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Course Outline
Introduction to AI in Autonomous Vehicles
- Comprehending levels of autonomy and the role of AI integration
- Survey of key AI frameworks and libraries utilized in autonomous driving
- Emerging trends and innovations in AI-driven vehicle autonomy
Deep Learning Foundations for Autonomous Driving
- Neural network architectures tailored for self-driving cars
- Convolutional Neural Networks (CNNs) for image analysis
- Recurrent Neural Networks (RNNs) for processing temporal data
Computer Vision for 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
- Applying Markov Decision Processes (MDP) in autonomous vehicles
- Training Deep Reinforcement Learning (DRL) models
- Learning driving policies through simulation-based environments
Sensor Fusion and Perception
- Combining LiDAR, RADAR, and camera data streams
- Kalman filtering and advanced sensor fusion methods
- Processing multi-sensor data for environment mapping
Deep Learning Models for Driving Prediction
- Creating models for behavioral prediction
- Forecasting trajectories for obstacle avoidance
- Recognizing driver state and intent
Model Evaluation and Optimization
- Key metrics for assessing model accuracy and performance
- Optimization strategies for real-time execution
- Deploying trained models onto autonomous vehicle platforms
Case Studies and Real-World Applications
- Examining incidents and safety challenges in autonomous vehicles
- Reviewing successful deployments of AI-driven driving systems
- Practical project: Building 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 seeking to specialize in autonomous driving applications
- AI specialists focused on developing automotive AI solutions
- Developers interested in applying deep learning techniques to self-driving vehicles
21 Hours
