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Generative Ai For Automotive Engineers
Published 7/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 2h 45m | Size: 814 MB
1000+ GenAI prompts for Smarter Automotive Engineering
What you'll learn[/center]

Understand how Generative AI applies to core mechanical and automotive engineering contexts.
Apply over 1000 expert-level prompts provided in the course to real-world design, Automotive, manufacturing, and diagnostics.
Identify engineering decisions and workflows that can be translated into structured AI prompts.
Explore the use of large language models (LLMs) in CAD support, simulation input generation, diagnostics, and documentation.
Recognize the limitations of LLMs in high-precision engineering tasks and apply prompt-based techniques to mitigate errors.
Learn how to structure prompts for generating technical, dimensional, and tabular outputs suitable for engineering use.
Embed engineering constraints, material specs, parameters, and roles into prompt templates for higher accuracy.
Use system-level prompts to simulate roles like co-designer, quality inspector, or diagnostic expert.
Build layered prompts for clarity, verification, and progressive output refinement.
Generate prompts for concept sketches, parametric design, and constraint-based CAD outputs.
Automate Bill of Material generation and produce CAD-ready design tables through prompt sequences.
Create virtual test setups using prompts for stress, thermal, vibration, and crash simulations.
Generate structured prompts for interpreting FEA, CFD, and digital twin data.
Develop diagnostic prompts for OBD-II and CAN code interpretation, fault isolation, and repair recommendation.
Design chained prompt workflows for predictive maintenance and condition monitoring.
Write prompts that support process sheet generation, torque specifications, robotic assembly, and jig setup.
Use prompts to classify painted/welded surface defects and auto-generate inspection checklists.
Automate NCR and CAPA documentation and create traceable audit logs using generative outputs.
Convert test logs and design sessions into markdown reports, approval slide decks, and BOM summaries.
Build and deploy a reusable prompt library tailored to engineering roles and tasks.
Requirements
Basic Understanding of Automotive Engineering Concepts
Description
This course, Generative AI for Automotive Engineers, is designed for professionals seeking to embed AI-powered prompt engineering into core automotive workflows-from concept to production. The course begins by exploring how Generative AI integrates with mechanical and automotive contexts, followed by identifying decision points that can be converted into effective prompt sequences. It delves into the role of language models in CAD, simulation, and diagnostics, and addresses the inherent limitations of LLMs in precision tasks-providing methods to mitigate those gaps through structured prompt design.The second part focuses on crafting high-impact engineering prompts. Learners will practice writing prompts for technical, tabular, and dimensional outputs, embedding parameters and constraints effectively, and using system prompts to simulate roles like AI co-designer or virtual inspector. Techniques such as clarification loops, verification prompts, and expansion prompts are introduced to enhance reliability and control. Moving into CAD applications, the course teaches how to generate concept sketches and constraint-based designs, automate Bill of Material creation, iterate lightweight EV components, and produce CAD-ready outputs with dimensions and tolerances.In the simulation section, students write prompts for boundary condition setups, crash scenario generation, and thermal or structural model interpretation. For diagnostics, the course trains learners to interpret OBD-II and CAN codes, build NLP-based fault trees, compose intelligent maintenance prompts, and design end-to-end diagnostic chains. Manufacturing support is covered through process sheet generation, torque and sequence prompts, tooling instructions, and preventive maintenance flows. Learners also tackle visual defect classification in painted or welded surfaces, prompt-based checklist creation, NCR and CAPA automation, and quality log generation. The course concludes with reporting prompts that convert logs and designs into markdown reports, BoM summaries, approval decks, and audit logs.To support ongoing use, learners receive a curated library of 1000 expert-level prompts across design, diagnostics, simulation, assembly, and inspection-ready for real-world engineering tasks.
Who this course is for
Automotive Engineers and Mechanical Designers
Simulation and Test Engineers
Manufacturing and Production Engineers
Quality Assurance and Inspection Professionals
Vehicle Diagnostics and Maintenance Technicians
Engineering Managers and Technical Leads
R&D and Innovation Teams in Automotive OEMs or Tier-1 Suppliers
Engineering Students and Early Career Professionals