❗The content presented here is sourced directly from Edx platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [March 06th, 2023]
What skills and knowledge will you acquire during this course?
The skills and knowledge that will be acquired during this course include:
- Understanding and applying matrix algebra in the context of linear models
- Using matrix operations to represent and analyze differences between experimental units
- Performing statistical inference on these differences
- Utilizing the R programming language for matrix operations
- Gaining proficiency in advanced statistical concepts such as hierarchical models
- Developing advanced software engineering skills, including parallel computing and reproducible research concepts
- Applying statistical and programming knowledge to analyze high-dimensional data
- Learning about experimental design and analysis of high-throughput experiments
- Familiarizing oneself with the Bioconductor package for genomics data analysis.
How does this course contribute to professional growth?
The course "Introduction to Linear Models and Matrix Algebra" contributes to professional growth by providing knowledge and skills in matrix algebra, statistical inference, and data analysis. It teaches students how to represent linear models using matrix algebra, which is a fundamental tool in experimental design and the analysis of high-dimensional data. The course also introduces students to the R programming language, which is commonly used for performing matrix operations and statistical analysis. By the third course, advanced statistical concepts such as hierarchical models are taught, and by the fourth course, advanced software engineering skills such as parallel computing and reproducible research concepts are covered. This course is part of two Professional Certificates, namely "Data Analysis for Life Sciences" and "Genomics Data Analysis," which can further enhance one's professional credentials. The course is self-paced, allowing students to learn at their own convenience. The class has received support from NIH grant R25GM114818.
Is this course suitable for preparing further education?
The course "Introduction to Linear Models and Matrix Algebra" is suitable for preparing further education.
