Course Information

Introduce your child to the exciting world of Artificial Intelligence with our course! This program teaches young students the basics of using PyTorch, a popular open-source machine learning library, to build and train artificial intelligence models.

Our course covers important topics such as neural networks, deep learning, supervised and unsupervised learning, and computer vision. It also includes hands-on training on creating and implementing AI models using PyTorch. The goal of our AI course is to equip students with the knowledge and skills needed to understand and work with AI, and to develop an interest in computer science and technology.

Make learning fun and interactive with our course that uses examples, exercises and projects that are age-appropriate and designed to make it easy for children to understand and practice AI concepts. The course will build interesting models to generate their own cartoon characters at the end to make learning enjoyable and engaging for children. Give your child a head start in the AI industry and enroll them in our AI and Pytorch course today!

Course Duration:

50 Minutes/Lecture

Class Consumption:

5 Points/Lecture

Prerequisites:

Python, Mathematics

Table of Course Content

Please take note that this content is subjected to change. Click the left black triangle to view details of each section.

Introduction for Building Your AI Models
  • Introduction to Deep Learning
  • Neural Networks Basics
  • Deep Neural Networks
  • Gradient Descent I
  • Gradient Descent II
Pytorch Basics
  • Pytorch Basics I
  • Pytorch Basics II
  • Pytorch Basics III
  • Pytorch Exercise Time
Convolutional Neural Networks
  • Foundations of Convolutional Neural Networks
  • Convolutional Neural Networks Models
  • Object Detection
  • Face Recognition
  • Neural Style Transfer
Convolutional Neural Networks Project
  • Build a Classifier For Cartoon Characters I
  • Build a Classifier For Cartoon Characters II
Natural Language Processing
  • Word Embeddings
  • Recurrent Neural Networks
  • Attention Mechanism
  • Transformer
  • Bert, GPT2 and Future
Natural Language Processing Project
  • Build a Translator I
  • Build a Translator II
  • Build a Translator III
Generative Models
  • Generative adversarial networks I
  • Generative adversarial networks II
  • Build Your Own Cartoon Character With GAN I
  • Build Your Own Cartoon Character With GAN II
  • Build Your Own Cartoon Character With GAN III
Build Your Own Models
  • Discuss Your Project I
  • Discuss Your Project II
  • Prepare Your Models
  • Find a Dataset
  • Exercise Time I
  • Exercise Time II
  • Exercise Time III
  • Presentation Time