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Applying Linear Algebra with R

Brandon Strain
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This course is no longer available. Find something similar by browsing:
Linear Algebra R Programming Regression Analysis Machine Learning Basics Matrix Arithmetic

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Read about what's good
what should give you pause
and possible dealbreakers
Builds a strong foundation for beginners who want to better understand foundational methods used in regression and machine learning
Develops basic matrix mathematics that will help build your foundation for multiple applications
Gives learners an edge in understanding innovation and groundbreaking topics in linear algebra
Explores linear algebra in R, which is standard in industry
Teaches skills, knowledge, and tools that are highly relevant to industry

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Career center

Learners who complete Applying Linear Algebra with R will develop knowledge and skills that may be useful to these careers:
Data Scientist
Many Data Scientists use linear algebra and regression to make sense of big data. This course could help you to build a foundation for understanding these techniques with an eye towards data science. In particular, the section covering how to put this math together into real world applications will be especially helpful.
See salaries and explore the career path for Data Scientist
Statistician
Statisticians must know linear algebra for working with big data sets. This course focuses specifically on applying linear algebra to datasets which could be particularly valuable.
See salaries and explore the career path for Statistician
Machine Learning Engineer
Linear algebra and regression are foundational topics in machine learning and many Machine Learning Engineers have these skills. While the course touches on these topics, a deeper dive into them would be needed to fully succeed as a Machine Learning Engineer. Still, this course could be a strong starting point for someone looking to work in this field.
See salaries and explore the career path for Machine Learning Engineer
Actuary
Actuaries may need to work with regression and big data to calculate risk in insurance and pension plans. This course covers these topics and could help an aspiring actuary build a solid foundation.
See salaries and explore the career path for Actuary
Operations Research Analyst
These professionals use machine learning and regression to understand and improve complex business processes. This course could be a solid starting block for someone looking to become an Operations Research Analyst.
See salaries and explore the career path for Operations Research Analyst
Data Analyst
Data Analysts use data to solve business problems and linear regression and machine learning are often their tools for doing so. This course could help a Data Analyst in their foundational knowledge of these topics.
See salaries and explore the career path for Data Analyst
Data Engineer
Data Engineers prepare big data for use with machine learning and other analytic tools. This course could provide a solid foundation for someone in this role, especially the sections on matrix arithmetic.
See salaries and explore the career path for Data Engineer
Market Research Analyst
Market Research Analysts use linear regression to analyze big datasets and understand consumer behavior. This course covers these topics and could help an aspiring analyst gain valuable skills.
See salaries and explore the career path for Market Research Analyst
Quantitative Analyst
Quantitative Analysts use big data to help investment firms make better decisions. They frequently use regression and machine learning and this course could provide a useful introduction to these topics.
See salaries and explore the career path for Quantitative Analyst
Business Analyst
Business Analysts use data to help companies make better decisions. This course could help someone in this role understand how to apply linear regression and other techniques to big data.
See salaries and explore the career path for Business Analyst
Software Engineer
Software Engineers often work with data and may need to use linear regression or machine learning to build features or train models. This course could provide valuable foundational knowledge to someone in this role.
See salaries and explore the career path for Software Engineer
Risk Manager
Risk Managers use data to assess and mitigate risk. This course could provide valuable knowledge to someone in this role, especially the section on linear regression in R. which can help to analyze and predict risk.
See salaries and explore the career path for Risk Manager
Database Administrator
Database Administrators maintain and optimize databases, which often requires working with big data. This course could provide valuable knowledge to someone in this role, especially the section on extracting important information from large data sets.
See salaries and explore the career path for Database Administrator
Financial Analyst
This course may be useful for Financial Analysts, as many use linear regression to better understand the stock market and make predictions. While the focus of this course is not finance, the foundational linear algebra knowledge it provides could be helpful to a Financial Analyst.
See salaries and explore the career path for Financial Analyst
Product Manager
Product Managers often work with data to understand customer needs and improve products and services. This course could provide useful foundational knowledge, especially the sections on matrix arithmetic and extracting information from large datasets.
See salaries and explore the career path for Product Manager

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Applying Linear Algebra with R.
Cover image
Matrix Computations
Save
Provides a comprehensive introduction to matrix computations, with a focus on algorithms and their implementation. It valuable resource for students who want to learn how to use linear algebra to solve computational problems.
Matrix Computations (Johns Hopkins Studies in the...
Hardcover
$$$
Cover image
Numerical Linear Algebra
Save
Provides a comprehensive introduction to numerical linear algebra, with a focus on the theory and implementation of algorithms. It valuable resource for students who want to learn how to use linear algebra to solve computational problems.
Numerical Linear Algebra: Twenty-Fifth Anniversary...
Paperback
$$$
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Linear Algebra with Applications
Save
This textbook provides a thorough treatment of linear algebra, with a focus on applications in engineering and the sciences. It valuable resource for students who want to learn how to use linear algebra to solve real-world problems.
Linear Algebra with Application, 5ed
Paperback
$$
Student Solutions Manual for Linear Algebra with...
Paperback
$$$
Linear Algebra with Applications: Pearson New...
Paperback
$$$
Linear Algebra with Applications (2nd Edition)
Hardcover
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Linear Algebra With Applications
Hardcover
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Student's Solutions Manual for Linear Algebra with...
Paperback
$$$
Linear Algebra With Applications
Hardcover
$$
Linear Algebra with Applications
Paperback
$$$
Linear Algebra and Application
Paperback
$$
Linear Algebra with Applications
Kindle Edition
$$$
Introduction to Linear Algebra
Save
This classic textbook provides a comprehensive introduction to linear algebra, covering the basics as well as advanced topics such as eigenvalues and eigenvectors. It valuable resource for anyone who wants to deepen their understanding of linear algebra.
Introduction to Linear Algebra (Gilbert Strang, 5)
Hardcover
$$$
Introduction to Linear Algebra (Gilbert Strang)
Hardcover
$$$$
Introduction to Linear Algebra, Third Edition
Hardcover
$$$
Introduction to Linear Algebra
Hardcover
$$$
Introduction To Linear Algebra, 5Th Edn
Hardcover
$$$
Introduction to Linear Algebra
Paperback
$$$$
Introduction to Linear Algebra
Hardcover
$$$
Cover image
Applied Linear Statistical Models
Save
Provides a comprehensive introduction to applied linear statistical models, with a focus on the use of R. It valuable resource for students who want to learn how to use linear algebra to model and analyze data.
Applied Linear Statistical Models 5ed (Pb 2013)
Paperback
$$
Applied Linear Statistical Models: Regression,...
Hardcover
$$
Cover image
An Introduction to Statistical Learning
Save
Provides a comprehensive introduction to statistical learning, with a focus on the use of R. It valuable resource for students who want to learn how to use linear algebra to model and analyze data.
An Introduction to Statistical Learning: with...
Hardcover
$$$
Cover image
The Elements of Statistical Learning
Save
Provides a comprehensive introduction to statistical learning, with a focus on the use of R. It valuable resource for students who want to learn how to use linear algebra to model and analyze data.
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Kindle Edition
$$$
Cover image
Machine Learning with R
Save
Provides a comprehensive introduction to machine learning, with a focus on the use of R. It valuable resource for students who want to learn how to use linear algebra to model and analyze data.
Machine Learning with R - Fourth Edition: Learn...
Paperback
$$
Machine Learning with R - Second Edition: Expert...
Kindle Edition
$$
Machine Learning with R - Third Edition: Expert...
Paperback
$$
(Italiano) Machine Learning con R: Conoscere le tecniche per...
Kindle Edition
$$
R: Unleash Machine Learning Techniques
Kindle Edition
$$$
Machine Learning with R: Learn How to Use R to...
Paperback
$$
(中文) Machine learning and R language (3rd edition of the...
Paperback
$$
Cover image
Deep Learning with R, Second Edition
Save
Provides a comprehensive introduction to deep learning, with a focus on the use of R. It valuable resource for students who want to learn how to use linear algebra to model and analyze data.
Deep Learning with R, Second Edition
Paperback
$$$
Deep Learning with R, Second Edition
Kindle Edition
$$
Cover image
Reinforcement Learning, second edition
Save
Provides a comprehensive introduction to reinforcement learning, with a focus on the use of R. It valuable resource for students who want to learn how to use linear algebra to model and analyze data.
Reinforcement Learning, second edition: An...
Hardcover
$$$
Reinforcement Learning, second edition: An...
Kindle Edition
$$$
Cover image
Text Mining with R
Save
Provides a comprehensive introduction to natural language processing, with a focus on the use of R. It valuable resource for students who want to learn how to use linear algebra to model and analyze data.
Text Mining with R
Paperback
Check
Text Mining with R
Kindle Edition
Check
Introduction to Linear Algebra
Save
This introductory textbook provides a clear and concise overview of linear algebra. It good choice for students who are new to the subject or who need a refresher.
Introduction to Linear Algebra (Gilbert Strang)
Hardcover
$$$$
Cover image
Linear Algebra and Its Applications, Global Edition
Save
This textbook provides a comprehensive introduction to linear algebra, with a focus on applications in business and economics. It good choice for students who are interested in using linear algebra to model and solve business problems.
Linear Algebra and Its Applications, Global Edition
Paperback
Check
Linear Algebra and Its Applications, Global Edition
Kindle Edition
Check
Cover image
Linear Models with Python
Save
Provides a comprehensive introduction to linear models, with a focus on the use of R. It valuable resource for students who want to learn how to use linear algebra to model and analyze data.
Linear Models with Python (Chapman & Hall/CRC Texts...
Hardcover
$$$
Linear Models with Python (Chapman & Hall/CRC Texts...
Kindle Edition
$$$

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Time
1 hours
Via
Pluralsight
Instructor
Brandon Strain
This course belongs to a collection called Building Statistical and Mathematical Models with R. It's comprised of nine courses:
  1. Understanding Statistical Models and Mathematical Models
  2. Solving Problems with Numerical Methods
  3. Applying the Mathematical MASS Model with R
  4. Applying Differential Equations and Inverse Models with R
  5. Performing Dimension Analysis with R
  6. Applying Linear Algebra with R (viewing)
  7. Building Statistical Summaries with R
  8. Implementing Bootstrap Methods in R
  9. Implementing Monte Carlo Method in R
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Builds a strong foundation for beginners who want to better understand foundational methods used in regression and machine learning
Develops basic matrix mathematics that will help build your foundation for multiple applications
Gives learners an edge in understanding innovation and groundbreaking topics in linear algebra
Explores linear algebra in R, which is standard in industry
Teaches skills, knowledge, and tools that are highly relevant to industry
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