A practical, no-code course on how aerospace and mechanical engineers actually use AI in 2026. Learn AI-accelerated CFD/FEA workflows, generative design in Fusion 360, AI-assisted MATLAB/Simulink, digital twins, predictive maintenance, AI for materials selection, and how to use LLMs for requirements engineering and standards research without compromising safety or traceability. Built for engineering students and early-career engineers. Earn a free certificate to add to your LinkedIn and resume.
Aerospace and mechanical engineers work with simulation, design iteration, and compliance-heavy documentation every day. This free course shows you how AI tools fit into those existing workflows without replacing engineering judgment. You will work through AI-accelerated CFD and FEA with Ansys SimAI, generative design in Fusion 360 and Siemens NX, AI-assisted materials selection, digital twins, predictive maintenance, and smarter MATLAB and Simulink workflows. The course is built for engineering students and early-career engineers who want to apply AI in their own field, not learn a new one.
Beyond design and simulation, the course covers the compliance side of engineering AI. You will learn how to use LLMs for requirements engineering and traceability, and how to read standards and technical papers faster without losing the safety mindset that aerospace and mechanical work demands. Every module treats verification as non-negotiable, because the course knows that AI output in an engineering context must be checked before it is trusted.
The course is completely free. Complete all modules and pass the final exam to earn a certificate of completion you can add to your LinkedIn profile or resume. Whether you are studying aerospace engineering, working in a mechanical design role, or just starting your career, this course gives you a practical foundation for integrating AI into the engineering workflows you already use.
4 modules • 10 lessons
The course covers AI-accelerated CFD and FEA with Ansys SimAI, generative design in Fusion 360 and Siemens NX, AI for materials selection, digital twins and predictive maintenance in aerospace, AI-assisted MATLAB and Simulink workflows, and using LLMs for requirements engineering and reading technical standards faster.
Yes, the course is completely free. After completing all modules and passing the final exam, you receive a certificate of completion that you can add to your LinkedIn profile or resume.
No prior AI experience is required. The course is designed for engineering students and early-career engineers who already know their engineering domain and want to learn how AI fits into it. Familiarity with concepts like CFD, FEA, or MATLAB is helpful but not mandatory.
Yes. The course dedicates a full module to requirements engineering, traceability, and reading standards such as DO-178C with AI assistance. It also builds a verification mindset throughout every module, because aerospace and mechanical work requires checking AI output before acting on it.
The course covers Ansys SimAI for simulation, Fusion 360 and Siemens NX for generative design, MATLAB and Simulink with AI-assisted workflows, and large language models for requirements and standards research. All workflows are practical and no-code where possible.
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