Python is a high-level and general-purpose programming language with data science and machine learning packages. Use the instructions to install Python for Windows, MacOS, or Linux as a first step. If there are multiple Python versions, find the correct location…

Welcome to Python for Data-Driven Engineering. This introductory lesson covers variable types such as boolean, integer, float, and string. It introduces operators, conditional statements, for loops, while loops, print statements, conversion between types…

A tuple is a data structure in Python that is similar to a list, but it is immutable, meaning that it cannot be changed once created. This makes tuples more efficient and less prone to errors, because they cannot be modified by mistake. A tuple is one of…

A Python list is an ordered collection of objects that can be of different types, including other lists. Lists are created using square brackets and can be modified, searched, and iterated over. They are an essential part of the Python language and are used…

A Python set is an unordered collection of unique elements. It is useful because it can perform mathematical set operations such as union, intersection, and difference. Additionally, sets are faster to search than lists or dictionaries because they are implemented…

A dictionary is a set with 🔐 key:value pairs. It is designed to lookup values based on the 🔑 key to return a 🔒 value. An example is a dictionary of words (key) with a definition for each word (value).

Data-Driven Engineering: https://apmonitor.com/dde
DDE…

Data-driven engineering relies on information, often stored in the form of collections of numbers as matrices and arrays. NumPy (Numerical Python extensions) is a library for data processing with multi-dimensional arrays and mathematical functions to operate…

Data-driven engineering is the process of reading, cleansing, calculating, rearranging, and exporting data. Pandas is a library for working with data with common high-level functions that simplify the processing steps of analytics and informatics.

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This lab is an application of feedback control for a temperature control device. The latest files are at https://apmonitor.com/heat.htm


Heat output is adjusted by modulating the voltage to a transistor. A thermistor measures the temperature. Energy from…

An overview of a a Process Dynamics and Control course with Python. Example applications include vehicle speed control, tanks, reactors, systems biology, Arduino temperature control, and many others. The course leads with applications and reinforces with…

This lab is an application of feedback control for a temperature control device. Heat output is adjusted by modulating the voltage to a transistor. A thermistor measures the temperature. Energy from the transistor output is transferred by conduction and convection…

Big data and the Industrial Internet of Things (IIoT) rely on data transfer to consolidate and share information. There are many methods to acquire and send data for industrial systems with a range of proprietary and community-based standards that facilitate…

The engineers at Raspberry Pi needed a solution for debugging Arm-based MCUs. They developed a solution: the Raspberry Pi Debug Probe.

The conservation of energy is used as a foundational principle to derive the transient temperature response of a heater. An Arduino-based temperature lab tests the energy balance prediction. See https://apmonitor.com/heat.htm

pyFirmata is an additional library package for Python that allows serial communication between a Python program on a PC and an Arduino. It gives access to read or write any of the Analog or Digital pins on the Arduino.

For PI control of the TCLab, use the IMC and ITAE tuning correlations and compare the integral absolute error difference between setpoint and measured temperature for a setpoint change from 23 to 60 degC.

Common tuning correlations for PI control are the…