Exploring Julia for Statistical and Numerical Techniques in Electrical Engineering: Case Studies Aligned with EAC Standard 2024

Abstract

In response to the Engineering Accreditation Council (EAC) Standard 2024, which mandates the integration of numerical and statistical techniques into engineering education, this paper advocates the adoption of the Julia programming language as a modern computational platform. Julia combines the speed of low-level languages with the intuitive syntax of high-level mathematical tools, making it ideal for electrical engineering curricula. This study presents practical case studies that illustrate Julia's application in solving circuit equations, performing frequency-domain signal analysis, and conducting data-driven modeling, key skills that directly map to Programme Outcomes (PO1, PO2, PO5). Julia's robust ecosystem, including packages such as DifferentialEquations.jl, Plots.jl, and Makie.jl support simulation, analysis, and high-quality visualization, enabling students to translate mathematical models into computational solutions effectively. Early pilot feedback suggests enhanced student engagement, deeper conceptual understanding, and stronger computational literacy. Rather than prescribing Julia, this paper offers a framework and encouragement for its integration wherever appropriate within engineering programs. Embedding Julia in labs, numerical courses, and final-year projects not only aligns with OBE and EAC standards but also equips graduates with industry-relevant skills for solving complex, data-driven engineering problems in a sustainable and accessible way.