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If you have concerns about the course, please email to me or open the github issue. I value all suggestions.
- Email: [email protected].
This course is intended to train students majored in thermal energy engineering in good software skills for producing code.
We will cover:
- writing clean, testable, high quality code in Python
- interactive analysis and literate programming with the IPython Notebook
- a useful set of algorithmic and apply abstraction and decomposition to solve the complex problems
- computational tools to model and understand data(numpy, matplotlib, scipy)
- debug programs using a standardized approach
- write unit tests and evaluate software quality
- use version control
- C/C++ programming with GCC(basic data structure and algorithm)
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A laptop computer will be needed in the classroom.
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John V. Guttag. Introduction to Computation and Programming Using Python. Revised and expanded edition. MIT Press. 2013.08.
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梁杰译. 编程导论. 人民邮电出版社(第1版) . 2015.03
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Guttag, John. Introduction to Computation and Programming Using Python: With Application to Understanding Data. MIT Press, 2016. ISBN: 9780262529624.
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https://mitpress.mit.edu/index.php?q=books/introduction-computation-and-programming-using-python-0
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Accompanying Python3 Code:https://mitpress.mit.edu/sites/all/modules/patched/pubdlcnt/pubdlcnt.php?file=/sites/default/files/code-978-0-262-52962-4_0.zip&nid=321887
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Python 3 documentation. https://docs.python.org/3/
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Michael J . Mora. Fundamentals of Engineering Thermodynamics(7th Edition). John Wiley & Sons, Inc. 2011
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An Introduction to GCC http://www.network-theory.co.uk/docs/gccintro/index.html.
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Scott Chacon,Ben Straub. Pro Git. https://git-scm.com/book/en/v2/Getting-Started-About-Version-Control
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Please install Jupyter to read and interactive with the notebook.
Online read-only versions:
http://nbviewer.ipython.org/github/PySEE/home/tree/S2018/notebook/
The Course graded on an 100 point scale and then weighted according to the following distribution:
- In-class Exercises: 20%
- Practices(5):60%, Bonus Points: +5
- Final Exam: 20%
Please Visit Practices for details: https://github.com/PySEE/Practices/
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Github(5):Github、Git
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Python and Interactive Computing(15):The Simple Simulator of Rankine cycle
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The Object-oriented Programming(20): The General Simulator of Rankine cycle
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Data Analysis(15):Statistics, regression and visualization
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Unit Test(5):IAPWS-IF97 physical properties calculation and unit test
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Bonus Points(+5): C/C++ Programming with GCC, Ubuntu
This repository contain all files of the course. You can manually download these files,
We recommend that you use git to clone and update this repository.
After you have installed git, You may use the following commands:
- shallowly cloning the branch of repository for saving bandwidth
>git clone --depth 1 -b S2018 https://github.com/PySEE/home.git
This will create a folder home on your computer with the files in subdirectories.
As we release new files, or if we update an already released files, you'll have to update your repository.
You can do this by changing into the home directory and executing:
>git pull
That's it - you'll have the latest version of the repository.
you may also use any GUI git client to clone and update this repository, for example: Visual Studio Code ,or GitHub Desktop
We highly recommend you practice coding whenever you have a few minutes.
You NEED to get your hands dirty and practice