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"Python (Computer program language) Study and teaching."
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Computational tools for engineers course overview
Welcome to ChE263 which teaches computer skills useful to engineers and scientists. It covers MATLAB, Python, Mathcad, computer programs for doing all types of math, both numerically and symbolically; Excel, a spreadsheet program; and Visual Basic Application, a programming language to automate Microsoft Office applications.
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Debugging Python with ipdb and Sypder
A powerful debugging tool for Python is the pdb (or ipdb) tool that is part of the Integrate Development Environment of Spyder (available from the Anaconda download). This exercise shows how to debug code to fix syntax and logical programming errors.
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Chemical reaction differential equations in Python
Concentrations on chemical species from mole balances are solved for 1, 2, and 4 species in Python with the Scipy.Integrate package ODEINT.
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Curve fit with Excel and Python
Nonlinear regression with heart rate data is shown in both Microsoft Excel and Python. GEKKO and SciPy curve_fit are used as two alternatives in Python.
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Data analysis with Python for Excel users
A common task for scientists and engineers is to analyze data from an external source. By importing the data into Python, data analysis such as statistics, trending, or calculations can be made to synthesize the information into relevant and actionable information.
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Arduino TCLab for engineering education
The Temperature Control Lab is a plug-and-play Arduino device to teach programming, heat transfer, machine learning, data science, process dynamics, and control with real data. Two heaters and an LED are adjusted with MATLAB or Python. Two temperature sensors show how much heat is transferred or lost. Thermochromic pigment turns pink when hot and black when it cools off. The take-home lab gives real data so that theory and methods come alive with concrete and tangible examples.
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Python data science essentials
Become an efficient data science practitioner by understanding Python's key concepts. About This Video: Quickly get familiar with data science using Python 3.6. Save time (and effort) with all the essential tools explained. Create effective data science projects and avoid common pitfalls with the help of examples and hints dictated by experience. In Detail. The Python Data Science Essentials video series takes you through all you need to know to succeed in data science using Python. Get insights into the core of Python data, including the latest versions of Jupyter Notebook, NumPy, Pandas and scikit-learn. In this course, you will delve into building your essential Python 3.6 data science toolbox, using a single-source approach that will allow to work with Python 2.7 as well. Get to grips fast with data munging and preprocessing, and prepare for machine learning and visualization techniques.
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Improving Engagement in Program Construction Examples for Learning Python Programming
This research is focused on how to support students’ acquisition of program construction skills through worked examples. Although examples have been consistently proven to be valuable for student’s learning, the learning technology for computer science education lacks program construction examples with interactive elements that could engage students. The goal of this work is to investigate the value of the “engaging” features in programming examples. We introduce PCEX, an online tool developed to present program construction examples in an engaging fashion. We also present the results of a controlled study with a between-subject design that was conducted in a large introductory Python programming class to compare PCEX with non-interactive worked examples focused on program construction. The results of our study show the positive impact of interactive program construction examples on student’s engagement, problem-solving performance, and learning.
Journal Article