Duration: 5 days – 35 hrs
Overview
This course provides participants with a comprehensive understanding of how Artificial Intelligence (AI) is revolutionizing the automotive industry. Through real-world examples, case studies, and hands-on activities, participants will explore AI applications in autonomous driving, smart manufacturing, predictive maintenance, and in-vehicle systems. By the end of the course, they will gain the knowledge and skills to apply AI technologies to solve complex automotive challenges and improve operational efficiency.
Objectives
• Understand the role of AI in transforming the automotive industry, including its applications in autonomous driving, manufacturing, and vehicle diagnostics.
• Explore AI technologies such as machine learning, neural networks, and computer vision used in autonomous vehicles and smart systems.
• Gain insights into AI-driven predictive maintenance, enabling proactive vehicle diagnostics and reducing downtime.
• Learn how AI optimizes automotive manufacturing processes and supply chain management for improved efficiency.
• Analyze ethical and regulatory considerations surrounding AI in the automotive sector, ensuring compliance and safety.
• Apply AI techniques through hands-on projects, including object detection and predictive maintenance models.
Audience
• Automotive engineers, designers, and developers
• Data scientists and AI specialists
• Professionals working in automotive manufacturing, supply chain, or customer experience
• Technology enthusiasts and automotive professionals interested in AI
Prerequisites
• Basic understanding of automotive systems and technology
• Familiarity with programming concepts (e.g., Python) and data analysis
• Knowledge of machine learning or AI fundamentals is helpful but not required
• Interest in the application of AI technologies within the automotive industry
Course Content
Module 1: Introduction to Artificial Intelligence in Automotive
• Overview of AI and Machine Learning (ML)
o What is AI?
o Types of AI (Narrow, General, Super AI)
o Role of ML in AI advancements
• History of AI in the Automotive Industry
o Evolution of AI in automotive applications
o Key milestones and innovations
Module 2: AI in Autonomous Driving
• Understanding Autonomous Vehicles
o Levels of vehicle autonomy (SAE Levels 0-5)
o Core technologies behind self-driving cars (sensors, LIDAR, RADAR, cameras)
• AI Algorithms for Autonomous Driving
o Object detection and recognition
o Path planning and decision-making
o Reinforcement learning and its applications in autonomous navigation
• Challenges in Autonomous Driving
o Regulatory issues
o Safety and ethical considerations
Module 3: AI in Automotive Manufacturing and Supply Chain
• AI in Smart Manufacturing (Industry 4.0)
o Role of AI in optimizing production lines
o Predictive maintenance using AI and IoT
• AI-Driven Supply Chain Optimization
o Use of AI in managing inventories and logistics
o Forecasting demand with AI
Module 4: AI in Predictive Maintenance and Vehicle Diagnostics
• Predictive Maintenance Overview
o How AI models predict equipment failures
o Benefits of predictive maintenance for automotive companies
• AI in Vehicle Diagnostics
o AI-powered diagnostic systems
o Predicting component wear and tear
Module 5: AI in Automotive Design and Engineering
• AI-Powered Design Tools
o How AI assists in vehicle design
o Generative design algorithms
• AI in Engineering Simulation
o Use of AI in crash simulations and performance testing
o Optimizing engineering workflows with AI
Module 6: AI in Customer Experience and Personalization
• AI-Powered In-Vehicle Assistants
o Voice recognition systems (e.g., natural language processing)
o Personalized infotainment systems
• AI for Predictive Personalization
o Analyzing driver behavior to personalize vehicle settings
o AI-enabled driver assistance systems
Module 7: The Future of AI in Automotive
• Emerging Trends in AI and Automotive Technology
o AI in electric vehicles (EVs)
o The rise of connected and smart cars
• AI and the Future of Mobility
o AI’s role in shared mobility, ride-hailing, and robo-taxis
o Integration of AI with V2X (vehicle-to-everything) technologies
Module 8: Ethical and Regulatory Considerations
• AI Ethics in Automotive
o Handling biases in AI models
o Ethical dilemmas in autonomous decision-making
• Regulatory Framework for AI in Automotive
o Current regulations for AI in the automotive industry
o Compliance and safety standards
Module 9: Hands-On Projects and Case Studies
• Case Study 1: AI in Autonomous Vehicle Development
o Real-world example from leading automakers
• Case Study 2: AI in Predictive Maintenance Implementation
• Practical Workshop
o Building a simple AI model for vehicle component failure prediction
o Implementing AI for object detection in self-driving cars
Module 10: Conclusion and Future Opportunities
• Key Takeaways
o Summary of AI’s impact on the automotive industry
• Future Career Opportunities in AI and Automotive
o AI-related roles in automotive engineering, data science, and research
