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Course Outline
Introduction to AI in Autonomous Vehicles
- Exploring autonomous driving levels and AI integration.
- Reviewing AI frameworks and libraries utilized in autonomous driving.
- Examining trends and innovations in AI-powered vehicle autonomy.
Deep Learning Fundamentals for Autonomous Driving
- Neural network architectures designed for self-driving cars.
- Using convolutional neural networks (CNNs) for image processing.
- Utilizing recurrent neural networks (RNNs) for temporal data analysis.
Computer Vision for Autonomous Driving
- Object detection using YOLO and SSD.
- Lane detection and road following techniques.
- Semantic segmentation for comprehensive environmental perception.
Reinforcement Learning for Driving Decisions
- Applying Markov Decision Processes (MDP) in autonomous vehicles.
- Training deep reinforcement learning (DRL) models.
- Simulation-based learning for driving policy development.
Sensor Fusion and Perception
- Integrating LiDAR, RADAR, and camera data.
- Kalman filtering and sensor fusion techniques.
- Multi-sensor data processing for environment mapping.
Deep Learning Models for Driving Prediction
- Constructing behavioral prediction models.
- Trajectory forecasting for obstacle avoidance.
- Recognizing driver state and intent.
Model Evaluation and Optimization
- Evaluating metrics for model accuracy and performance.
- Optimization techniques for real-time execution.
- Deploying trained models on autonomous vehicle platforms.
Case Studies and Real-World Applications
- Analyzing autonomous vehicle incidents and safety challenges.
- Exploring successful implementations of AI-driven driving systems.
- Project: Developing a lane-following AI model.
Summary and Next Steps
Requirements
- Strong proficiency in Python programming.
- Prior experience with machine learning and deep learning frameworks.
- Knowledge of automotive technology and computer vision concepts.
Target Audience
- Data scientists targeting autonomous driving projects.
- AI specialists dedicated to automotive AI development.
- Developers keen on applying deep learning to self-driving vehicle technologies.
21 Hours
