AI course for K12 Students

Learn AI By Building A Self-Driving Car

Description


The course introduces the fundamental knowledge of artificial intelligence (AI) using 10Botics AutoGo. It covers the basic of image processing and machine learning methods as well as neural network and convolutional neural network (CNN). Students have to apply the knowledge and principles learned to train their own self-driving car using 10Botics AutoGo.

The course is suitable for Grade 6 to Grade 12 students. The recommended duration of the course is 12 hours with a maximum of 12 students a class. It does not require any prior knowledge to programming as all the training process could be done in an app. The students could have hands-on experience in AI, they could experiment whatever they want with the 10Botics AutoGo. After the course, students can leverage various deep learning and computer vision technology to extend the capability of the car to solve different challenges from the real world.

Who This Course Is For


  • Anyone who is interested in self-driving technology and donkey cars
  • Anyone who wants to learn the basic concept of machine learning and deep learning
  • Teachers who want to teach AI in the simplest and fun way
  • All skill levels are welcome!

Requirements


Highlights


  • Learn the fundamentals of AI and machine learning
  • Train a self-driving vehicle (10Botics AutoGo) with an app
  • A step-by-step guide to getting started with the 10Botics AutoGo
  • All the training process can be done in an app and without a GPU
  • Learning through play and experiment!

Learning Outcomes


  • The students should be able to:
  • Understand the fundamental of AI
  • Train a machine learning model
  • Acquire the skills in improving the machine learning model
  • Leverage various deep learning and computer vision technology to extend the capability of the car

Curriculum


Lesson 1: Five Big Ideas in Artificial Intelligence (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.

Our Partners

Google Colab

Raspberry Pi

Google TensorFlow

Google Coral

Nvidia Jetson Nano

Course feedback

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