Earth System Data Science in the Cloud

Session Overview

  • Welcome & Thank You!
  • Introductions
  • Data Driven Science
  • What is Data Science?
  • What is Earth System Data Science in the Cloud?
  • Course Goals and Objectives
  • Module Goals and Objectives
  • Course Logistics

Welcome!

Thank you!

Lot’s of people made this possible:

  • Dr. Otis Brown

IT:

  • Scott Wilkins
  • Jonathan Brannock
  • Steven Marcus

AWS:

  • Chris Stoner

NOAA!

Introductions

dwillett@cicsnc.org

ggraham@cicsnc.org

Session Overview

  • Welcome & Thank You!
  • Introductions
  • Data Driven Science
  • What is Data Science?
  • What is Earth System Data Science in the Cloud?
  • Course Goals and Objectives
  • Module Goals and Objectives
  • Course Logistics

Data Driven Science

Schleder et al. 2019 DOI: 10.1088/2515-7639/ab084b

Data Science

Earth System Data Science in the Cloud

  • Scale
  • Speed
  • Reactive and Real Time
  • Efficient (Cost and Computation)

Earth System Data Science in the Cloud

  • Give you the tools to scale your analysis on the cloud.
  • Enable you to work effectively in interdisciplinary data-driven teams
  • Understand and leverage Artificial Intelligence for research
  • Rapidly learn and adopt new technologies and paradigms

Course Goals & Objectives

  1. Make the Impossible Possible
  2. 10x Performance


Principles & Practices

Module Goals & Objectives

Module Goals & Objectives

By the end of this module, you should:

  • Be able to hit the ground running with Python in the next modules of the course.
  • Have a core grasp of scientific programming fundamentals to incorporate into your work in and outside this course.
  • Understand how to leverage AI programming assistants for rapid prototyping.
  • Be familiar with version control strategies
  • Understand how APIs can be used to share information.

Specifically, by the end of this module, you will have accomplished the following:

  • Used the command line to navigate your environment and launch scripts.
  • Written programming scripts to ingest and parse data.
  • Leveraged packages and libraries to perform programming tasks.
  • Built functions to repeat common tasks.
  • Used programming AI assistants.
  • Documented your code.
  • Created basic plots using programming languages.

Module Outline

Days:

  1. Introduction & Core Programming Skills
  2. Version Control, LLMs, and Computing
  3. More Advanced Programming
  4. Production ML & Data Viz
  5. Parallel Computing & Exercise

Session Overview

  • Welcome & Thank You!
  • Data Driven Science
  • What is Data Science?
  • What is Earth System Data Science in the Cloud?
  • Course Goals and Objectives
  • Module Goals and Objectives
  • Course Logistics

Course Logistics

Zulip

DOs

  • Use Channels
    • (Specifically our Channel)
    • Posts are threads/specific topics
  • REPLY IN THREAD
  • Actually write (and think about it)

DON’Ts

  • Spam channel
  • Reply to all outside of threads
  • Hit enter (send message) after every word

Strategies for Success

This is a lot of information.

  • You would not be here if you could not handle it.
  • Be present.
  • You will not understand everything the first time. That is OK!
  • Keep a Journal of topics to return to and explore more
  • You will see each topic/idea at least 3 times on separate days
  • Ask questions
  • Invest the time now…

Final Note

We made this course for you! We want your feedback!

Please reach out anytime on Zulip or at dwillett@cicsnc.org & ggraham@cicsnc.org.

Pre-course Assessment


Pre-Course Assessment

Earth System Data Science in the Cloud