This course teaches AI infrastructure from the shallower to the deeper, step by step, and lays the foundation for AI learning. It is a compulsory course for stepping into the door of AI learning. You will learn data processing Python suites (Numpy, Pandas, Scipy, Matplotlib, Seaborn...); learn to use scikit-learn to implement machine learning algorithms (Regression, Decision Forest, KNN or Kmeans, etc.) in application topics, and verify models Performance and parameter tuning to optimize the model; learn to use Keras/TensorFlow to build deep neural networks, such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Reinforcement Learning, and Generative Confrontation Internet (Generative Adversarial Networks), etc., to realize artificial intelligence topics such as face recognition and natural language dialogue.