- Python Programming
- Data Model
- Eigenvalues And Eigenvectors
- Matrices
- Linear Algebra
Offered By


What you will learn
Use Python to solve vector equations
Apply linear algebra concepts such as the inverse of a matrix, row reduction, and eigenvalues and eigenvectors
Use regression models
Apply linear algebra to analyze data, create, and make predictions based off of a regression model
Skills you will gain
About this Specialization
Applied Learning Project
Throughout this specialization, learners can practice individually and with peers using Python and linear algebra concepts. Learners will also engage in programming assignments, peer-graded assignments, quizzes, and discussion topics such as data modeling and matrices. For the Capstone project, learners will employ linear regression models to solve real-world problems, apply skills to analyze data, and develop linear regression models to make predictions.
Familiarity with mathematical thinking and concepts, some knowledge of Calculus, and a basic understanding of Python (all of these are not required)
Familiarity with mathematical thinking and concepts, some knowledge of Calculus, and a basic understanding of Python (all of these are not required)
How the Specialization Works
Take Courses
A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.
Hands-on Project
Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.
Earn a Certificate
When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.

There are 4 Courses in this Specialization
Introduction to Linear Algebra and Python
This course is the first of a series that is designed for beginners who want to learn how to apply basic data science concepts to real-world problems. You might be a student who is considering pursuing a career in data science and wanting to learn more, or you might be a business professional who wants to apply some data science principles to your work. Or, you might simply be a curious, lifelong learner intrigued by the powerful tools that data science and math provides. Regardless of your motivation, we’ll provide you with the support and information you need to get started.
Fundamental Linear Algebra Concepts with Python
In this course, you'll be introduced to finding inverses and matrix algebra using Python. You will also practice using row reduction to solve linear equations as well as practice how to define linear transformations. Let's get started!
Building Regression Models with Linear Algebra
In this course, you'll learn how to distinguish between the different types of regression models. You will apply the Method of Least Squares to a dataset by hand and using Python. In addition, you will learn how to employ a linear regression model to identify scenarios. Let's get started!
Capstone: Data Science Problem in Linear Algebra Framework
In this course, you'll review the specifics of the Capstone project. In addition, you will create and run your regression model and share your results with your peers. Let's get started!
Offered by

Howard University
Founded in 1867, Howard University is a private, research university that is comprised of 14 schools and colleges. Students pursue more than 140 programs of study leading to undergraduate, graduate and professional degrees. The University operates with a commitment to Excellence in Truth and Service and has produced one Schwarzman Scholar, three Marshall Scholars, four Rhodes Scholars, 12 Truman Scholars, 25 Pickering Fellows and more than 165 Fulbright recipients. Howard also produces more on-campus African American Ph.D. recipients than any other university in the United States. For more information on Howard University, visit www.howard.edu.
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