Learning goals for MTH348

Role in Curriculum

Data science, machine learning and AI are increasingly important technologies with major impacts. An effective understanding of the underlying algorithms and implementation difficulties requires a deeper understanding of linear algebra than that provided by the current linear algebra course MTH 338. The aim of this course is to provide the additional foundational concepts needed, with an emphasis on effective computational methods. In particular, this course aims to prepare our majors for further study at the graduate level in data science and AI.

Learning Goals and Assessment

Students will be able to find canonical forms for matrices

When the class is being assessed, the final exams will include embedded questions to assess student performance on these topic-specific learning goals.

Students will be able to find exponentials of matrices.

Same.

Students will be able to apply factorization algorithms.

Same.

Students will be able to apply principal component analysis algorithms.

Same.

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When assessment activities are done, the results will be summarized in memorandum form and filed with the department chairperson for record keeping purposes.

Information obtained from assessment will be used to assess and self-reflect on the success of the course and to make any necessary changes to improve teaching and learning effectiveness.