人工智慧：機器學習與理論基礎 (Artificial Intelligence - Learning & Theory)
本課程第二部分著重在和人工智慧密不可分的機器學習。課程內容包含了機器學習基礎理論（包含 1990 年代發展的VC理論）、分類器（包含決策樹及支援向量機）、神經網路（包含深度學習）及增強式學習（包含深度增強式學習。此部份技術包含最早追溯至 1950 年代直到最近 2016 年附近的最新發展。此課程從基礎理論開始，簡介了各機器學習主流技法以及從淺層學習架構演變到最近深度架構的轉換。
本課程之核心目標為：
（一）使同學對人工智慧相關的機器學習技術有基礎概念
（二）同學能夠理解機器學習基礎理論、分類器、神經網路、增強式學習
（三）同學能將相關技術應用到自己的問題上
修課前，基礎背景知識：
需要的先備知識：計算機概論
建議的先備知識：資料結構與演算法
None
Syllabus
Syllabus - What you will learn from this course
Week 1
Concept learning
Week 2
Computational Learning Theory
Week 3
Classification
Week 4
Neural Network and Deep learning
Week 5
Reinforcement learning
FAQ
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Reviews
Professor Ding's teaching is conscientious and the lectures are clearly explained
整體上, 是值得推薦的入門課程, 把machine learning的基本課程與熱門的topics提出來講. 習題的內容算簡單, 大部份在檢驗觀念.
