Assignments:

Assignments will be posted here usually by Saturday afternoon. They will be due (via upload) the following Thursday by 8 pm. The first portion of each friday class is devoted to discussing the various approaches to the assigned problem.

Structure of the Assignments:

• Most all will deal with real data, in some cases dirty data.
• All assignments will have multiple parts to allow you practice in data organization, management, manipulation, processing, analysis, and representation.
• All assignments can be done collaboratively with group size maximum = 3.
• All assignments have built-in failure modes and obstacles to overcome because this is the best way to learn this stuff. Our expectation is that all groups will encounter failure modes.
• There is never any one right way to do the assignment; multiple approaches using multiple tools is what the assignments are designed to encourage.
• For the first few assignments you can use any tools/programming that you like (you will find that many approaches won't work) but eventually we want to migrate you to using python or fortran (gfort) on ACISS as the principal way to perform data analysis on large data sets.
  
  First Exercise::
  
  Array Based Image Operations Due by 8pm Thursday Apr 9
  
  Second Exercise::
  
  Even More Array Based Image Operations Due by 8pm Thursday Apr 16
  
  Third Exercise::
  
  Extracting correlations and data inferences from multiple parameters Due by 8pm Thursday Apr 23
  
  Fourth Exercise::
  
  Custom queries and reporting of a multi-parameter data base. Due by 10pm Thursday May 7
  
  Fifth Exercise::
  
  Formatted Read and Write Operations Due by 10pm Thursday May 14
  
  Sixth Exercise::
  
  Noisy Data: The Central England Temperature Record Due by 10pm Thursday May 21
  
  Seventh Exercise::
  
  Finding the Global Minimum solution Due by 10pm Thursday May 28
  
  Eighth Exercise::
  
  Gaining experience with netCDF Due by 8pm Friday June 12