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    • Computational Science

    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

      Divide and Conquer, Sorting and Searching, and Randomized Algorithms

      Skills you'll gain: Algorithms, Graph Theory, Data Structures, Theoretical Computer Science, Computational Thinking, Mathematical Theory & Analysis, Analysis, Probability, Design Strategies

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.3K reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      Python for Data Science, AI & Development

      Skills you'll gain: Jupyter, Automation, Web Scraping, Python Programming, Data Manipulation, Data Import/Export, Scripting, Data Structures, Data Processing, Data Collection, Application Programming Interface (API), Pandas (Python Package), Programming Principles, NumPy, Object Oriented Programming (OOP), Computer Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      40K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      U

      University of California San Diego

      Biology Meets Programming: Bioinformatics for Beginners

      Skills you'll gain: Bioinformatics, Programming Principles, Computational Thinking, Analysis

      4.2
      Rating, 4.2 out of 5 stars
      ·
      1.6K reviews

      Beginner · Course · 1 - 4 Weeks

    • V

      Vanderbilt University

      MATLAB Programming for Engineers and Scientists

      Skills you'll gain: Data Visualization, Image Analysis, Data Visualization Software, Matlab, Machine Learning Methods, Algorithms, User Interface (UI), Applied Machine Learning, Object Oriented Programming (OOP), Statistical Methods, Data Analysis, Computer Programming, Programming Principles, Data Processing, Application Development, Data Structures, Scripting, Debugging, Mathematical Software, Data Manipulation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      18K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Introduction to Data Science

      Skills you'll gain: SQL, Jupyter, Data Mining, Peer Review, Data Modeling, Databases, Stored Procedure, Relational Databases, R Programming, Database Design, Query Languages, Data Science, Database Management, Big Data, Data Cleansing, Computer Programming Tools, GitHub, Data Visualization Software, Cloud Computing, Data Analysis

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      97K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      D

      Deep Teaching Solutions

      Learning How to Learn: Powerful mental tools to help you master tough subjects

      Skills you'll gain: Learning Strategies, Time Management, Willingness To Learn, Mental Concentration, Creativity, Persistence, Stress Management, Self-Awareness, Adaptability

      4.8
      Rating, 4.8 out of 5 stars
      ·
      92K reviews

      Beginner · Course · 1 - 4 Weeks

    • Placeholder
      Status: [object Object]
      New AI skills
      G

      Google

      Google Data Analytics

      Skills you'll gain: Data Storytelling, Rmarkdown, Data Visualization, Data Presentation, Data Ethics, Interactive Data Visualization, Interviewing Skills, Data Cleansing, Data Validation, Ggplot2, Tableau Software, Presentations, Spreadsheet Software, Data Analysis, Data Visualization Software, Stakeholder Communications, Dashboard, Sampling (Statistics), Analytics, Stakeholder Management

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      164K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Placeholder
      U

      University of Colorado Boulder

      Foundations of Data Structures and Algorithms

      Skills you'll gain: Theoretical Computer Science, Algorithms, Data Structures, Graph Theory, Operations Research, Public Key Cryptography Standards (PKCS), Computational Logic, Cryptography, Computational Thinking, Pseudocode, Design Strategies, Combinatorics, Programming Principles, Computer Programming, Computer Science, Encryption, Network Model, Linear Algebra, Analysis, Mathematical Modeling

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      702 reviews

      Advanced · Specialization · 3 - 6 Months

    • Placeholder
      J

      Johns Hopkins University

      Data Science: Foundations using R

      Skills you'll gain: Rmarkdown, Exploratory Data Analysis, Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Data Visualization, Statistical Programming, Ggplot2, Dimensionality Reduction, Data Visualization Software, Data Integration, Knitr, Data Analysis, Data Import/Export, General Science and Research, Data Sharing, Statistical Reporting

      4.6
      Rating, 4.6 out of 5 stars
      ·
      48K reviews

      Beginner · Specialization · 3 - 6 Months

    • Placeholder
      J

      Johns Hopkins University

      Data Science

      Skills you'll gain: Shiny (R Package), Rmarkdown, Exploratory Data Analysis, Regression Analysis, Leaflet (Software), Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Data Visualization, Plotly, Machine Learning Algorithms, Interactive Data Visualization, Probability & Statistics, Knitr

      4.5
      Rating, 4.5 out of 5 stars
      ·
      51K reviews

      Beginner · Specialization · 3 - 6 Months

    • Placeholder
      Status: Free
      Free
      U

      University of Geneva

      Simulation and modeling of natural processes

      Skills you'll gain: Simulations, Python Programming, Statistical Methods, Numerical Analysis, Mathematical Modeling, Probability Distribution, Visualization (Computer Graphics), Mechanics, Artificial Intelligence

      4.3
      Rating, 4.3 out of 5 stars
      ·
      394 reviews

      Mixed · Course · 1 - 3 Months

    • Placeholder
      Status: Free
      Free
      U

      University of Alberta

      Problem Solving, Python Programming, and Video Games

      Skills you'll gain: Computational Thinking, Programming Principles, Computer Programming, Program Development, Software Quality Assurance, Python Programming, Algorithms, Software Design, Visualization (Computer Graphics), Debugging, Problem Management, Computer Science, Test Planning

      4.3
      Rating, 4.3 out of 5 stars
      ·
      230 reviews

      Beginner · Course · 1 - 3 Months

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

    • Divide and Conquer, Sorting and Searching, and Randomized Algorithms: Stanford University
    • Python for Data Science, AI & Development: IBM
    • Biology Meets Programming: Bioinformatics for Beginners: University of California San Diego
    • MATLAB Programming for Engineers and Scientists: Vanderbilt University
    • Introduction to Data Science: IBM
    • Learning How to Learn: Powerful mental tools to help you master tough subjects: Deep Teaching Solutions
    • Google Data Analytics: Google
    • Foundations of Data Structures and Algorithms: University of Colorado Boulder
    • Data Science: Foundations using R: Johns Hopkins University
    • Data Science: Johns Hopkins 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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