Considering the fact that 1997, Program Carpentry has taught scientists and engineers the ideas, expertise, and equipment they have to use and produce software system extra productively. All the articles is freely attainable beneath a Creative Commons license, and we're frequently incorporating and updating lectures, videos, and workout routines.
Can Program Carpentry allow you to? These comments from previous pupils and our three-minute pitch,
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Is it possible to guide Software Carpentry? We're an open source/open license challenge, and there are several strategies in which volunteers can contribute. We also have a number of funding versions, so if you ever would love to assist folks throughout the globe solve the conditions they deal with presently, and put together them to tackle the larger difficulties of parallelism,
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Edition four
We are currently updating the subject matter and format to ensure that pupils can give good results because of the substance they desire, whenever they require it. The lectures we have now completed to date cover: Version Command – Learn how to collaborate with other individuals and automatically create a record of previous perform using a edition command system.
The Shell – Much of scientific computing involves the Unix operating system. Effectively using the shell is one on the first steps to efficient Unix programming.
Python – A versatile open supply language that is increasingly popular among scientific programmers.
Testing – The basics of software package testing, including exception handling and unit testing.
Sets and Dictionaries – Using associative data structures to better represent data that isn’t a list or vector.
Regular Expressions – Manipulate text quickly with this powerful set of pattern matching resources.
Databases – An introduction to SQL,
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Classes and Objects – The basics of object-oriented programming.
Program Design – An example driven introduction to effective program design.
Make – This tool will assist automate everything from large software programs builds to batch processes.
Matrix Programming – Use array libraries to make numerical programs smaller and faster.
MATLAB – The world’s most popular numerical programming language.
Multimedia Programming – Do the job with images, sound, and other media.
Spreadsheets – Learn to make use of spreadsheets for data organization, analysis,
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Essays – Longer (non-video) discussion of some important ideas in scientific programming.
Recommended Reading – An annotated bibliography.
Glossary – Key terms. Edition 3
The lecture notes from Edition 3 of this course (2004-2009) are to choose from at
Further Reading How Do Researchers Really Use Computers?
How Do Experts Develop and Use Scientific Software system?
Those Who Will Not Learn From History…
Software package Carpentry: Getting Researchers to Write Better Code by Making Them Even more Productive
Where’s the Real Bottleneck in Scientific Computing?
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