COURSE 01 · COMPUTATIONAL FOUNDATIONS WITH PYTHON

A six-session intensive course in scientific programming, numerical modeling, engineering visualization, and validated computational problem-solving.

COURSE OUTCOME

Translate governing equations into reliable Python workflows using NumPy, reusable functions, vectorized calculations, unit checks, and technical visualization.

SESSION ROADMAP

01 · Engineering Computation & Reproducible Workflows

02 · Arrays, Vectorization & Parameter Studies

03 · Scientific Visualization & Interpretation

04 · Thermal-Fluid Models & Validation

05 · Experimental Data & Uncertainty

06 · Integrated Computational Project

ENGINEERING LABS

• Classify internal-flow regimes using Reynolds number

• Model multilayer wall heat loss and insulation performance

• Predict transient tank-heating time from an energy balance

• Perform parameter sweeps and interpret sensitivity plots

• Validate results using units, limiting cases, and physical reasoning

DELIVERABLE

A documented, Colab-ready engineering analysis notebook with reusable functions, publication-quality plots, and verification checks.

TWO LEVELS OF CHALLENGE

CORE TRACK — guided implementation for students building Python fluency

ADVANCED TRACK — uncertainty analysis, nonlinear correlations, and model comparison

FINAL PROJECT OPTIONS

Thermal-system simulator · Heat-exchanger model · Performance predictor · Engineering design study