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Free Download Digital Twin Applications in Automotive Engineering
Published 8/2025
Created by Aditya Bharat Patil
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 11 Lectures ( 2h 0m ) | Size: 597 MB
A Complete Guide to Digital Twins in Automotive: Learn Vehicle Simulation, Virtual Testing & Real-Time Diagnostics
What you'll learn
Mechanical, Mechatronics, and Automotive Engineers
Embedded Systems and Control Engineers
Product Development and R&D Teams
Systems Engineers & MBSE Practitioners
Fleet Operations Managers & Maintenance Engineers
Graduate Students & Researchers in Automotive or Systems Engineering
Professionals transitioning into Automotive AI, IoT, or Digital Manufacturing
Requirements
Basic knowledge of mechanical or automotive systems Familiarity with engineering design or simulation concepts No prior experience with digital twins or programming needed Optional: Exposure to tools like MATLAB, CAD, or Python is helpful but not required
Description
The future of automotive engineering is here - and it's digital, dynamic, and data-driven.In this in-depth course, you'll explore how Digital Twin technology is transforming the design, testing, optimization, and lifecycle management of modern vehicles. From high-fidelity simulation to predictive maintenance and real-time telemetry, digital twins are changing how we build and operate intelligent, high-performance automotive systems.Whether you're an engineer, product developer, systems architect, or technical leader - this course will equip you with the tools and frameworks to understand, apply, and lead in the age of digital twins.What You'll Learn Core concepts behind digital twins and their evolution in automotive systems How digital twins are applied across design, simulation, control, and testing The role of MBSE (Model-Based Systems Engineering) and digital thread integration Fleet-wide data collection, edge computing, and cloud-twin synchronization Predictive maintenance, OTA updates, and real-world industry case studies Future trends: AI-augmented twins, quantum simulation, neuromorphic control, and blockchain Who This Course is ForMechanical, Automotive, and Mechatronics EngineersEmbedded Systems and Control EngineersR&D and Product Development TeamsMBSE Practitioners and Systems EngineersFleet Managers, Diagnostics, and Reliability ProfessionalsGraduate Students and Industry Transitioners exploring AI, IoT, or Smart Manufacturing What You NeedA basic understanding of mechanical or automotive systemsFamiliarity with engineering modeling, simulation, or system designNo prior experience with digital twins, AI, or programming is requiredBy the end of this course, you'll be able to design and deploy digital twin frameworks, connect physical systems to simulation environments, and understand how data, physics, and software combine to drive real-time decisions across the automotive product lifecycle.Join us and build the future of automotive innovation, one twin at a time.
Who this course is for
Basic understanding of mechanical or automotive systems Familiarity with engineering concepts like simulation or control systems No prior experience with digital twin tools or AI required Optional: experience with CAD, MATLAB, or Python is helpful but not necessary This course is designed to guide you step-by-step - from foundational concepts to real-world applications.
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