Name: Senior Experiment Kit
Suitable Age: Grades 10 to 12
Product Introduction: The Senior Experiment Kit features an integrated design and is developed based on the Linux system, offering an out-of-the-box experience. It supports artificial intelligence learning, data processing and analysis, as well as data management. Equipped with a wealth of sensor modules including light, temperature and humidity, infrared, ultrasonic, and potentiometer sensors, it also supports external devices such as servo motors, digital tubes and LCD display modules, enabling flexible hardware control and diverse experimental scenarios.
Course Introduction: The accompanying curriculum provides a complete learning path, ranging from Python programming fundamentals to artificial intelligence applications. In the beginner stage, students start with Python syntax and basic hardware experiments, completing hands-on projects such as servo motor control, infrared alarm systems, light detection, and temperature and humidity monitoring. In the intermediate stage, they advance to ultrasonic distance measurement, IoT communication, web scraping, data processing, and visualization, developing skills in data analysis and network application development. In the advanced stage, students dive into machine learning and deep learning, exploring scikit-learn and neural networks to build projects like speech recognition, facial recognition, handwritten digit recognition, and advertisement prediction, ultimately achieving seamless integration of AI and IoT technologies.
Course Catalog
| No. | Course Name | No. | Course Name |
| Lesson 1 | Python Basic Syntax | Lesson 20 | Python Basics: Numpy |
| Lesson 2 | Python Operators | Lesson 21 | Python Basics: Pandas |
| Lesson 3 | Conditions and Loops | Lesson 22 | Python Basics: Data Visualization |
| Lesson 4 | Strings and Lists | Lesson 23 | Python Basics: Web Crawler |
| Lesson 5 | Dictionaries | Lesson 24 | Basic Knowledge of Machine Learning |
| Lesson 6 | Function Application | Lesson 25 | scikit-learn Library |
| Lesson 7 | File Processing | Lesson 26 | Linear Regression Algorithm |
| Lesson 8 | LED Light Experiment | Lesson 27 | Decision Tree |
| Lesson 9 | Key Experiment | Lesson 28 | K-Nearest Neighbors (KNN) Algorithm |
| Lesson 10 | Servo Motor Experiment | Lesson 29 | K-Means Clustering |
| Lesson 11 | Infrared Alarm Experiment | Lesson 30 | Speech Recognition |
| Lesson 12 | Light Sensor Experiment | Lesson 31 | Image Recognition Application |
| Lesson 13 | Temperature and Humidity Sensor Experiment | Lesson 32 | Face Recognition Application |
| Lesson 14 | Potentiometer Experiment | Lesson 33 | Text Recognition Application |
| Lesson 15 | Ultrasonic Experiment | Lesson 34 | Neural Networks and Deep Learning |
| Lesson 16 | Nixie Tube Experiment | Lesson 35 | Neural Networks and Machine Learning: Ancient Poetry Generator |
| Lesson 17 | Dot Matrix Screen Experiment | Lesson 36 | Neural Networks and Machine Learning: Advertising Prediction |
| Lesson 18 | Internet of Things (IoT) Experiment | Lesson 37 | Neural Networks and Machine Learning: Gesture Recognition |
| Lesson 19 | Internet Experiment | Lesson 38 | Neural Networks and Machine Learning: Handwritten Digit Recognition |
| Lesson 39 | Neural Networks and Machine Learning: Image Clustering |