A reading that introduces numerical ODE-based simulation of thermal systems — covering Newton's law of cooling and related heat-transfer models — which learners use to understand how to model and solve temperature-evolution problems computationally.
Topics
This module covers 8 topics. Open a topic to see its subtopics.
Module Content
9 items.
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A reading that outlines the full engineering data workflow from raw data acquisition through cleaning, exploration, and analysis, giving learners and instructors a conceptual roadmap for the topics covered throughout the module.
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A reading that covers how to load raw engineering datasets into Python, inspect their structure, identify data-type issues, duplicates, and index misalignments, serving as a practical starting point for any data analysis task.
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A reading that explains techniques for detecting and handling missing values, outliers, sensor saturation, and formatting errors in raw engineering datasets, which learners apply to prepare data for reliable analysis or model training.
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A reading that teaches how to use matplotlib to create and customize engineering plots — including time-series, comparison, and distribution charts — which learners use to visualize and communicate data and simulation results effectively.
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A reading that introduces ordinary differential equations and numerical time-stepping methods (such as Euler and Runge-Kutta) as the foundation for simulating dynamic engineering systems, which learners use before tackling domain-specific simulation topics.
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A reading that covers numerical simulation of mechanical systems such as mass-spring-damper models, explaining how to set up and solve their governing ODEs to predict vibration, resonance, and transient behavior.
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A reading that explains how to model and numerically simulate RC and RLC electrical circuits using ODE methods derived from Kirchhoff's laws, which learners use to predict voltage and current dynamics over time.
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A reading that introduces numerical ODE-based simulation of thermal systems — covering Newton's law of cooling and related heat-transfer models — which learners use to understand how to model and solve temperature-evolution problems computationally.