Feedback | Fri, August 7th, 10-11:30am MT |
+| 11 | Final Project Presentations| Thurs, August 13th, 12-1:30pm MT |
+
+
+## Student Expectations
+### Hours & Payment
+At the beginning of the program, the student and the supervisor will discuss working hours. At a minimum:
+* We require that each intern logs a total of 200 working hours over the course of the internship. Ideally this will be 20 hours per week for the 10 week duration of the internship, Friday 6/5/20 through Friday 8/14/20. However, each individual partner institution can make their own rules about how they want to distribute intern hours throughout the program, for example, if they would like to allow students to work for additional hours certain weeks to make up for a week of vacation.
+* Interns must submit a tentative weekly work schedule to their mentor. This will be used to ensure that students meet the minimum working hours requirement.
+* You will be paid a stipend for your participation in this program.
+
+### Events & Assignments
+Throughout the internship period, interns will be required to submit assignments and there will be mandatory workshops, webinars, and events. These assignments and events will focus on building core skills that will be useful in the job market. Interns are required to:
+* Give a practice presentation and final presentation on your research in August.
+* Submit all technical workshop assignments on time and a blog post at the end of the semester. The blog post will follow guidelines outlined in this document.
+* Attend all internship events. If a student cannot attend an event, or will be late to an event they must notify their supervisor and the HDR program manager. Event attendance is tracked in this spreadsheet.
+
+## Supervisor Expectations
+With the program timeline, prior to the internship start date, students will have limited technical experience. The internship is where much of their learning will occur, so it is important that the project be data-intensive and that supervisors have time to spend mentoring students. Supervisors must:
+* Provide projects that are data-intensive.
+* Have an understanding that they will be responsible for helping students learn and time in July and August to mentor their students.
+* Attend all technical workshops and webinars, as possible.
+* Support the students in getting help. Mentors are also learning many of these skills so may not be able to answer every question and that is totally ok. Mentors may encourage students to ask questions on Discourse or reach out to another EDSC mentor or peer when they run into issues.
+* Meet with interns at least once a week to provide guidance.
+* Discuss working hours with their students on the outset of the program. While the stipend payments will be distributed by CU Boulder, each school will be responsible for ensuring that students are working 20 hours per week for the duration of the summer.
+* Ask the internship HDR program manager before giving interns any exceptions to general internship rules (e.g. extended time off, flexibility in 20 hour/week rule).
+* Ensure that their students are attending all events, tracked in this spreadsheet.
+
+## Program Evaluation and Research Study
+We will be conducting surveys and interviews during the program as part of a research study to gather feedback on how the program is going, how it can be improved in future years and learn about best practices in teaching Earth Data Science in different formats to different groups of participants. Your participation in the study will be voluntary, all data will be de-identified by the research team (not part of the program staff), kept confidential, and only reported in aggregated form. Your responses won’t impact your performance in the program in any way.
+
+However, as part of the program, all Earth Data Science Corps participants will be asked to complete all surveys whether or not they consent to having their data be included in the study. Your stipend covers participation and no additional financial incentives will be provided.
+
+
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