• For Individuals
  • For Businesses
  • For Universities
  • For Governments
Coursera
Log In
Join for Free
Coursera
  • Browse
  • Numerical Analysis

Numerical Analysis Courses Online

Master numerical analysis for solving mathematical problems computationally. Learn about algorithms for approximation, integration, and differential equations.

Skip to search results

Filter by

Subject
Required
 *

Language
Required
 *

The language used throughout the course, in both instruction and assessments.

Learning Product
Required
 *

Build job-relevant skills in under 2 hours with hands-on tutorials.
Learn from top instructors with graded assignments, videos, and discussion forums.
Learn a new tool or skill in an interactive, hands-on environment.
Get in-depth knowledge of a subject by completing a series of courses and projects.
Earn career credentials from industry leaders that demonstrate your expertise.
Earn career credentials while taking courses that count towards your Master’s degree.
Earn your Bachelor’s or Master’s degree online for a fraction of the cost of in-person learning.
Complete graduate-level learning without committing to a full degree program.
Earn a university-issued career credential in a flexible, interactive format.
Graduate level learning within reach.

Level
Required
 *

Duration
Required
 *

Skills
Required
 *

Subtitles
Required
 *

Educator
Required
 *

Explore the Numerical Analysis Course Catalog

  • Status: New
    New
    Status: Free Trial
    Free Trial
    U

    University of Pittsburgh

    Mathematical Foundations for Data Science and Analytics

    Skills you'll gain: Statistical Analysis, NumPy, Probability Distribution, Matplotlib, Statistics, Pandas (Python Package), Data Science, Probability & Statistics, Probability, Statistical Modeling, Predictive Modeling, Data Analysis, Linear Algebra, Predictive Analytics, Statistical Methods, Mathematics and Mathematical Modeling, Applied Mathematics, Python Programming, Machine Learning, Logical Reasoning

    Build toward a degree

    Beginner · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    T

    The Hong Kong University of Science and Technology

    Numerical Methods for Engineers

    Skills you'll gain: Matlab, Engineering Calculations, Numerical Analysis, Mathematical Software, Engineering Analysis, Linear Algebra, Differential Equations, Applied Mathematics, Mathematical Modeling, Simulation and Simulation Software, Computational Thinking, Estimation, Integral Calculus, Scripting, Simulations, Calculus, Scientific Visualization, Programming Principles, Plot (Graphics), Algorithms

    4.9
    Rating, 4.9 out of 5 stars
    ·
    398 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Integral Calculus and Numerical Analysis for Data Science

    Skills you'll gain: Integral Calculus, Numerical Analysis, Calculus, Data Science, Mathematical Theory & Analysis, Applied Mathematics, Linear Algebra, Derivatives

    4.6
    Rating, 4.6 out of 5 stars
    ·
    102 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    T

    The Hong Kong University of Science and Technology

    Mathematics for Engineers

    Skills you'll gain: Differential Equations, Linear Algebra, Matlab, Engineering Calculations, Engineering Analysis, Numerical Analysis, Finite Element Methods, Integral Calculus, Mathematical Software, Mechanical Engineering, Calculus, Algebra, Applied Mathematics, Mathematical Modeling, Engineering, Simulation and Simulation Software, Advanced Mathematics, Geometry, Computational Thinking, Estimation

    4.8
    Rating, 4.8 out of 5 stars
    ·
    7.6K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Data Analysis with Python

    Skills you'll gain: Exploratory Data Analysis, Data Wrangling, Data Transformation, Data Analysis, Data Cleansing, Data Manipulation, Data Import/Export, Predictive Modeling, Regression Analysis, Statistical Analysis, Pandas (Python Package), Scikit Learn (Machine Learning Library), Data-Driven Decision-Making, Matplotlib, Feature Engineering, Data Visualization, Data Pipelines, NumPy, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    19K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    U

    University of Michigan

    The Finite Element Method for Problems in Physics

    Skills you'll gain: Finite Element Methods, Engineering Analysis, Numerical Analysis, Mathematical Modeling, Advanced Mathematics, C++ (Programming Language), Object Oriented Programming (OOP)

    4.6
    Rating, 4.6 out of 5 stars
    ·
    558 reviews

    Intermediate · Course · 3 - 6 Months

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Linear Algebra for Machine Learning and Data Science

    Skills you'll gain: Linear Algebra, NumPy, Dimensionality Reduction, Machine Learning Methods, Data Transformation, Data Manipulation, Data Science, Applied Mathematics, Mathematical Modeling, Machine Learning, Python Programming

    4.6
    Rating, 4.6 out of 5 stars
    ·
    2.2K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    L

    Ludwig-Maximilians-Universität München (LMU)

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

    Skills you'll gain: Finite Element Methods, Numerical Analysis, Engineering Analysis, Jupyter, Differential Equations, Applied Mathematics, Mathematical Modeling, Python Programming, Mechanics, Vibrations, Linear Algebra, Simulations

    4.8
    Rating, 4.8 out of 5 stars
    ·
    388 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    B

    Birla Institute of Technology & Science, Pilani

    Mathematics for Engineering

    Skills you'll gain: Engineering Calculations, Data Analysis, Trigonometry, Engineering Analysis, Probability & Statistics, Computational Logic, Statistical Analysis, Linear Algebra, Logical Reasoning, Deductive Reasoning, Calculus, Analytics, Bayesian Statistics, Statistical Modeling, Artificial Intelligence and Machine Learning (AI/ML), Differential Equations, Statistical Inference, Theoretical Computer Science, Programming Principles, Descriptive Analytics

    4.6
    Rating, 4.6 out of 5 stars
    ·
    161 reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Mathematics for Machine Learning and Data Science

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Mathematical Modeling, Machine Learning, Machine Learning Methods, Data Transformation

    4.6
    Rating, 4.6 out of 5 stars
    ·
    2.9K reviews

    Intermediate · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Pennsylvania

    Finance & Quantitative Modeling for Analysts

    Skills you'll gain: Return On Investment, Financial Reporting, Financial Acumen, Financial Data, Capital Budgeting, Financial Statements, Financial Modeling, Mathematical Modeling, Statistical Modeling, Regression Analysis, Business Modeling, Income Statement, Risk Analysis, Cash Flows, Financial Analysis, Business Mathematics, Corporate Finance, Spreadsheet Software, Google Sheets, Microsoft Excel

    4.5
    Rating, 4.5 out of 5 stars
    ·
    17K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Expressway to Data Science: Essential Math

    Skills you'll gain: Linear Algebra, Integral Calculus, Algebra, Numerical Analysis, Calculus, Graphing, Applied Mathematics, Data Science, Mathematical Theory & Analysis, Data Analysis, Statistical Methods, Derivatives

    4.5
    Rating, 4.5 out of 5 stars
    ·
    457 reviews

    Intermediate · Specialization · 3 - 6 Months

Numerical Analysis learners also search

Statistical Analysis
Predictive Modeling
Statistical Modeling
Predictive Analytics
Data Modeling
Beginner Predictive Analytics
Predictive Analytics Projects
Regression Analysis
1234…606

In summary, here are 10 of our most popular numerical analysis courses

  • Mathematical Foundations for Data Science and Analytics: University of Pittsburgh
  • Numerical Methods for Engineers: The Hong Kong University of Science and Technology
  • Integral Calculus and Numerical Analysis for Data Science: University of Colorado Boulder
  • Mathematics for Engineers: The Hong Kong University of Science and Technology
  • Data Analysis with Python: IBM
  • The Finite Element Method for Problems in Physics: University of Michigan
  • Linear Algebra for Machine Learning and Data Science: DeepLearning.AI
  • Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python: Ludwig-Maximilians-Universität München (LMU)
  • Mathematics for Engineering: Birla Institute of Technology & Science, Pilani
  • Mathematics for Machine Learning and Data Science: DeepLearning.AI

Skills you can learn in Algorithms

Graphs (22)
Mathematical Optimization (21)
Computer Program (20)
Data Structure (19)
Problem Solving (19)
Algebra (12)
Computer Vision (10)
Discrete Mathematics (10)
Graph Theory (10)
Image Processing (10)
Linear Algebra (10)
Reinforcement Learning (10)

Frequently Asked Questions about Numerical Analysis

Numerical analysis is a branch of mathematics that focuses on developing algorithms and methods to solve mathematical problems using numerical approximations. It involves studying the accuracy, stability, and efficiency of numerical techniques for solving problems that may be too complex or time-consuming to solve analytically. Numerical analysis plays a crucial role in various fields such as engineering, physics, computer science, and finance, where accurate and efficient numerical solutions are essential.‎

To become proficient in Numerical Analysis, you need to learn the following skills:

  1. Mathematics: A strong foundation in mathematical concepts such as calculus, linear algebra, and differential equations is crucial for understanding the underlying principles of numerical analysis.

  2. Programming: Proficiency in programming languages like Python, MATLAB, or R is essential for implementing numerical algorithms and solving complex problems. You should also be comfortable with data structures, loops, conditionals, and functions.

  3. Statistics: Understanding statistical concepts will help you analyze and interpret numerical data accurately. Concepts like probability theory, hypothesis testing, and regression analysis will be useful for various numerical analysis techniques.

  4. Numerical Methods: Familiarity with various numerical algorithms, such as root-finding methods, interpolation, numerical integration, and solving linear systems, is essential. You should also know how to apply these methods effectively to solve real-world problems.

  5. Optimization: Knowledge of optimization techniques, including linear and nonlinear programming, gradient descent, and constrained optimization, will enable you to optimize functions and find optimal solutions in numerical analysis scenarios.

  6. Data Visualization: Being able to visually represent numerical data through graphs, charts, and plots is essential for gaining insights and effectively communicating results. Familiarize yourself with data visualization tools and techniques, such as matplotlib or ggplot.

  7. Problem-Solving and Critical Thinking: Numerical analysis often involves encountering complex problems that require analytical thinking and problem-solving skills. Develop your ability to think critically, break down problems into smaller components, and approach them methodically.

Remember that learning Numerical Analysis is a continuous process, and keeping up with the latest advancements in the field is important. Utilize online courses, books, interactive tutorials, and practice problems to enhance your skills and stay up-to-date with the evolving techniques in this domain.‎

With Numerical Analysis skills, you can pursue a variety of job opportunities in both academic and professional fields. Some of the possible career paths include:

  1. Data Analyst: Employers across various industries require professionals who can analyze and interpret complex numerical data to drive informed business decisions.

  2. Quantitative Analyst: Banks, investment firms, and hedge funds often hire individuals proficient in Numerical Analysis to develop quantitative models and strategies for financial forecasting and risk management.

  3. Statistician: Statisticians utilize Numerical Analysis techniques to design experiments, collect and analyze data, and make predictions and recommendations in areas such as healthcare, marketing, social sciences, and more.

  4. Actuary: Actuaries use mathematical models, including Numerical Analysis, to evaluate and manage financial risks for insurance companies, ensuring they set accurate premiums and reserves.

  5. Research Scientist: Government agencies, research institutions, and private companies employ research scientists with Numerical Analysis skills to conduct mathematical and statistical research for various fields, like physics, biology, engineering, and more.

  6. Software Developer: Numerical Analysis expertise is beneficial for software developers working on projects involving simulations, algorithms, or mathematical modeling.

  7. Academic Researcher/Professor: Academic institutions often have research and teaching positions where Numerical Analysis knowledge is highly sought after, particularly in mathematics, engineering, physics, and computer science departments.

Remember, this is not an exhaustive list, and there are many more options available based on your specific interests and industry preferences.‎

Numerical Analysis is best suited for individuals who have a strong foundation in mathematics and a keen interest in problem-solving. This field requires a deep understanding of calculus, linear algebra, and numerical methods. People who enjoy working with numbers, analyzing data, and developing algorithms will find studying Numerical Analysis highly rewarding. Additionally, individuals pursuing careers in fields such as engineering, computer science, finance, or data analysis can greatly benefit from studying Numerical Analysis as it provides essential tools for solving complex mathematical problems encountered in these domains.‎

Here are some topics that are related to Numerical Analysis that you can study:

  1. Interpolation and approximation techniques
  2. Numerical integration and differentiation
  3. Solution methods for linear and nonlinear equations
  4. Matrix computation and linear algebra techniques
  5. Algorithms for solving optimization problems
  6. Numerical methods for solving differential equations
  7. Numerical methods for solving partial differential equations
  8. Monte Carlo methods and simulations
  9. Finite element analysis
  10. Computational methods for solving eigenvalue problems

These topics cover a wide range of numerical analysis techniques and concepts. You can explore them further by taking online courses, watching video tutorials, or reading textbooks on the subject.‎

Online Numerical Analysis courses offer a convenient and flexible way to enhance your knowledge or learn new Numerical analysis is a branch of mathematics that focuses on developing algorithms and methods to solve mathematical problems using numerical approximations. It involves studying the accuracy, stability, and efficiency of numerical techniques for solving problems that may be too complex or time-consuming to solve analytically. Numerical analysis plays a crucial role in various fields such as engineering, physics, computer science, and finance, where accurate and efficient numerical solutions are essential. skills. Choose from a wide range of Numerical Analysis courses offered by top universities and industry leaders tailored to various skill levels.‎

When looking to enhance your workforce's skills in Numerical Analysis, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

Other topics to explore

Arts and Humanities
338 courses
Business
1095 courses
Computer Science
668 courses
Data Science
425 courses
Information Technology
145 courses
Health
471 courses
Math and Logic
70 courses
Personal Development
137 courses
Physical Science and Engineering
413 courses
Social Sciences
401 courses
Language Learning
150 courses

Coursera Footer

Skills

  • Artificial Intelligence (AI)
  • Cybersecurity
  • Data Analytics
  • Digital Marketing
  • English Speaking
  • Generative AI (GenAI)
  • Microsoft Excel
  • Microsoft Power BI
  • Project Management
  • Python

Certificates & Programs

  • Google Cybersecurity Certificate
  • Google Data Analytics Certificate
  • Google IT Support Certificate
  • Google Project Management Certificate
  • Google UX Design Certificate
  • IBM Data Analyst Certificate
  • IBM Data Science Certificate
  • Machine Learning Certificate
  • Microsoft Power BI Data Analyst Certificate
  • UI / UX Design Certificate

Industries & Careers

  • Business
  • Computer Science
  • Data Science
  • Education & Teaching
  • Engineering
  • Finance
  • Healthcare
  • Human Resources (HR)
  • Information Technology (IT)
  • Marketing

Career Resources

  • Career Aptitude Test
  • Examples of Strengths and Weaknesses for Job Interviews
  • High-Income Skills to Learn
  • How Does Cryptocurrency Work?
  • How to Highlight Duplicates in Google Sheets
  • How to Learn Artificial Intelligence
  • Popular Cybersecurity Certifications
  • Preparing for the PMP Certification
  • Signs You Will Get the Job After an Interview
  • What Is Artificial Intelligence?

Coursera

  • About
  • What We Offer
  • Leadership
  • Careers
  • Catalog
  • Coursera Plus
  • Professional Certificates
  • MasterTrack® Certificates
  • Degrees
  • For Enterprise
  • For Government
  • For Campus
  • Become a Partner
  • Social Impact
  • Free Courses
  • Share your Coursera learning story

Community

  • Learners
  • Partners
  • Beta Testers
  • Blog
  • The Coursera Podcast
  • Tech Blog

More

  • Press
  • Investors
  • Terms
  • Privacy
  • Help
  • Accessibility
  • Contact
  • Articles
  • Directory
  • Affiliates
  • Modern Slavery Statement
  • Manage Cookie Preferences
Learn Anywhere
Download on the App Store
Get it on Google Play
Logo of Certified B Corporation
© 2025 Coursera Inc. All rights reserved.
  • Coursera Facebook
  • Coursera Linkedin
  • Coursera Twitter
  • Coursera YouTube
  • Coursera Instagram
  • Coursera TikTok