Special Topic - AI Marine Application Course

AI4kids cooperated with Professor Huang Yingzhe's team from Sun Yat-sen University to record audio-visual teaching.
Through online learning, you can step into the cross-disciplinary practical courses of AI and marine biology!

This course provides a preview of some chapters and units. You are welcome to watch and learn first before deciding whether to purchase the full course!

What you will learn in this online course

YOLO technical background: computer vision, CNN, YOLO training profile, introduction to Cloud AIoT system architecture, and network environment.

【Teacher Introduction】

Professor Huang Yingzhe from Sun Yat-sen University

Professor Huang Yingzhe is a professor in the Department of Education at Sun Yat-sen University. His main research areas include educational psychology, educational measurement, instructional design and technology, and qualitative research methods. His research results have been published in several international journals and he serves on the editorial boards of several international journals.

In addition, Professor Huang Ying-Che also serves as a director of several education-related associations, including the Educational Psychology Association of the Republic of China, the Taiwan Educational Measurement Association, and the International Association for Technology in Education. He has also won several awards related to educational research, such as the Taiwan Academic Award.

【Detailed chapter content】

Unit 1 AIoT Concept
Content: Introduction to the background and vision of AIoT
Unit 2 AIoT Display
Contents: Turtle Eggs
Unit 3 Topic Introduction: Smart Aquarium
Content:Introduction to the application and architecture of smart aquarium
Unit 4 YOLO technical background: computer vision, CNN
Content: Introduction to the background knowledge of deep learning image recognition
Unit 5 YOLO technical background: YOLO introduction and presentation
Content: Introduction to YOLO and its technical features
Unit 6 YOLO Training Profile Unit 7 YOLO Technical Background: YOLO Implementation
Content: Use aquarium videos as materials to conduct labeling teaching and practice. Then train YOLO for smart aquarium
Unit 8: Sample requirements in the context of smart aquariums, the impact of sample labeling accuracy, the impact of water quality and light source Unit 9: Practical labeling demonstration
Content: labelimg
Unit 10: Setting up cameras and establishing video streaming
Content: Using the local network camera as the source to create a video stream
Unit 11 introduces Cloud AIoT system architecture and network environment
Content:Introduction to the AIoT architecture of cloud computing (data flow)
Unit 12 YOLO Example on Colab
Content: Using Google Colab cloud computing as a platform, receive image streams, run YOLO, and perform real-time image recognition.
Unit 13 Test Assessment

Total course time: 3:42:22
Number of classes: 13

Assessment <br>Assessment question type: Multiple choice Number of assessment questions: 44 questions

Verification certificate

The certification certificate can be uploaded to the Ministry of Education's learning process platform .<br>The steps are as follows:
Log in to the learning history upload page → Multiple learning performance → Certification record → Domestic / Other / iQiyi Smart Technology / Certificate name (please select the test name) / Level score / Certificate code (please refer to the list below) → Upload supporting documents