Difference between revisions of "IU:TestPage"
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=== What is the purpose of this course? === |
=== What is the purpose of this course? === |
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| + | === Course objectives based on Bloom’s taxonomy === |
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| + | |||
| + | ==== - What should a student remember at the end of the course? ==== |
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| + | By the end of the course, the students should be able to |
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| + | * List basic notions of linear algebra |
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| + | * Understand key principles involved in solution of linear equation systems and the properties of matrices |
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| + | * Linear regression analysis |
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| + | * Fast Fourier Transform |
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| + | * How to find eigenvalues and eigenvectors for matrix diagonalization and single value decomposition |
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| + | |||
| + | ==== - What should a student be able to understand at the end of the course? ==== |
||
| + | By the end of the course, the students should be able to |
||
| + | * Key principles involved in solution of linear equation systems and the properties of matrices |
||
| + | * Become familiar with the four fundamental subspaces |
||
| + | * Linear regression analysis |
||
| + | * Fast Fourier Transform |
||
| + | * How to find eigenvalues and eigenvectors for matrix diagonalization and single value decomposition |
||
| + | |||
| + | ==== - What should a student be able to apply at the end of the course? ==== |
||
| + | By the end of the course, the students should be able to |
||
| + | * Linear equation system solving by using the vector-matrix approach |
||
| + | * Make linear regression analysis |
||
| + | * Fast Fourier Transform |
||
| + | * To find eigenvalues and eigenvectors for matrix diagonalization and single value decomposition |
||
Revision as of 16:20, 9 March 2022
Analytical Geometry \& Linear Algebra -- II
- Course name: Analytical Geometry \& Linear Algebra -- II
- Course number: XYZ
Course Characteristics
Key concepts of the class
- fundamental principles of linear algebra,
- concepts of linear algebra objects and their representation in vector-matrix form
What is the purpose of this course?
Course objectives based on Bloom’s taxonomy
- What should a student remember at the end of the course?
By the end of the course, the students should be able to
- List basic notions of linear algebra
- Understand key principles involved in solution of linear equation systems and the properties of matrices
- Linear regression analysis
- Fast Fourier Transform
- How to find eigenvalues and eigenvectors for matrix diagonalization and single value decomposition
- What should a student be able to understand at the end of the course?
By the end of the course, the students should be able to
- Key principles involved in solution of linear equation systems and the properties of matrices
- Become familiar with the four fundamental subspaces
- Linear regression analysis
- Fast Fourier Transform
- How to find eigenvalues and eigenvectors for matrix diagonalization and single value decomposition
- What should a student be able to apply at the end of the course?
By the end of the course, the students should be able to
- Linear equation system solving by using the vector-matrix approach
- Make linear regression analysis
- Fast Fourier Transform
- To find eigenvalues and eigenvectors for matrix diagonalization and single value decomposition