In this project course, we aim to develop an advance AI framework for air pollution forecasting that takes into consideration environmental factors such as wind and temperature. The project will involve the following tasks: 1. Upgrading the LSTM framework: The student will update our previously developed LSTM framework to incorporate environmental factors that influence air pollutant consideration. They will use Python and deep learning libraries such as TensorFlow to implement the updated framework. 2. Model training and evaluation. The student will train the updated LSTM model on the preprocessed data and evaluate its performance using metrics such as mean absolute error, root mean squared error, and coefficient of determination (R-squared). By completing the project, the student will gain valuable experience in deep learning, data preprocessing, and environmental science. Students should seek the course instructor's approval to take this course.