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Course Outline
Foundations of AI in Autonomous Vehicles
- Exploring autonomous driving levels and the integration of AI
- Reviewing key AI frameworks and libraries utilized in autonomous driving
- Examining current trends and innovations in AI-powered vehicle autonomy
Deep Learning Essentials for Autonomous Driving
- Neural network architectures tailored for self-driving cars
- Convolutional Neural Networks (CNNs) for image processing
- Recurrent Neural Networks (RNNs) for handling temporal data
Computer Vision in Autonomous Driving
- Object detection using YOLO and SSD architectures
- Techniques for lane detection and road following
- Semantic segmentation for environmental awareness
Reinforcement Learning for Driving Decisions
- Markov Decision Processes (MDP) applied to autonomous vehicles
- Training Deep Reinforcement Learning (DRL) models
- Simulation-based approaches for learning driving policies
Sensor Fusion and Perception
- Combining data from LiDAR, RADAR, and cameras
- Applying Kalman filtering and sensor fusion methods
- Processing multi-sensor data for comprehensive environment mapping
Deep Learning Models for Driving Prediction
- Constructing behavioral prediction models
- Trajectory forecasting to enable obstacle avoidance
- Recognizing driver state and intent
Model Evaluation and Optimization
- Defining metrics for model accuracy and performance
- Optimization strategies for real-time execution
- Deploying trained models onto autonomous vehicle platforms
Case Studies and Practical Applications
- Reviewing autonomous vehicle incidents and associated safety challenges
- Investigating successful deployments of AI-driven driving systems
- Project: Developing an AI model for lane following
Requirements
- Strong proficiency in Python programming
- Practical experience with machine learning and deep learning frameworks
- Knowledge of automotive technology and computer vision principles
Target Audience
- Data scientists aspiring to specialize in autonomous driving applications
- AI specialists concentrating on automotive AI development
- Developers eager to apply deep learning techniques to self-driving vehicles
21 Hours
