本課程旨在培養學生具備資料科學、機器學習與人工智慧之基礎理論與實務應用能力，透過資料擷取與處理、模型建構、程式設計與實際資料集操作，使學生掌握人工智慧專案之基本技能。課程目標包括: 奠定資料科學與人工智慧基礎知識, 培養資料蒐集、處理與特徵工程能力, 熟悉模型之建構與分析方法, 掌握模型最佳化技術, 理解 Transformer 與注意力機制之原理及應用, 培養人工智慧實務整合與問題解決能力。

This course aims to cultivate students' basic theoretical and practical application abilities in data science, machine learning and artificial intelligence. Through data acquisition and processing, model construction, programming and actual data set operation, students will master the basic skills of artificial intelligence projects. Course objectives include: laying the basic knowledge of data science and artificial intelligence, cultivating data collection, processing and feature engineering capabilities, becoming familiar with model construction and analysis methods, mastering model optimization technology, understanding the principles and applications of Transformer and attention mechanisms, and cultivating practical integration and problem-solving capabilities of artificial intelligence.

1. Python資料科學自學聖經：不只是建模！用實戰帶你預測趨勢、找出問題與發現價值 (基峯,ACL065700) (Book 1)
2. StatQuest 圖解神經網路與深度學習 (深智, DM2619) (Book 2)

1. Python data science self-study bible: not just modeling! Use practical experience to help you predict trends, identify problems and discover value (Jifeng, ACL065700) (Book 1)
2. StatQuest Graphical Neural Networks and Deep Learning (Deepzhi, DM2619) (Book 2)