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    • Scientific Computing

    Scientific Computing Courses Online

    Learn scientific computing for data analysis and simulations. Understand algorithms, numerical methods, and programming for scientific applications.

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    Explore the Scientific Computing Course Catalog

    • P

      Packt

      Practical Quantum Computing with IBM Qiskit for Beginners

      Skills you'll gain: IBM Cloud, Cryptography, Algorithms, Python Programming, Linear Algebra, Programming Principles, Computer Science, Theoretical Computer Science, Emerging Technologies, Test Case, Jupyter, Physics, Simulations, Software Installation, Debugging, Development Environment

      Beginner · Course · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM DevOps and Software Engineering

      Skills you'll gain: User Story, CI/CD, Istio, Open Web Application Security Project (OWASP), Software Development Life Cycle, Continuous Integration, Linux Commands, Kubernetes, Cloud Computing Architecture, Application Deployment, Test Driven Development (TDD), Gherkin (Scripting Language), Jenkins, Bash (Scripting Language), Agile Software Development, DevOps, Git (Version Control System), Flask (Web Framework), Jupyter, Grafana

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      60K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      R

      Rice University

      Parallel, Concurrent, and Distributed Programming in Java

      Skills you'll gain: Apache Kafka, Apache Spark, Apache Hadoop, Distributed Computing, Java Programming, Java, Software Architecture, Systems Architecture, Data Structures, System Programming, Programming Principles, Servers, Application Frameworks, Debugging, Algorithms, Performance Tuning, Network Protocols, Computer Science, Functional Design, Scalability

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.6K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Generative AI Fundamentals

      Skills you'll gain: Prompt Engineering, Generative AI, ChatGPT, OpenAI, Data Ethics, Large Language Modeling, Leadership and Management, Business Leadership, Strategic Leadership, Business Ethics, Legal Risk, IBM Cloud, Google Cloud Platform, Artificial Intelligence, Program Development, Artificial Neural Networks, Business Development, Deep Learning, Content Creation, Business Transformation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.2K reviews

      Beginner · Specialization · 3 - 6 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), Version Control, Other Programming Languages, Query Languages

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

      Beginner · Course · 1 - 3 Months

    • Y

      Yale University

      Introduction to Psychology

      Skills you'll gain: Psychology, Mental and Behavioral Health Specialties, Child Development, Mental Health, Human Learning, Social Sciences, Behavioral Health, Neurology, Biology, Scientific Methods

      4.9
      Rating, 4.9 out of 5 stars
      ·
      31K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM AI Foundations for Business

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

      IBM

      Introduction to Data Science

      Skills you'll gain: SQL, Jupyter, Data Literacy, Data Mining, Peer Review, Data Modeling, Relational Databases, Stored Procedure, Databases, Data Science, Big Data, Query Languages, Data Cleansing, Data Visualization Software, GitHub, Business Analysis, Cloud Computing, Data Analysis, R Programming, Digital Transformation

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      99K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Introduction to Generative AI

      Skills you'll gain: Generative AI, Application Development, Artificial Intelligence, Google Cloud Platform, Machine Learning Methods

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.8K reviews

      Beginner · Course · 1 - 4 Weeks

    • K

      Korea Advanced Institute of Science and Technology(KAIST)

      Introduction to Quantum Information

      Skills you'll gain: Emerging Technologies, Digital Communications, Encryption, Theoretical Computer Science, Cryptography, Linear Algebra, Algorithms, Computational Thinking, Information Technology, Physics, Simulations, Mathematical Modeling

      4.2
      Rating, 4.2 out of 5 stars
      ·
      122 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Operating Systems and You: Becoming a Power User

      Skills you'll gain: Package and Software Management, File Systems, Microsoft Windows, Desktop Support, Linux, Operating Systems, OS Process Management, Linux Administration, Remote Access Systems, System Monitoring, Command-Line Interface, User Accounts, Systems Administration, Technical Support and Services, File Management, Linux Commands, Software Installation, Identity and Access Management, Authorization (Computing), Virtualization

      4.7
      Rating, 4.7 out of 5 stars
      ·
      29K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Mathematics for Machine Learning

      Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Probability & Statistics, Feature Engineering, Data Transformation, Jupyter, Data Science, Advanced Mathematics, Statistics, Machine Learning Algorithms, Machine Learning Methods, Statistical Analysis, Artificial Neural Networks, Algorithms, Data Manipulation, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      15K reviews

      Beginner · Specialization · 3 - 6 Months

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    In summary, here are 10 of our most popular scientific computing courses

    • Practical Quantum Computing with IBM Qiskit for Beginners: Packt
    • IBM DevOps and Software Engineering: IBM
    • Parallel, Concurrent, and Distributed Programming in Java: Rice University
    • Generative AI Fundamentals: IBM
    • Tools for Data Science: IBM
    • Introduction to Psychology : Yale University
    • IBM AI Foundations for Business: IBM
    • Introduction to Data Science: IBM
    • Introduction to Generative AI : Google Cloud
    • Introduction to Quantum Information: Korea Advanced Institute of Science and Technology(KAIST)

    Frequently Asked Questions about Scientific Computing

    Scientific computing is the high-powered, research-focused application of computing theories and methodologies to solve scientific problems. Another way to view scientific computing is that it is the intersection point between computer science, numerical mathematics, and modeling. In scientific computing, there are a variety of tools, techniques, and theories used to analyze science, engineering, and mathematical computer models of problems. This field of study is also known as computational science. With either definition, it is an area of science that encompasses many different disciplines while using advanced computing capabilities to understand and solve problems with natural systems.‎

    Scientific computing is valuable to learn as many of the concepts explored in this area deal with futuristic ways to use computers. One of these ways is due to the increased power of supercomputers in recent years. As a result, it has become easier for computer scientists to use scientific computing to create complex simulations that were previously unimaginable, such as particle physics. Someone who has learned computing through networking, computer hardware, programming, databases, or algorithms could have the right mix of skills and insights to learn scientific computing‎

    Typical career opportunities that can arise from learning scientific computing include working as a data scientist, cloud operations specialist, scientific programmer/modeler, data engineer, or DevOps engineer. Additional roles are in data acquisition, ingestion, and research integration as a computational scientist. Other roles involve creating user interfaces and back-end services to automate the scientific output of multi-institutional science research projects.‎

    When you take online courses about scientific computing, you can learn the fundamentals of science research and the mathematical methodologies involved in this scientific approach. You may also be exposed to data analysis as it relates to mathematical modeling, along with related knowledge originally developed within mathematics. Today, this set of mathematical techniques and theories is a major part of scientific computing known as numerical analysis. Taking online courses can help you learn more about these data-rich fields, as well as newer, advanced technologies like Databricks and Apache Spark that scientific computing experts use in large research projects.‎

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

    When looking to enhance your workforce's skills in Scientific Computing, 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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