Introduction to Linear Algebra and Python (Coursera)

Offered by Howard University,
Introduction to Linear Algebra and Python (Coursera)

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.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

In this course, we'll cover the fundamentals of linear algebra, including systems of linear equations, matrix operations, and vector equations. Whether you’ve learned some of these concepts before and are looking for a refresher or you’re brand new to the ideas we’ll cover, you’ll find the materials to support you. Let's get started!
Course 1 of 4 in the Linear Algebra for Data Science Using Python Specialization.

Syllabus

WEEK 1
Introduction to Matrices and Linear Algebra
In module 1, you'll learn how to explain fundamental concepts of linear algebra and how to use Python, one of the most powerful programming languages, to model different data. We will cover the following learning objectives.

WEEK 2
Using Linear Algebra Concepts in Python
Let's recap! In module 1, you performed software installation, learned some best practices, and learned how graphs are used to model data in Python. In module 2, you'll gain the knowledge you need to use linear algebra to solve data science problems. You'll also perform matrix algebra on large data sets using Python. We will cover the following learning objectives.

WEEK 3
Vector Equations and Systems of Linear Equations
Let's recap! In module 2, you learned how to use linear algebra to solve data science problems. Using Python, you also learned how to perform matrix algebra on large data sets. In module 3, you will learn how to define vector equations and use vector equations to model data. We will cover the following learning objectives.

WEEK 4
Real-World Applications of Vector Equations
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:- Version control - Git Bash, Jupyter Notebook via Anaconda, NumPy and SymPy, and other software tools, Modeling data, Matrix algebra and, Vector equations. In the final module of the course, you'll apply what you've learned to concrete, real-world examples. You'll practice using vector equations to study data sets and provide peer reviews. We will cover the following learning objectives.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Global Warming II: Create Your Own Models in Python (Coursera) Coursera
University of Chicago

Global Warming II: Create Your Own Models in Python (Coursera)

This class provides a series of Python programming exercises intended to explore the use of numerical modeling in the Earth system and climate sciences. The scientific background for these models is presented in a companion class, Global Warming I: The Science and Modeling of Climate Change. This class assumes that you are new to Python programming (and this is indeed a great way to learn Python!), but that you will be able to pick up an elementary knowledge of Python syntax from another class or from on-line tutorials.

Sep 7th 2026
5-12 Weeks
AI for Efficient Programming: Harnessing the Power of LLMs (Coursera) Coursera
Fred Hutchinson Cancer Center

AI for Efficient Programming: Harnessing the Power of LLMs (Coursera)

This course on Artificial Intelligence (AI) for software development explores the use of AI large language models such as ChatGPT, Bard, and others and their potential benefits and challenges. Through examples and hands-on activities, you will develop an understanding of the ways in which AI can speed up software development tasks and free up time for more creative and strategic work.

Sep 7th 2026
4 Weeks
Understanding China, 1700-2000: A Data Analytic Approach, Part 2 (Coursera) Coursera
The Hong Kong University of Science and Technology - HKUST

Understanding China, 1700-2000: A Data Analytic Approach, Part 2 (Coursera)

The purpose of this course is to summarize new directions in Chinese history and social science produced by the creation and analysis of big historical datasets based on newly opened Chinese archival holdings, and to organize this knowledge in a framework that encourages learning about China in comparative perspective. Our course demonstrates how a new scholarship of discovery is redefining what is singular about modern China and modern Chinese history.

Aug 31st 2026
4 Weeks
Data Science in Stratified Healthcare and Precision Medicine (Coursera) Coursera
University of Edinburgh

Data Science in Stratified Healthcare and Precision Medicine (Coursera)

An increasing volume of data is becoming available in biomedicine and healthcare, from genomic data, to electronic patient records and data collected by wearable devices. Recent advances in data science are transforming the life sciences, leading to precision medicine and stratified healthcare. In this course, you will learn about some of the different types of data and computational methods involved in stratified healthcare and precision medicine.

Sep 7th 2026
5-12 Weeks
An Introduction to Interactive Programming in Python (Part 2) (Coursera) Coursera
Rice University

An Introduction to Interactive Programming in Python (Part 2) (Coursera)

This two-part course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera. To make learning Python easy, we have developed a new browser-based programming environment that makes developing interactive applications in Python simple.

Sep 7th 2026
4 Weeks
Audio Signal Processing for Music Applications (Coursera) Coursera
Stanford University,Universitat Pompeu Fabra

Audio Signal Processing for Music Applications (Coursera)

In this course you will learn about audio signal processing methodologies that are specific for music and of use in real applications. We focus on the spectral processing techniques of relevance for the description and transformation of sounds, developing the basic theoretical and practical knowledge with which to analyze, synthesize, transform and describe audio signals in the context of music applications.

Sep 14th 2026
5-12 Weeks
Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python (Coursera) Coursera
Ludwig-Maximilians-Universität München

Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python (Coursera)

Interested in learning how to solve partial differential equations with numerical methods and how to turn them into python codes? This course provides you with a basic introduction how to apply methods like the finite-difference method, the pseudospectral method, the linear and spectral element method to the 1D (or 2D) scalar wave equation.

Sep 7th 2026
5-12 Weeks
An Introduction to Interactive Programming in Python (Part 1) (Coursera) Coursera
Rice University

An Introduction to Interactive Programming in Python (Part 1) (Coursera)

This two-part course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera. To make learning Python easy, we have developed a new browser-based programming environment that makes developing interactive applications in Python simple.

Sep 7th 2026
5-12 Weeks
Data Processing Using Python (Coursera) Coursera
Nanjing University

Data Processing Using Python (Coursera)

This course is mainly for non-computer majors. It starts with the basic syntax of Python, to how to acquire data in Python locally and from network, to how to present data, then to how to conduct basic and advanced statistic analysis and visualization of data, and finally to how to design a simple GUI to present and process data, advancing level by level.

Sep 14th 2026
5-12 Weeks
Python Data Visualization (Coursera) Coursera
Rice University

Python Data Visualization (Coursera)

This if the final course in the specialization which builds upon the knowledge learned in Python Programming Essentials, Python Data Representations, and Python Data Analysis. We will learn how to install external packages for use within Python, acquire data from sources on the Web, and then we will clean, process, analyze, and visualize that data. This course will combine the skills learned throughout the specialization to enable you to write interesting, practical, and useful programs.

Sep 4th 2026
4 Weeks