该不该选Data and Knowledge Modeling and Analysis这门课？

这门课是学校一个搞AI，ML的老师开的课。不知道和machine learning有多大的关系？project要用到matlab/python/R. 如果有了解的同学，可以说一下上这门课价值大不大吗？先在此谢过！！
Course Description

Engineers encounter data in many of their tasks. Whether the sources of this data may be experiments, databases, computer files, or the Internet, there is a dire need for effective methods to model and analyze the data and extract useful knowledge and information from it. This course aims to provide engineering graduate students with essential knowledge of data representation, grouping, mining and knowledge discovery.

Major Topics

Data types, sources, nature, scales and distributions
Data representations, transformation, dimensionality reduction and normalization
Classification: Statistical based, Distance based, Decision based.
Clustering: Partition-based, Hierarchical, Model and Density based, others.
Retrieval and Mining: Similarity measures and matching techniques.
Knowledge discovery in data: Association rules mining, web mining, text mining.
Performance measures and tools: Statistical Analysis, Validity and Assessment Measures.

个人认为非常有用，值得一上

跟ML的基础原理相关的内容不多
感觉更偏向数据挖掘
我觉得很有用

感谢楼上的两位啊！