AI課程：Sensors in Self-driving Car

Lesson 1: Introduction of AI Lesson 1 focuses on having an overview of AI, and train your own self-driving car using 10Botics AutoGo. 

 

Lesson 2: Image Processing Lesson 2 talks about how does the computer read an image, and transform the images using Colab. 

 

Lesson 3: Image Classification Lesson 3 will walk you through the algorithms used in supervised learning – KNN & SVM, and how does the computer make use of the data to train an autopilot model.

 

Lesson 4: Neural Network Lesson 4 Introduces the neural network and teaches activation functions and optimization. You can try different model type in 10Botics AutoGo

 

Lesson 5: Convolution Neural Network (CNN) Lesson 5 introduces covolutional neural network, and try different model type in 10Botics AutoGo. 

 

Lesson 6: Overfitting & Augmentation Lesson 6 introduces overfitting, and teaches you how to determine whether a model is good-fit or overfit or underfit. If it is overfitting, we can improve it by data augmentation.

 

Lesson 7: Transfer Learning Lesson 7 introduces transfer learning and how to use it in 10Botics AutoGo. You can even have an in-class racing to apply all the knowledge you’ve learnt before.

 

Lesson 8: Sensors in Self-driving Car Lesson 8 introduces the sensors in 10Botics AutoGo and self-driving car in the reality. You can add a ultrasonic sensor in AutoGo to stop the car from crushing.

 

Lesson 9: Ethics, Legal & Social Impacts Lesson 9 discusses the effects of self-driving car in society in different aspects, including ethics, legal and social.