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Numerical Analysis Courses

Numerical analysis courses can help you learn techniques for solving equations, numerical integration, interpolation, and error analysis. You can build skills in optimizing algorithms, implementing numerical methods, and analyzing computational efficiency. Many courses introduce tools like MATLAB, Python, and R, that support applying these methods to real-world problems in engineering, physics, and data science.


Popular Numerical Analysis Courses and Certifications


  • 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
    ·
    411 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
    ·
    109 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, electromagnetics, Algebra, Applied Mathematics, Mathematical Modeling, Engineering, Simulation and Simulation Software, Advanced Mathematics, Geometry, Computational Thinking

    4.8
    Rating, 4.8 out of 5 stars
    ·
    7.7K reviews

    Beginner · Specialization · 3 - 6 Months

  • 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, Engineering Calculations, Differential Equations, Applied Mathematics, Mathematical Modeling, Distributed Computing, Python Programming, Mechanics, Vibrations, Simulations

    4.8
    Rating, 4.8 out of 5 stars
    ·
    389 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, Differential Equations, Engineering Analysis, Mathematical Software, Numerical Analysis, Mathematical Modeling, Advanced Mathematics, Applied Mathematics, Linear Algebra, C++ (Programming Language), Calculus, Algorithms

    4.6
    Rating, 4.6 out of 5 stars
    ·
    562 reviews

    Intermediate · Course · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    T

    The Hong Kong University of Science and Technology

    Differential Equations for Engineers

    Skills you'll gain: Differential Equations, Engineering Analysis, Applied Mathematics, Calculus, Integral Calculus, Numerical Analysis, Mathematical Modeling, Advanced Mathematics, Linear Algebra, Vibrations, Electrical Engineering, Derivatives

    4.9
    Rating, 4.9 out of 5 stars
    ·
    2.2K reviews

    Beginner · Course · 1 - 3 Months

What brings you to Coursera today?

  • Status: New
    New
    Status: Preview
    Preview
    J

    JetBrains

    Python from Scratch: Learn by Coding

    Skills you'll gain: Integrated Development Environments, File I/O, Software Development Tools, Python Programming, Development Environment, Data Structures, Computer Programming, Programming Principles, Scripting, Maintainability, Code Review, Data Processing, NumPy, Computational Thinking, Software Installation, Numerical Analysis

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Optical Engineering

    Skills you'll gain: Electrical Engineering, electromagnetics, Performance Tuning, Image Quality, Engineering, Scientific, and Technical Instruments, Simulation and Simulation Software, Engineering Calculations, Design Software, Image Analysis, Engineering Analysis, Computer-Aided Design, Engineering Design Process, Numerical Analysis, Applied Mathematics, Electronic Components, System Design and Implementation, Systems Design, Human Factors, Physics, System Configuration

    Build toward a degree

    4.3
    Rating, 4.3 out of 5 stars
    ·
    375 reviews

    Advanced · 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, Machine Learning Algorithms, Data Preprocessing, Machine Learning, Machine Learning Methods

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.1K reviews

    Intermediate · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Linear Algebra from Elementary to Advanced

    Skills you'll gain: Linear Algebra, Algebra, Applied Mathematics, Advanced Mathematics, Artificial Intelligence and Machine Learning (AI/ML), Mathematical Modeling, Engineering Analysis, Mathematical Theory & Analysis, Numerical Analysis, Geometry, Data Transformation, Applied Machine Learning, Dimensionality Reduction, Markov Model, Probability

    4.7
    Rating, 4.7 out of 5 stars
    ·
    220 reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    L

    L&T EduTech

    Industrial Power Systems Analysis and Stability

    Skills you'll gain: Electrical Systems, Electric Power Systems, Electrical Power, Control Systems, Electrical Equipment, Three-Phase, High Voltage, Wiring Diagram, Systems Analysis, Simulation and Simulation Software, Electrical Engineering, Network Analysis, Engineering Analysis, Numerical Analysis, Low Voltage, Mathematical Modeling, Simulations, Power Electronics, Graph Theory, Differential Equations

    4.5
    Rating, 4.5 out of 5 stars
    ·
    44 reviews

    Intermediate · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Differential Calculus through Data and Modeling

    Skills you'll gain: Calculus, Applied Mathematics, Data Modeling, Estimation, Graphing, Mathematical Modeling, Numerical Analysis, Algebra, Mathematical Software, Engineering Calculations, Linear Algebra, Trigonometry, Operations Research, Data Analysis, Graphical Tools, Advanced Mathematics, Derivatives, Mathematical Theory & Analysis, Geometry

    4.8
    Rating, 4.8 out of 5 stars
    ·
    387 reviews

    Intermediate · Specialization · 3 - 6 Months

Searches related to numerical analysis

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

  • 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
  • Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python: Ludwig-Maximilians-Universität München (LMU)
  • The Finite Element Method for Problems in Physics: University of Michigan
  • Differential Equations for Engineers: The Hong Kong University of Science and Technology
  • Python from Scratch: Learn by Coding: JetBrains
  • Optical Engineering: University of Colorado Boulder
  • Mathematics for Machine Learning and Data Science: DeepLearning.AI
  • Linear Algebra from Elementary to Advanced: Johns Hopkins University

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 to obtain numerical solutions to mathematical problems. It plays a crucial role in various fields, including engineering, physics, finance, and computer science, where analytical solutions may be difficult or impossible to obtain. By providing methods to approximate solutions, numerical analysis enables professionals to model complex systems, analyze data, and make informed decisions based on quantitative insights.‎

A background in numerical analysis can open doors to various career opportunities. Common job roles include data analyst, quantitative analyst, software engineer, and research scientist. Professionals in these positions often utilize numerical methods to solve real-world problems, optimize processes, and analyze large datasets. Additionally, industries such as finance, technology, and academia highly value expertise in numerical analysis, making it a valuable skill set for job seekers.‎

To excel in numerical analysis, you should develop a strong foundation in mathematics, particularly calculus, linear algebra, and differential equations. Familiarity with programming languages such as Python, R, or MATLAB is also essential, as these tools are commonly used to implement numerical methods. Additionally, understanding statistical concepts and data visualization techniques can enhance your ability to analyze and interpret results effectively.‎

There are several online courses available that can help you learn numerical analysis. For instance, the Integral Calculus and Numerical Analysis for Data Science course provides a solid introduction to the subject, integrating practical applications in data science. Exploring various platforms can help you find the best fit for your learning style and goals.‎

Yes. You can start learning numerical analysis on Coursera for free in two ways:

  1. Preview the first module of many numerical analysis courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in numerical analysis, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn numerical analysis effectively, start by identifying your current skill level and setting clear learning goals. Begin with foundational mathematics courses, then progress to specialized numerical analysis courses. Engage in hands-on practice by working on real-world problems and projects. Joining online forums or study groups can also provide support and enhance your understanding through collaboration.‎

Typical topics covered in numerical analysis courses include error analysis, numerical solutions of equations, interpolation, numerical integration, and numerical differentiation. Advanced courses may also explore topics like optimization, numerical linear algebra, and the application of numerical methods in data science and engineering. This comprehensive curriculum equips learners with the skills needed to tackle complex mathematical problems.‎

For training and upskilling employees in numerical analysis, courses that focus on practical applications and industry relevance are ideal. Programs like the Data Analysis and Interpretation Specialization provide a comprehensive overview of data analysis techniques, while the Business Statistics and Analysis Specialization emphasizes statistical methods in business contexts. These courses can enhance workforce capabilities and drive data-informed decision-making.‎

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.

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