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Lecture 1 Introduction

Presentation slides are posted on Canvas

Key Points

  1. What is computational research?
  2. Data analysis pipeline for computational research.
  3. Challenges in research computing: Complexity, Reproducibility, Data Size.
  4. Topics we will cover in class.
  5. Class logistics.

Topics we will cover in class

  1. Python Programming
  2. Open-source Computing
  3. Big Data

Learning Goals

  1. Be able to construct complete, well-structured programs in Python.
  2. Read and write most common atmospheric and environmental sciences data formats.
  3. Perform basic exploratory data analysis.
  4. Use visualization to enhance interpretation of environmental science data, including making maps and interactive visualizations.
  5. Practice open-source research through version control, packaging etc.
  6. Practice big-data analysis with parallel computing.
  7. Understand the concepts of cloud computing.