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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

      Generative AI: Prompt Engineering Basics

      Skills you'll gain: Prompt Engineering, ChatGPT, Generative AI, Large Language Modeling, Image Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.7K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Alberta

      Software Product Management

      Skills you'll gain: Requirements Analysis, Agile Software Development, Agile Methodology, Kanban Principles, Project Planning, Requirements Elicitation, Sprint Retrospectives, Requirements Management, Functional Requirement, Business Requirements, Sprint Planning, Software Development Methodologies, Software Development Life Cycle, Scrum (Software Development), Software Technical Review, Code Review, Software Development, Product Requirements, Risk Management Framework, User Story

      4.7
      Rating, 4.7 out of 5 stars
      ·
      12K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Conduct UX Research and Test Early Concepts

      Skills you'll gain: UI/UX Research, Usability Testing, User Experience Design, Usability, Presentations, User Research, User Experience, Design Research, Research Design, User Centered Design, Research Methodologies, Prototyping, Interviewing Skills, Information Privacy

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.9K reviews

      Beginner · Course · 1 - 4 Weeks

    • T

      The University of Edinburgh

      Data Science in Stratified Healthcare and Precision Medicine

      Skills you'll gain: Precision Medicine, Bioinformatics, Image Analysis, Medical Imaging, Big Data, Health Informatics, Statistical Methods, Data Science, Machine Learning, Natural Language Processing, Probability & Statistics, Data Analysis, Molecular Biology, Network Analysis, Graph Theory, Healthcare Ethics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      334 reviews

      Intermediate · Course · 1 - 3 Months

    • S

      Stanford University

      Cryptography I

      Skills you'll gain: Cryptography, Data Encryption Standard, Encryption, Key Management, Advanced Encryption Standard (AES), Public Key Cryptography Standards (PKCS), Cybersecurity, Authentications, Data Integrity, Secure Coding, Algorithms

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.4K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Irvine

      Data Science Fundamentals

      Skills you'll gain: Data Ethics, Predictive Modeling, Unsupervised Learning, Natural Language Processing, Predictive Analytics, Data Analysis, Classification And Regression Tree (CART), Regression Analysis, Data Mining, Statistical Analysis, Data Science, Social Media, Text Mining, Anomaly Detection, Business Analytics, Decision Tree Learning, Statistical Modeling, Big Data, Analytics, Cloud Computing

      4.3
      Rating, 4.3 out of 5 stars
      ·
      240 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Washington

      Machine Learning

      Skills you'll gain: Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Modeling, Artificial Intelligence, Deep Learning, Data Mining, Computer Vision, Statistical Machine Learning, Predictive Analytics, Text Mining, Machine Learning Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      16K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Drug Development Product Management

      Skills you'll gain: Clinical Trials, Pharmaceuticals, Clinical Research, Commercialization, Pharmacotherapy, Pharmacology, Regulatory Affairs, Intellectual Property, Portfolio Management, Bioinformatics, New Product Development, Medical Science and Research, Strategic Partnership, Product Marketing, Go To Market Strategy, Health Care Procedure and Regulation, Business Strategy, Marketing Strategies, Market Dynamics, Molecular Biology

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Visualization with Python

      Skills you'll gain: Data Visualization Software, Plotly, Data Visualization, Dashboard, Interactive Data Visualization, Matplotlib, Seaborn, Data Presentation, Data Analysis, Geospatial Information and Technology, Pandas (Python Package), Scatter Plots, Histogram, Heat Maps, Box Plots

      4.5
      Rating, 4.5 out of 5 stars
      ·
      12K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM Introduction to Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Unsupervised Learning, Supervised Learning, Dimensionality Reduction, Regression Analysis, Statistical Inference, Machine Learning Algorithms, Data Processing, Machine Learning, Data Access, Anomaly Detection, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Statistical Analysis, Data Analysis, Applied Machine Learning, Data Cleansing, Data Manipulation, Predictive Modeling

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

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      GPU Programming

      Skills you'll gain: Artificial Neural Networks, Image Analysis, Event-Driven Programming, C and C++, Scalability, Deep Learning, Software Development, Machine Learning Methods, Performance Tuning, Linear Algebra, Distributed Computing, System Programming, Computer Graphics, Computer Hardware, Computer Vision, Numerical Analysis, Computer Architecture, Data Processing, Data Structures, Performance Testing

      Build toward a degree

      2.7
      Rating, 2.7 out of 5 stars
      ·
      151 reviews

      Intermediate · Specialization · 3 - 6 Months

    • T

      The University of Sydney

      Positive Psychiatry and Mental Health

      Skills you'll gain: Mental Health, Stress Management, Community Mental Health Services, Mindfulness, Mental Health Diseases and Disorders, Psychiatry, Positivity, Rehabilitation, Resilience, Behavioral Health, Clinical Psychology, Mental Health Therapies, Psychotherapy, Personal Development, Mental and Behavioral Health, Creativity, Self-Awareness, Occupational Therapy, Empowerment, Physical Therapy

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.8K reviews

      Mixed · Course · 1 - 3 Months

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    1…232425…615

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

    • Generative AI: Prompt Engineering Basics: IBM
    • Software Product Management: University of Alberta
    • Conduct UX Research and Test Early Concepts: Google
    • Data Science in Stratified Healthcare and Precision Medicine: The University of Edinburgh
    • Cryptography I: Stanford University
    • Data Science Fundamentals: University of California, Irvine
    • Machine Learning: University of Washington
    • Drug Development Product Management: University of California San Diego
    • Data Visualization with Python: IBM
    • IBM Introduction to Machine Learning: IBM

    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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