108年第2學期-1152 Programming Design 課程資訊
評分方式
評分項目 | 配分比例 | 說明 |
---|---|---|
Homework in class and at home | 40 | |
Midterm Exam and Team Projects | 30 | |
Final Exam and Team Projects | 30 |
選課分析
本課程名額為 70人,已有49 人選讀,尚餘名額21人。
登入後可進行最愛課程追蹤 [按此登入]。
教育目標
Except for statistical learning, which is generally offered by mathematics or statistics
departments in the majority of the universities across the globe, the rest are taught by
computer science department. In the recent years, this separation is disappearing but
the collaboration between the two departments is still not complete. Programmers are
intimidated by the complex theorems and proofs and statisticians hate talking (read as
coding) to machines all the time. But as more industries are becoming data and product
driven, the need for getting the two departments to speak a common language is strongly
emphasized. Roles in industry are suitably revamped to create openings like machine
learning engineers, data engineers, and data scientists into a broad group being called the
data science team.
Electronic
課程資訊
基本資料
必修課,學分數:0-3
上課時間:四/6,7,8[M007]
修課班級:管理學院1
修課年級:年級以上
選課備註:全英語授課,限管院國際菁英組、僑生、外籍生選課。以人工加選,
教師與教學助理
授課教師:姜自強
大班TA或教學助理:尚無資料
Office Hour四/5
授課大綱
授課大綱:開啟授課大綱(授課計畫表)
(開在新視窗)
參考書目
1. Using R
2. Machine Learning Using R
Karthik Ramasubramanian
Abhishek Singh
開課紀錄
您可查詢過去本課程開課紀錄。 Programming Design歷史開課紀錄查詢