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    • Parallel Computing

    Parallel Computing Courses Online

    Learn parallel computing for high-performance computing applications. Understand how to design and implement parallel algorithms.

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    Explore the Parallel Computing Course Catalog

    • U

      University of Colorado Boulder

      Introduction to High-Performance and Parallel Computing

      Skills you'll gain: Bash (Scripting Language), Scalability, Distributed Computing, Big Data, Operating Systems, File Systems, Linux, Job Control Language (JCL), Command-Line Interface, Performance Tuning, Computer Architecture

      Build toward a degree

      3.6
      Rating, 3.6 out of 5 stars
      ·
      137 reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      Introduction to Cloud Computing

      Skills you'll gain: Cloud Computing Architecture, Cloud Services, Cloud Security, Cloud Infrastructure, Cloud Platforms, Cloud Computing, Cloud Development, Cloud Storage, Infrastructure As A Service (IaaS), Software As A Service, Emerging Technologies, Cloud-Native Computing, Hybrid Cloud Computing, IBM Cloud, Virtual Machines, Serverless Computing, Microservices, Identity and Access Management, DevOps

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.3K reviews

      Beginner · Course · 1 - 3 Months

    • 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

    • 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, OS Process Management, Data Structures, Performance Testing

      Build toward a degree

      2.7
      Rating, 2.7 out of 5 stars
      ·
      146 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: AI skills
      AI skills
      I

      IBM

      IBM Full Stack Software Developer

      Skills you'll gain: Istio, Node.JS, Software Development Life Cycle, Unit Testing, Object-Relational Mapping, Cloud Computing Architecture, Server Side, Application Deployment, React Redux, Kubernetes, Cloud Services, OpenShift, Git (Version Control System), Cloud Applications, Full-Stack Web Development, HTML and CSS, Cloud Computing, Jupyter, Large Language Modeling, Interviewing Skills

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      55K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • R

      Rice University

      Parallel Programming in Java

      Skills you'll gain: Java Programming, Java, Distributed Computing, Programming Principles, Application Frameworks, Algorithms, Performance Tuning, Functional Design, Scalability, Computer Science

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.2K reviews

      Intermediate · Course · 1 - 3 Months

    • É

      École Polytechnique Fédérale de Lausanne

      Functional Programming in Scala

      Skills you'll gain: Scala Programming, Apache Spark, Apache Hadoop, User Interface (UI), Distributed Computing, Programming Principles, Big Data, Software Design, Data Structures, Software Design Patterns, Functional Design, Data Manipulation, Object Oriented Programming (OOP), Interactive Data Visualization, Computer Programming, Data Processing, Real Time Data, Visualization (Computer Graphics), Performance Tuning, Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      11K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: New AI skills
      New AI skills
      G

      Google

      Google Data Analytics

      Skills you'll gain: Data Storytelling, Data Literacy, Data Visualization, Data Presentation, Data Ethics, Rmarkdown, 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), R Programming

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      167K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free
      Free
      P

      Princeton University

      Computer Architecture

      Skills you'll gain: Microarchitecture, Computer Architecture, Hardware Architecture, Computer Systems, Computer Engineering, Distributed Computing, Operating Systems, Performance Tuning, Scalability

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Advanced · Course · 3 - 6 Months

    • I
      I

      Multiple educators

      IBM and ISC2 Cybersecurity Specialist

      Skills you'll gain: Network Security, Incident Response, Cloud Computing Architecture, Penetration Testing, Computer Security Incident Management, Cloud Services, Security Controls, Business Continuity, Disaster Recovery, Information Assurance, Peripheral Devices, Cybersecurity, Configuration Management, Computing Platforms, Cloud Security, Cloud Infrastructure, Network Troubleshooting, Cloud Platforms, Encryption, Data Storage

      4.7
      Rating, 4.7 out of 5 stars
      ·
      13K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • S

      Stanford University

      Algorithms

      Skills you'll gain: Data Structures, Graph Theory, Algorithms, Bioinformatics, Theoretical Computer Science, Network Model, Computational Thinking, Network Analysis, Analysis, Programming Principles, Probability & Statistics, Network Routing, Probability, Operations Research, Design Strategies

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

      Intermediate · Specialization · 3 - 6 Months

    • Status: New
      New
      I

      IBM

      IBM Java Developer

      Skills you'll gain: Spring Framework, Cloud-Native Computing, Software Development Life Cycle, Database Design, Hibernate (Java), Restful API, Front-End Web Development, Docker (Software), Containerization, Git (Version Control System), GitHub, Model View Controller, Microservices, HTML and CSS, Object Oriented Programming (OOP), Spring Boot, Object-Relational Mapping, Large Language Modeling, Java Programming, Interviewing Skills

      4.6
      Rating, 4.6 out of 5 stars
      ·
      5.4K reviews

      Beginner · Professional Certificate · 3 - 6 Months

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

    • Introduction to High-Performance and Parallel Computing: University of Colorado Boulder
    • Introduction to Cloud Computing: IBM
    • Parallel, Concurrent, and Distributed Programming in Java: Rice University
    • GPU Programming: Johns Hopkins University
    • IBM Full Stack Software Developer: IBM
    • Parallel Programming in Java: Rice University
    • Functional Programming in Scala: École Polytechnique Fédérale de Lausanne
    • Google Data Analytics: Google
    • Computer Architecture: Princeton University
    • IBM and ISC2 Cybersecurity Specialist: ISC2

    Skills you can learn in Software Development

    Programming Language (34)
    Google (25)
    Computer Program (21)
    Software Testing (21)
    Web (19)
    Google Cloud Platform (18)
    Application Programming Interfaces (17)
    Data Structure (16)
    Problem Solving (14)
    Object-oriented Programming (13)
    Kubernetes (10)
    List & Label (10)

    Frequently Asked Questions about Parallel Computing

    Parallel computing is the design, study, and process of using algorithms to make multiple computers solve computational problems simultaneously. In parallel computing, problems are split up into several parts for more than two computers to work on at the same time. These parts each have their own set of instructions that are executed on multiple central processing units (CPUs).

    Parallel computing speeds up problem-solving in computational learning. Previously, most computations were done individually by software written for use on a single computer with one CPU. This meant that only one instruction could be executed at any time.‎

    It's important to learn about parallel computing because it is the primary system used by programmers today to increase computation power for faster application problem solving and processing power. From multi-core personal computers to supercomputers, parallel computing is what is driving the core processing power.

    A processor is the computing power that drives your phone, laptop, and tablet. With more power in the processor, applications will run faster and better on your mobile device. Even smartphones are using multicore processing power, with some up to four and eight cores. Parallel computing helps to make this possible. This alone makes parallel computing worth knowing about for its current device applications and also its growing importance into the future.‎

    Learning parallel computing can bring you into careers as a parallel programming architect, a software engineer, or a high performance computing engineer. Many companies are looking for computing talents who can deliver and innovate in the graphics and parallel computing fields.

    Companies are continually looking to develop new parallel programming models for their GPU architecture. This is where learning about parallel computing can help you to succeed. By gaining new knowledge for creating new infrastructures and new architectures in parallel computing, you can play a part in advancing the state-of-the-art graphics performance in parallel programming models.‎

    When you take online courses about parallel computing, you will understand programming, software development, and computational power more clearly. You will study topics like data-parallel programs, how to express the functions of common parallel algorithms, and how to write and use parallel code in programs that use parallel collections to achieve higher computational performance. In these courses, industry experts will teach you not just how parallel computing works in relation to modern GPU architecture, but also how you can use your knowledge base to advance your careers in our increasingly digital world.‎

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

    When looking to enhance your workforce's skills in Parallel 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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