Linear Algebra for Data Science in R
|
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.
Linear algebra is one of the most important set of tools in applied mathematics and data science. In this course, you’ll learn how to work with vectors and matrices, solve matrix-vector equations, perform eigenvalue/eigenvector analyses and use principal component analysis to do dimension reduction on real-world datasets. All analyses will be performed in R, one of the world’s most-popular programming languages.
User Reviews
Be the first to review “Linear Algebra for Data Science in R”
Related Products
Real-Time Analytics with Apache Storm
Study the use of Apache Storm for processing real-time data streams and generating insights on-the-fly.
Data Analyst
Learn the skills to analyze, interpret, and present data for informed business decisions.
Predictive Analytics for Business
Learn to predict future outcomes and trends through statistical modeling techniques.
Learn Python 3
Learn the basics of Python 3.12, one of the most powerful, versatile, and in-demand programming languages today.
Learn Python for Data Science
Get started with Python for Data Science in this beginner-friendly skill path.
Intro to Data Analysis
Understand the principles of data analysis, including techniques for data collection, cleaning, and interpretation.
There are no reviews yet.