校際選修

115-1 選課時程

進行中

  • 初選第一階段 6/15/2026
  • 初選第二階段 6/22/2026
  • 校際選修 8/24/2026
  • 初選第三階段 8/31/2026
  • 開學後加退選 9/7/2026
  • 逾期加退選 9/21/2026
選課資源

人工智慧原理與實務

Artificial Intelligence: Concept and Practice

學期
109-2
學分
2 學分
當期課號
B836
永久課號
B1803
開課單位
生物醫學資訊研究所
授課教師
洪哲倫
校區
陽明
類別
選修
上課時間表
週一
3
10:10–11:00
人工智慧原理與實務
YR319
2 節連堂
4
11:10–12:00

* 根據陽明交大上課時間表所列

概述

本課程將會講授人工智慧的基礎知識,同時會也介紹基礎的人工智慧演算法以及實作演算法。在課程的期末專案,學生可以完成一個人工智慧應用。Conducting in English Artificial intelligence (AI) refers as simulation of human intelligence demonstrated by computers. The goal of AI is to create systems that understand, think, learn, and behave like humans to solve practical problems. Nowadays, many applications achieve great success by adopting AI, and, more over, AI technology can be more intelligent than human. In this course, we will study the most fundamental knowledge for understanding AI. We will introduce the basic AI algorithms and implementation of hands-on applications of these algorithms. In the final project, students will complete their AI-based applications.

教學方式

本課程主要的目的是要讓學生了解人工智慧基礎知識,同時學生可以學習如何撰寫人工智慧應用的程式。The purpose of this course is to provide the most fundamental knowledge to the students so that they can understand what the AI is. Meanwhile, students can learn how to programming AI for applications in practice.

週次計畫
週次主題
第 1 週Introduction to Artificial Intelligence
第 2 週Introduction to Artificial Intelligence
第 3 週The Concept of Machine Learning
第 4 週Machine Learning in Practice (1)
第 5 週Machine Learning in Practice (2)
第 6 週The Concept of Deep Learning
第 7 週Tomb Sweeping Day
第 8 週Introduction to Docker and Tools
第 9 週Convolutional Neural Network in Practice: Classification
第 10 週Convolutional Neural Network in Practice: Object Detection
第 11 週Convolutional Neural Network in Practice: Segmentation
第 12 週Final Project Presentation: Topic
第 13 週Recurrent Neural Network in Practice
第 14 週Natural Language Processing in Practice
第 15 週Inference on Embedded System
第 16 週Final Projection Presentation: Demonstration
第 17 週Dragon Boat Festival
第 18 週Final Projection Tuning
教科書

Deep Learning Ian Goodfellow, Yoshua Bengio, Aaron Courville ISBN: 0262035618 2016 Introduction to Deep Learning Eugene Charniak ISBN: 0262039516 2019