大數據分析、機器學習、與人工智慧方法

• 開課系所 : 管理學院碩士班
• 授課教師 : 康藝晃
• 授課方式 : 課堂講授
• 學分數 : 3學分

課程目標

This course is designed for students who need hands-on training of data engineering, machine learning, and general understanding of AI. We will begin with introduction to the rise and evolution of the Data Science. Its applications in various fields, such as business, healthcare, insurance, and finance, will also be discussed. This course covers the basic concepts of Big Data Analytics, Data Engineering, Business Analytics, MapReduce Design Patterns, Supervised & Unsupervised Machine Learning, in-memory computing, Functional Programming, Deep Neural Networks, and Machine Learning Interpretability. Students will also be introduced to how to use R programming language and its packages to solve real-world big data problems.

課程大綱

1. Students will be introduced to theories & techniques in different fields related to AI, including probability & statistics, scientific computing, data engineering, algorithm design, statistical learning, deep learning, and explainable AI.
2. Prerequisite: Basic understanding of relational databases, SQL, data structures, probability & statistics, college-level calculus, and matrix operations are required. Familiar with at least one high-level programming language. Scientific programming language, such as R, Matlab, Python, Scala, Julia, and SAS are preferred. Students who have taken CM502 are welcomed.