程式設計與人工智慧(二)

臺北科技大學 114-2 學期課程，課號 355724。

課程大綱

本課程為「程式設計與人工智慧（一）」之進階課程，著重於 Python 程式設計的延伸應用，並導入機器學習與深度學習之核心概念。課程以 TensorFlow 與 Keras 為主要工具，透過實作多層感知器（MLP）、卷積神經網路（CNN）及循環神經網路（RNN），使學生具備人工智慧模型建構、訓練、評估與應用的能力。 This course is a continuation of Programming and Artificial Intelligence (I). It focuses on advanced Python-based programming techniques and introduces students to machine learning and deep learning concepts. Using TensorFlow and Keras, students will learn to design, train, evaluate, and deploy neural network models, including Multilayer Perceptrons (MLP), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN), through hands-on practice and real-world datasets.

課程進度

1. Course Introduction 2. Overview of Artificial Intelligence, Machine Learning, and Deep Learning 3. Introduction to TensorFlow and Keras 4. Setting Up the Deep Learning Development Environment 5. GPU Acceleration and CUDA Configuration 6. Midterm Exam I 7. Fundamentals of Multilayer Perceptrons (MLP) 8. Data Preprocessing and Feature Engineering 9. MLP Implementation: Handwritten Digit Recognition 10. Model Evaluation and Overfitting Prevention 11. Fundamentals of Convolutional Neural Networks (CNN) 12. CNN Implementation: Image Classification 13. Fundamentals of Recurrent Neural Networks (RNN) 14. Midterm Exam II 15. RNN Implementation: Time-Series Prediction 16. Model Saving and Loading 17. Model Deployment and Practical Applications 18. Final Exam ※ Course schedule and content are subject to adjustment based on students’ learning progress.

評量方式

Midterm Exam I: 30% Midterm Exam II: 30% Final Exam: 40% ※ Evaluation items and grading weights are subject to adjustment based on students’ learning progress.

教材

【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】 使用外文原文書：否 參考書籍: Python零基礎入門班 碁峰圖書 精通 Python｜運用簡單的套件進行現代運算 碁峰圖書 機器學習與深度學習特訓班 碁峰圖書