Artificial Intelligence (AI) in Automotive Training Course
This course explores the application of AI within the automotive industry, placing particular emphasis on Machine Learning and Deep Learning. It equips learners to identify suitable technologies for various in-vehicle scenarios, ranging from basic automation and image recognition to complex autonomous decision-making processes.
This course is available as onsite live training in Latvia or online live training.Course Outline
Current State of Technology
- Existing applications
- Potential future uses
Rules-Based AI
- Simplifying decision-making processes
Machine Learning
- Classification
- Clustering
- Neural Networks
- Types of Neural Networks
- Review of working examples and discussion
Deep Learning
- Essential terminology
- Determining when to use (or avoid) Deep Learning
- Estimating computational resources and costs
- Brief theoretical foundation for Deep Neural Networks
Deep Learning in Practice (primarily using TensorFlow)
- Data preparation
- Selecting the loss function
- Choosing the appropriate neural network architecture
- Balancing accuracy against speed and resource usage
- Training the neural network
- Evaluating efficiency and error rates
Sample Use Cases
- Anomaly detection
- Image recognition
- ADAS (Advanced Driver Assistance Systems)
Requirements
Participants are expected to possess programming experience in any language and an engineering background. However, hands-on coding is not required during the course sessions.
Open Training Courses require 5+ participants.
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