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Duration 21 hours
Course Outline
Introduction to AI in Autonomous Vehicles
- Exploring autonomous driving levels and the role of AI integration
- Survey of AI frameworks and libraries prevalent in autonomous driving
- Emerging trends and innovations in AI-driven vehicle autonomy
Deep Learning Basics for Autonomous Driving
- Neural network architectures suited for self-driving cars
- Convolutional neural networks (CNNs) for image analysis
- Recurrent neural networks (RNNs) for handling temporal data
Computer Vision for Autonomous Driving
- Object detection implementations using YOLO and SSD
- Methods for lane detection and road-following strategies
- Semantic segmentation techniques for environmental awareness
Reinforcement Learning for Driving Decisions
- Application of Markov Decision Processes (MDP) in autonomous vehicles
- Training deep reinforcement learning (DRL) models
- Simulation-based approaches for developing driving policies
Sensor Fusion and Perception
- Combining data from LiDAR, RADAR, and cameras
- Techniques for Kalman filtering and sensor fusion
- Processing multi-sensor data for comprehensive environment mapping
Deep Learning Models for Driving Prediction
- Constructing behavioral prediction models
- Forecasting trajectories for effective 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 efficiency
- Deployment of trained models on autonomous vehicle platforms
Case Studies and Real-World Applications
- Reviewing autonomous vehicle incidents and associated safety challenges
- Examining successful case studies of AI-driven driving systems
- Capstone Project: Developing an AI model for lane-following
Requirements
- Solid 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 dedicated to automotive AI development
- Developers exploring deep learning applications for self-driving vehicles
