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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

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM Generative AI Engineering

      Skills you'll gain: Prompt Engineering, Large Language Modeling, Predictive Modeling, Unit Testing, Supervised Learning, Feature Engineering, Generative AI, Keras (Neural Network Library), Deep Learning, Exploratory Data Analysis, Artificial Intelligence, Data Wrangling, ChatGPT, Natural Language Processing, Data Analysis, Jupyter, Unsupervised Learning, PyTorch (Machine Learning Library), Generative AI Agents, Data Ethics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      87K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      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, Mathematical Software, Engineering Calculations, Data Analysis, Data Processing, Engineering Analysis, Computer Programming, Programming Principles, UI Components, Software Design, Debugging

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

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Applied Data Science with Python

      Skills you'll gain: Matplotlib, Network Analysis, Feature Engineering, Data Visualization Software, Interactive Data Visualization, Scientific Visualization, Pandas (Python Package), Applied Machine Learning, Supervised Learning, Text Mining, Visualization (Computer Graphics), Statistical Visualization, Scikit Learn (Machine Learning Library), Network Model, Jupyter, NumPy, Graph Theory, Data Manipulation, Natural Language Processing, Data Analysis

      4.5
      Rating, 4.5 out of 5 stars
      ·
      34K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Foundations of User Experience (UX) Design

      Skills you'll gain: Design Thinking, User Research, User Experience Design, User Centered Design, Usability, Web Content Accessibility Guidelines, Cross Platform Development, Prototyping, Wireframing, Sprint Planning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      73K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      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 Wrangling, Data Visualization, Plotly, Machine Learning Algorithms, Plot (Graphics), Knitr

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

      Beginner · Specialization · 3 - 6 Months

    • U

      University of California San Diego

      Biology Meets Programming: Bioinformatics for Beginners

      Skills you'll gain: Bioinformatics, Programming Principles, Molecular Biology, Python Programming, Computational Thinking, Biology, Algorithms, Data Structures

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

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Amsterdam

      Introduction to Communication Science

      Skills you'll gain: Culture, Interpersonal Communications, Media and Communications, Liberal Arts, Social Studies, Research, Ancient History, Anthropology, European History, Qualitative Research, Research Methodologies

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.9K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM Data Analytics with Excel and R

      Skills you'll gain: Data Storytelling, Interactive Data Visualization, Shiny (R Package), Data Wrangling, Exploratory Data Analysis, Relational Databases, Big Data, Data Visualization Software, Ggplot2, Database Design, Data Analysis, IBM Cognos Analytics, Statistical Analysis, Data Presentation, Data Mining, Dashboard, Excel Formulas, Data Manipulation, Web Scraping, Microsoft Excel

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      28K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM AI Foundations for Business

      Skills you'll gain: Large Language Modeling, Artificial Intelligence, Data Literacy, Data Mining, Generative AI, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Information Architecture, Strategic Decision-Making, Enterprise Architecture, ChatGPT, Cloud Computing, Data Analysis, Data Science, Deep Learning, Machine Learning, Data Strategy, Business Strategy, Business Process Automation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      94K reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Foundations of Data Science

      Skills you'll gain: Data Storytelling, Data Ethics, Data Analysis, Workflow Management, Data-Driven Decision-Making, Analytical Skills, Data Science, Project Design, Communication, Business, Business Workflow Analysis, Stakeholder Communications, Machine Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.2K reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Tools for Data Science

      Skills you'll gain: Jupyter, Data Visualization Software, Data Science, GitHub, Big Data, R Programming, Statistical Programming, Application Programming Interface (API), Machine Learning, Cloud Computing, Git (Version Control System), Other Programming Languages, Version Control, Query Languages

      4.5
      Rating, 4.5 out of 5 stars
      ·
      30K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Foundations of Cybersecurity

      Skills you'll gain: Cybersecurity, Security Controls, Cyber Attacks, Security Management, Cyber Security Strategy, Incident Response, Cyber Risk, Security Information and Event Management (SIEM), Information Assurance, Data Ethics, Network Analysis, Ethical Standards And Conduct

      Build toward a degree

      4.9
      Rating, 4.9 out of 5 stars
      ·
      34K reviews

      Beginner · Course · 1 - 4 Weeks

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    1…456…612

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

    • IBM Generative AI Engineering: IBM
    • MATLAB Programming for Engineers and Scientists: Vanderbilt University
    • Applied Data Science with Python: University of Michigan
    • Foundations of User Experience (UX) Design: Google
    • Data Science: Johns Hopkins University
    • Biology Meets Programming: Bioinformatics for Beginners: University of California San Diego
    • Introduction to Communication Science: University of Amsterdam
    • IBM Data Analytics with Excel and R: IBM
    • IBM AI Foundations for Business: IBM
    • Foundations of Data Science: Google

    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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