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Duration 21 hours
Course Outline
Introduction to AI in Autonomous Vehicles
- Exploring levels of autonomous driving and AI integration
- Survey of AI frameworks and libraries utilized in self-driving contexts
- Current trends and innovations in AI-driven vehicle autonomy
Deep Learning Foundations for Autonomous Driving
- Neural network architectures designed for self-driving cars
- Convolutional neural networks (CNNs) applied to image processing
- Recurrent neural networks (RNNs) for handling temporal data
Computer Vision Applications in Autonomous Driving
- Object detection using YOLO and SSD architectures
- Techniques for lane detection and road following
- Semantic segmentation for accurate environmental perception
Reinforcement Learning for Driving Decisions
- Application of Markov Decision Processes (MDP) in autonomous vehicles
- Training deep reinforcement learning (DRL) models
- Simulation-based learning approaches for driving policies
Sensor Fusion and Perception Systems
- Integrating data from LiDAR, RADAR, and cameras
- Applying Kalman filtering and other sensor fusion techniques
- Processing multi-sensor data for environmental mapping
Deep Learning Models for Driving Prediction
- Constructing behavioral prediction models
- Trajectory forecasting for effective 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 Real-World Applications
- Analyzing autonomous vehicle incidents and associated safety challenges
- Examining successful implementations of AI-driven driving systems
- Project: Development of a lane-following AI model
Requirements
- Strong proficiency in Python programming
- Practical experience with machine learning and deep learning frameworks
- Knowledge of automotive technology and computer vision concepts
Target Audience
- Data scientists aiming to specialize in autonomous driving applications
- AI specialists focused on developing automotive AI solutions
- Developers seeking to apply deep learning techniques to self-driving cars
