Merge branch 'master' into dev

Author: Leah Wasser

_events/course-materials/2017-01-17-earth-analytics-course.md

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+---
+layout: single
+title: Earth Systems Analytics Course - Register Now!
+text: 'To be held Spring 2017 - register now!'
+location: SEEC S125
+permalink: /course-materials/earth-analytics/
+date: 2017-01-17
+startTime: '3:00'
+endTime: '17:50'
+---
+
+## About
+
+This advanced, multidisciplinary course will address major
+questions in Earth science and teach students to use the
+analytical tools necessary to undertake exploration of ‘big
+scientific data’. If you are a graduate and undergraduate (junior/
+senior) student in the natural/social science disciplines with an
+interest in learning about computationally intensive science, this
+course is for you.
+
+### Example Course Science Topics (Topics subject to change):
+
+* **Climate & Disturbance (Fire / Drought / Permafrost):** How
+changing climate impacts natural disturbance systems.
+* **Land Processes (Erosion):** Identify how rapid and slow
+landscape evolution impacts our lives;
+* **Vegetation:** Determine what is driving Colorado forest
+dieback;
+* **Climate & Society:** Social media and web as a powerful
+means to understand climate impacts.
+* **Data Integration:** understand issues associated with
+integration data from various sources (scale, resolution, format)
+
+
+Throughout the semester, we will work together to build the
+following skills:
+
+* **Scientific programming:** Use the R / R-studio environment to
+access, process & visualize scientific data.
+* **Find / access scientific data:** Programmatic (API) access of
+data (NASA, USGS, etc.) via API’s.
+* **Communication/Collaboration:** refine cross- discipline
+collaborative writing and project development skills.
+* **High Performance Computing (HPC):** implement large scale
+data processing tasks on powerful remote servers.
+* **Efficient data approaches:** process data more quickly via
+using multiple “cores”.
+
+### Semester Project
+
+End of the semester Course Project: Students will choose a
+science question of interest to explore throughout the semester.
+They will apply skills learned in the course, to produce and
+present a final project.

_pages/learn.md

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 ## Data Intensive Courses
 A newly designed
-[Earth Systems Analytics course - GEOG 4100 / 5100]({{ site.url }}/course-materials/earth-analytics/)
+
+[Earth Systems Analytics course - GEOG 4463 / 5463]({{ site.url }}/course-materials/earth-analytics/)
 will be taught January 2017. This course fuses key topics related to the grand
 challenges in science, remote sensing and computationally intensive approaches.
 The course will be held in Spring 2017 at the CU Boulder campus. Stay tuned for