113年第1學期-6121 Business Analytics and AI Application 課程資訊
評分方式
評分項目 | 配分比例 | 說明 |
---|---|---|
Course Participation and Interaction | 30 | Students are required to attend class |
Assignment | 30 | |
Final exam/presentation | 40 |
選課分析
本課程名額為 50人,已有40 人選讀,尚餘名額10人。
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授課教師
金泰星教育目標
Students in this course will develop a comprehensive understanding of business analysis and AI fundamentals, covering topics such as business requirement analysis, data collection, and machine learning. Through hands-on exercises, students will gain proficiency in Python programming, from basic syntax to advanced techniques essential for business data and AI projects. Additionally, students will acquire data analysis skills using tools like Pandas and NumPy for data cleaning, analysis, and visualization, aiding in informed business decision-making. They will also learn web data extraction techniques, including HTML, CSS, and Beautiful Soup. With an introduction to machine learning tools such as Scikit-Learn, participants will be equipped to comprehend, implement, and evaluate machine learning models. Lastly, ethical considerations in AI projects and risk management approaches in business analysis and AI will be explored to ensure responsible and effective application of these technologies.
課程資訊
基本資料
必修課,學分數:3-0
上課時間:三/6,7,8[M023]
修課班級:國企碩學程1
修課年級:1年級以上
選課備註:English-Taught Course for All-Major Senior/Graduate Students
教師與教學助理
授課教師:金泰星
大班TA或教學助理:尚無資料
Office HourOffice hours are to be announced in class. Appointments can also be made with prior arrangement.
授課大綱
授課大綱:開啟授課大綱(授課計畫表)
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參考書目
1. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython 2nd Edition, William McKinney (Author), 2017.
2. AI-Powered Business Intelligence: Improving Forecasts and Decision Making with Machine Learning 1st Edition, Tobias Zwingmann (Author), 2022.
3. Automate the Boring Stuff with Python, 2nd Edition: Practical Programming for Total Beginners 2nd, Al Sweigart (Author), 2015.
開課紀錄
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