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    Computational Science Courses Online

    Understand computational science for solving complex scientific problems. Learn to use computational tools and simulations in various scientific disciplines.

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    Explore the Computational Science Course Catalog

    • S

      Stanford University

      Understanding Einstein: The Special Theory of Relativity

      Skills you'll gain: Physics, Timelines, Verification And Validation, Scientific Methods, Research, Mechanics, Mathematical Modeling, Systems Of Measurement

      4.9
      Rating, 4.9 out of 5 stars
      ·
      3.1K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Davis

      Computational Social Science Methods

      Skills you'll gain: Social Sciences, Network Analysis, Data Science, Machine Learning, Computational Thinking, Economics, Policy, and Social Studies, Artificial Intelligence, Data Analysis, Simulations, Big Data, Scientific Methods

      4.7
      Rating, 4.7 out of 5 stars
      ·
      342 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google

      Foundations of Business Intelligence

      Skills you'll gain: Stakeholder Engagement, Business Intelligence, Data Integration, Dashboard, Business Analytics, Real Time Data, Data Modeling, Data-Driven Decision-Making, Data Analysis, Requirements Elicitation, Business Metrics, Key Performance Indicators (KPIs), Data Pipelines, Project Documentation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.8K reviews

      Advanced · Course · 1 - 4 Weeks

    • D

      Duke University

      Introduction to Genetics and Evolution

      Skills you'll gain: Life Sciences, Molecular Biology, Biology, Biostatistics, Bioinformatics, Environment, Laboratory Research, Taxonomy, Scientific Methods, Experimentation, Mathematical Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.8K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Introduction to Probability and Data with R

      Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Software, Descriptive Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.8K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Power Electronics

      Skills you'll gain: Power Electronics, Control Systems, Semiconductors, Electronic Systems, Electrical Engineering, Electronic Components, Basic Electrical Systems, Electric Power Systems, Electrical Power, Systems Analysis, Electronics, Simulations, Engineering Analysis, Mathematical Modeling, Systems Design, Plot (Graphics), Technical Design, Engineering Design Process, Engineering Calculations, Matlab

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4.2K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Advanced Algorithms and Complexity

      Skills you'll gain: Algorithms, Network Routing, Network Model, Graph Theory, Operations Research, Theoretical Computer Science, Network Analysis, Data Structures, Computational Thinking, Linear Algebra, Computer Science, Big Data, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      694 reviews

      Advanced · Course · 1 - 3 Months

    • U

      University of Alberta

      Dino 101: Dinosaur Paleobiology

      Skills you'll gain: Biology, Physical Science, Life Sciences, Taxonomy, Environment, Scientific Methods, Research, Timelines

      4.9
      Rating, 4.9 out of 5 stars
      ·
      3.7K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Santa Cruz

      Go and C++: Programming in Two Successor Languages of C

      Skills you'll gain: C++ (Programming Language), Go (Programming Language), Data Structures, Object Oriented Programming (OOP), Software Design Patterns, Debugging, Object Oriented Design, Programming Principles, Unit Testing, Algorithms, C (Programming Language), Program Development, Integrated Development Environments, Computer Programming, Software Testing, Computer Science, Graph Theory, File Management, Artificial Intelligence, Integration Testing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      2.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    • D

      Duke University

      Introduction to Machine Learning

      Skills you'll gain: PyTorch (Machine Learning Library), Reinforcement Learning, Image Analysis, Applied Machine Learning, Deep Learning, Machine Learning, Natural Language Processing, Supervised Learning, Unsupervised Learning, Artificial Neural Networks, Computer Vision, Medical Imaging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.7K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado System

      C# Programming for Unity Game Development

      Skills you'll gain: Unity Engine, Debugging, Object Oriented Programming (OOP), Video Game Development, C# (Programming Language), Game Design, Software Design Patterns, Computer Programming, Event-Driven Programming, Data Structures, Integrated Development Environments, Data Storage, Application Development, Software Design, Program Development, UI Components, Cross Platform Development, Scripting, Data Import/Export, Development Environment

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.7K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Natural Language Processing in TensorFlow

      Skills you'll gain: Tensorflow, Natural Language Processing, Generative AI, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Text Mining, Data Processing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.5K reviews

      Intermediate · Course · 1 - 4 Weeks

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    In summary, here are 10 of our most popular computational science courses

    • Understanding Einstein: The Special Theory of Relativity: Stanford University
    • Computational Social Science Methods: University of California, Davis
    • Foundations of Business Intelligence: Google
    • Introduction to Genetics and Evolution: Duke University
    • Introduction to Probability and Data with R: Duke University
    • Power Electronics: University of Colorado Boulder
    • Advanced Algorithms and Complexity: University of California San Diego
    • Dino 101: Dinosaur Paleobiology: University of Alberta
    • Go and C++: Programming in Two Successor Languages of C: University of California, Santa Cruz
    • Introduction to Machine Learning: Duke University

    Frequently Asked Questions about Computational Science

    Computational science is an interdisciplinary field that utilizes computer modeling, simulation, and data analysis to solve complex problems across various scientific disciplines. It involves the application of computational techniques, algorithms, and mathematical models to study natural phenomena, analyze large datasets, and simulate complex systems. Computational science plays a crucial role in advancing scientific research, improving predictions, and facilitating scientific discovery across disciplines such as physics, chemistry, biology, engineering, and more.‎

    To excel in computational science, you need to develop the following skills:

    • Programming: Proficiency in programming languages such as Python, C++, or MATLAB to implement algorithms, perform data analysis, and develop computational models.
    • Mathematical Modeling: Understanding of mathematical concepts and techniques used in computational science, such as calculus, linear algebra, differential equations, and numerical methods.
    • Scientific Computing: Knowledge of computational techniques, including numerical integration, optimization, finite element methods, and numerical simulation.
    • Data Analysis: Skills in analyzing and interpreting complex datasets using statistical methods, data visualization, and machine learning techniques.
    • High-Performance Computing: Familiarity with parallel computing, distributed computing, and utilizing computational resources efficiently for large-scale simulations.
    • Computational Modeling: Ability to develop and implement computational models to simulate and study complex systems, phenomena, or processes.
    • Problem-Solving: Aptitude for formulating scientific problems in computational terms, designing algorithms, and solving them using computational tools.
    • Data Management: Proficiency in handling and processing large datasets, data storage, and data organization for efficient analysis and retrieval.
    • Scientific Visualization: Ability to effectively present and visualize scientific data, simulation results, and complex models for analysis and communication.
    • Collaboration and Interdisciplinary Skills: Capacity to work in multidisciplinary teams, communicate with domain experts, and integrate computational methods into scientific research.‎

    With computational science skills, you can pursue various job opportunities, including:

    • Computational Scientist
    • Research Scientist
    • Data Scientist
    • Simulation Engineer
    • Software Developer (specializing in scientific applications)
    • Computational Physicist
    • Computational Chemist
    • Bioinformatics Specialist
    • Computational Biologist
    • Research Analyst

    These roles involve utilizing computational techniques, developing and implementing models and simulations, analyzing scientific data, and contributing to scientific research in academia, government labs, research institutions, or industries.‎

    Computational science is well-suited for individuals who possess the following qualities:

    • Analytical and Mathematical Aptitude: Ability to analyze complex scientific problems, apply mathematical techniques, and derive meaningful insights using computational methods.
    • Programming Proficiency: Experience or willingness to learn programming languages and tools used in scientific computing, simulation, and data analysis.
    • Curiosity and Critical Thinking: A passion for scientific exploration, asking research questions, and devising innovative approaches to solving complex problems.
    • Interdisciplinary Interest: Eagerness to work across scientific disciplines, collaborate with domain experts, and apply computational methods to various scientific domains.
    • Problem-Solving Orientation: Aptitude for formulating and solving scientific problems, designing algorithms, and interpreting computational results in a scientific context.
    • Detail-Oriented: Meticulousness in handling and analyzing scientific data, ensuring accuracy in computational models, and interpreting simulation results.
    • Communication Skills: Ability to effectively communicate scientific concepts, present research findings, and collaborate with researchers from diverse backgrounds.
    • Continuous Learners: Willingness to stay updated with the latest research in computational science, emerging computational methodologies, and scientific domains.‎

    Several topics are related to computational science that you can study to enhance your skills and knowledge, including:

    • Numerical Methods and Algorithms
    • Mathematical Modeling and Simulation
    • Parallel and Distributed Computing
    • Scientific Data Analysis and Visualization
    • High-Performance Computing
    • Computational Physics
    • Computational Chemistry
    • Computational Biology
    • Computational Engineering
    • Machine Learning for Scientific Applications

    Exploring these topics through online courses, academic programs, research papers, and practical projects will provide a comprehensive understanding of the concepts and techniques used in computational science, enabling you to apply them effectively in scientific research and problem-solving.‎

    Online Computational Science courses offer a convenient and flexible way to enhance your knowledge or learn new Computational Science skills. Choose from a wide range of Computational Science courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Computational Science, 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.

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