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Course Outline
Foundations of AI in Autonomous Vehicles
- Examining autonomous driving levels and the role of AI integration
- Survey of key AI frameworks and libraries utilized in the field
- Current trends and emerging innovations in vehicle autonomy
Core Deep Learning Concepts for Driving
- Neural network architectures tailored for self-driving cars
- Use of Convolutional Neural Networks (CNNs) for image analysis
- Application of Recurrent Neural Networks (RNNs) to temporal data streams
Computer Vision Applications in Driving
- Object detection strategies using YOLO and SSD architectures
- Techniques for lane detection and road adherence
- Semantic segmentation for comprehensive environmental perception
Reinforcement Learning for Driving Decisions
- Markov Decision Processes (MDP) applied to autonomous vehicles
- Training Deep Reinforcement Learning (DRL) models
- Simulation-based approaches for developing driving policies
Sensor Fusion and Environmental Perception
- Integration of LiDAR, RADAR, and camera data streams
- Application of Kalman filtering and sensor fusion methods
- Processing multi-sensor data for precise environment mapping
Deep Learning for Driving Prediction
- Constructing models for behavioral prediction
- Forecasting trajectories to facilitate obstacle avoidance
- Recognizing driver state and intent
Model Assessment and Optimization
- Evaluating model accuracy and performance metrics
- Optimizing models for real-time execution efficiency
- Deployment strategies for trained models on vehicle platforms
Case Studies and Practical Applications
- Analysis of autonomous vehicle incidents and associated safety issues
- Review of successful deployments of AI-driven driving systems
- Project: Development of a functional lane-following AI model
Requirements
- Strong command of Python programming
- Practical experience with machine learning and deep learning frameworks
- Working knowledge of automotive technologies and computer vision principles
Target Audience
- Data scientists seeking to specialize in autonomous driving applications
- AI specialists dedicated to the development of automotive intelligence
- Developers exploring the application of deep learning in self-driving technologies
21 Hours
