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Course Outline
Introduction to AI in Autonomous Vehicles
- Understanding levels of autonomous driving and the role of AI integration
- Review of AI frameworks and libraries utilized in the autonomous driving sector
- Emerging trends and innovations in AI-driven vehicle autonomy
Deep Learning Foundations for Autonomous Driving
- Neural network architectures suited for self-driving applications
- Convolutional neural networks (CNNs) for image analysis
- Recurrent neural networks (RNNs) for processing temporal data
Computer Vision in Autonomous Driving
- Object detection implementation using YOLO and SSD
- Methods for lane detection and road following
- Applying semantic segmentation for environmental awareness
Reinforcement Learning for Driving Decisions
- Application of Markov Decision Processes (MDP) in autonomous vehicles
- Training deep reinforcement learning (DRL) models
- Simulation-based approaches for developing driving policies
Sensor Fusion and Perception Systems
- Synthesizing data from LiDAR, RADAR, and cameras
- Using Kalman filtering and advanced sensor fusion techniques
- Processing multi-sensor data for accurate environment mapping
Deep Learning Models for Driving Prediction
- Creating models for behavioral prediction
- Forecasting trajectories to ensure obstacle avoidance
- Recognizing driver state and intent
Model Evaluation and Optimization
- Defining metrics for model accuracy and overall performance
- Optimizing models for real-time execution efficiency
- Deploying trained models onto autonomous vehicle platforms
Case Studies and Real-World Applications
- Analyzing incidents in autonomous vehicles and associated safety challenges
- Examining successful deployments of AI-driven driving systems
- Practical project: Developing an AI model for lane following
Requirements
- Strong proficiency in Python programming
- Practical experience with machine learning and deep learning frameworks
- Working knowledge of automotive technologies and computer vision principles
Target Audience
- Data scientists looking to specialize in autonomous driving solutions
- AI specialists dedicated to automotive AI innovation
- Developers seeking to apply deep learning techniques to self-driving car technologies
21 Hours
