IS&T Research Computing Boot Camp - Python Language Track

Wednesday, January 6, 1 pm - 3 pmFriday, January 8, 1 pm - 3 pmMonday, January 11, 1 pm - 3 pmWednesday, January 13, 1 pm - 3 pmPython is a free and open-source programming language with a focus on ease-of-use and readability. Python has a comprehensive standard library, further expanded by a huge collection of third-party packages that can be easily used via package repositories such as PyPI. These packages add a wealth of functionality including notable packages for handling numerical and scientific tasks, statistics, data science, etc.This track is composed of four parts and you register for all four of them as a unit. The four parts take place on January 6, 8, 11, and 13, all from 1 pm to 3 pm. We also strongly encourage you to register for the two part ArcGIS Online sequence that continues using the same dataset you worked with here. The item to register for that is scheduled on Tuesday, January 19 from 10 am to 12pm and also registers you for the second part on Thursday, January 21 at the same time.Part One - Programming and Data: Language Basics and Example DatasetAnalyzing a large or complex set of data requires computational techniques implemented in a programming language. Part One introduces programming language basics and useful features. Concepts like data types and structures, syntax, loops, and control flow are introduced. How to use the Integrated Development Environment (IDE) is also demonstrated. An example dataset is introduced that will be used throughout all parts.Part Two - Data Processing and HandlingTo work with a dataset various operations are needed to bring it to a usable state within a program. Part Two walks through this process, covering reading in data from files; cleaning the data; formatting the data; and manipulating the data in memory. Various data structures will be discussed alongside their trade-offs.Part Three - Data Visualization: Plotting and GraphicsExamining complex patterns and correlations in data requires visualization to present the results in a digestible form. Part Three presents various ways to plot and visualize data. Different plotting techniques and formats are presented, along with various ways to format and configure their display and appearance.Part Four - Using Statistical Tools for Analyzing DataDiscovering and verifying meaningful patterns and correlations in data requires quantitative techniques that can analyze the data in a rigorous mathematical or algorithmic way. Part Four presents how to use various basic statistical tools to analyze the example dataset. The use of these tools is demonstrated and various example diagnostics, patterns, and correlations are examined in the example dataset.

When 1:00 pm to 3:00 pm on Wednesday, January 6, 2021
Location Zoom - Registered attendees will be emailed the Zoom link approximately two days before the tutorial