本課程同時著重理論基礎與實務能力，使學生具有完整的深度學習理論與實務， 並能應用在人工智慧領域，帶學生從深度學習在【機器視覺】、【藝術生成】和【遊戲對局】 3 大領域的應用面看起，並學習 3 大領域背後所用的技術, 包括卷積神經網路 (CNN)、循環神經網路 (RNN)、對抗式生成網路 (GAN)、深度強化式學習 (DRL)...等等。本課程的實做工具選擇了馬上就可以動手的 Google Colab 線上開發環境搭配 tf.Keras 框架來實作。

This course emphasizes both theoretical foundations and practical skills, providing students with comprehensive knowledge of deep learning theory and applications. It equips them to apply this knowledge in the field of artificial intelligence. The course introduces students to the applications of deep learning in three major areas: machine vision, art generation, and game playing. Students will also learn the underlying techniques used in these areas, including Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Generative Adversarial Networks (GAN), and Deep Reinforcement Learning (DRL), among others.
For hands-on practice, the course uses Google Colab, an online development environment, along with the tf.Keras framework for implementation.