Fundamental Linear Algebra Concepts with Python

Howard University via Coursera

Go to Course: https://www.coursera.org/learn/linear-algebra-concepts-python

Introduction

### Course Review: Fundamental Linear Algebra Concepts with Python For anyone eager to delve into the world of linear algebra while harnessing the power of Python programming, the **Fundamental Linear Algebra Concepts with Python** course on Coursera stands out as a remarkable choice. This course is perfect for students, data scientists, and professionals interested in building a solid mathematical foundation with practical applications. #### Course Overview This course provides a thorough introduction to key linear algebra concepts starting with the fundamentals of finding matrix inverses and progressing through essential operations and applications using Python. You will engage hands-on with Python throughout, ensuring the theoretical concepts are well understood and can be effectively applied in real-world scenarios. #### Course Syllabus Breakdown 1. **Introduction to Finding Inverses** - **Overview**: The journey begins with the fundamental definitions of linear equations. You will learn how to find the determinant of matrices and the importance of inverses in linear algebra. - **Learning Objectives**: By the end of this module, students will be proficient in using Python commands to manipulate matrices and will understand how these operations relate to inverse matrices. 2. **Introduction to Matrix Algebra with Python** - **Overview**: Building upon the first module, you'll explore matrix algebra functions in greater depth. This module emphasizes performing operations on larger datasets. - **Learning Objectives**: Students will become adept in executing various matrix algebra functions using Python, allowing them to work efficiently with more complex data structures. 3. **Solving Systems of Linear Equations** - **Overview**: This module focuses on one of the most practical applications of linear algebra: solving systems of linear equations. - **Learning Objectives**: You will learn several methods for finding solutions to linear equation systems, solidifying your understanding of how these principles apply in practice. 4. **Eigenvalues and Eigenvectors** - **Overview**: The final module brings all the concepts together. Here, you will engage with the important concepts of eigenvalues and eigenvectors, which are pivotal in many applications, including machine learning and data science. - **Learning Objectives**: Students will apply their knowledge through real-world examples, learning about linear transformations and the significance of eigenvalues and eigenvectors in practical applications. #### Course Highlights - **Practical Approach**: The course emphasizes hands-on learning with Python, enabling students to not only understand but also implement linear algebra concepts. - **Real-World Applications**: The final module's focus on applying learned concepts to real-world problems gives students the confidence to use their skills in practical scenarios. - **Structured Learning Path**: The course is well-structured, ensuring that each module builds upon the previous, facilitating a comprehensive understanding of the subject. #### Recommendations I highly recommend the **Fundamental Linear Algebra Concepts with Python** course for anyone looking to enhance their mathematical skills in a practical and applied manner. Whether you are a beginner looking to understand linear algebra or an experienced individual seeking to brush up on your skills with Python, this course has something valuable to offer. Moreover, the course caters well to modern data-related fields, making it particularly advantageous for aspiring data scientists and analysts. The integration of Python, a leading programming language in data science, into the study of linear algebra provides a significant edge in today’s data-driven job market. Whether you're aiming to advance your studies, improve your career prospects, or simply expand your knowledge, this course is a worthwhile investment in your educational journey. In conclusion, if you're ready to tackle linear algebra with Python and explore its vast applications, enroll in this course on Coursera today and enjoy the transition from theory to practical skill development!

Syllabus

Introduction to Finding Inverses

In module 1, you’ll learn how to define linear equations, how to use Python to find the determinant of matrices and how to perform different commands using Python. We will cover the following learning objectives.

Introduction to Matrix Algebra with Python

Let’s recap! In module 1, you learned how to define linear equations, how to use Python to find the determinant of matrices and how to perform different commands using Python. In module 2, you’ll learn how to explain different matrix algebra functions, perform matrix algebra on large data sets using Python. We will cover the following learning objectives.

Solving Systems of Linear Equations

Let’s recap! In module 2, you learned how to explain different matrix algebra functions and perform matrix algebra on large data sets using Python. In module 3, you will learn how to solve systems of linear equations using several methods. We will cover the following learning objectives.

Eigenvalues and Eigenvectors

Welcome to the final module of this course! Over the past 3 modules, you have been introduced to and gained knowledge on the following topics: determinants, inverses, matrix algebra with Python, row reduction and, systems of linear equations. In the final module of the course, you’ll apply what you’ve learned to concrete, real-world examples. You’ll practice using linear transformation, Eigenvalues and Eigenvectors, and solving applications. We will cover the following learning objectives.