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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

    • I

      IBM

      Information Technology (IT) and Cloud Fundamentals

      Skills you'll gain: Cloud Computing Architecture, Cloud Services, Peripheral Devices, Cybersecurity, Computing Platforms, Cloud Security, Cloud Infrastructure, Network Troubleshooting, Cloud Platforms, Encryption, Data Storage, Cyber Attacks, Software Development Life Cycle, Technical Support, Networking Hardware, Application Development, Computer Hardware, Information Technology, Cloud Computing, Databases

      4.7
      Rating, 4.7 out of 5 stars
      ·
      10K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Colorado Boulder

      Advanced Data Structures, RSA and Quantum Algorithms

      Skills you'll gain: Public Key Cryptography Standards (PKCS), Cryptography, Data Structures, Data Encryption Standard, Algorithms, Encryption, Theoretical Computer Science, Computer Science, Programming Principles, Computational Thinking, IBM Cloud, Linear Algebra, Mathematical Theory & Analysis, Arithmetic

      4.6
      Rating, 4.6 out of 5 stars
      ·
      30 reviews

      Advanced · Course · 1 - 4 Weeks

    • F

      Fractal Analytics

      Quantum Computing For Everyone - An Introduction

      Skills you'll gain: Computer Science, IBM Cloud, Algorithms, Data Ethics, Computational Thinking, Linear Algebra, Emerging Technologies, Cryptography, Physics, Applied Mathematics

      4
      Rating, 4 out of 5 stars
      ·
      63 reviews

      Beginner · Course · 1 - 4 Weeks

    • M

      Microsoft

      Introduction to Networking and Cloud Computing

      Skills you'll gain: Network Security, Cloud Computing, Network Infrastructure, Microsoft Azure, Cloud Services, Firewall, Computer Networking, Virtualization and Virtual Machines, Digital Transformation, Networking Hardware, Cybersecurity, Network Protocols, Artificial Intelligence and Machine Learning (AI/ML)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      484 reviews

      Beginner · Course · 1 - 3 Months

    • G

      Google Cloud

      Preparing for Google Cloud Certification: Cloud Engineer

      Skills you'll gain: Cloud Infrastructure, Kubernetes, Google Cloud Platform, Identity and Access Management, Prompt Engineering, Cloud Storage, Containerization, Infrastructure As A Service (IaaS), Cloud Computing Architecture, Cloud Management, Cloud Services, Load Balancing, Cloud Engineering, Application Deployment, Infrastructure as Code (IaC), Virtual Machines, Cloud Computing, Data Storage, Network Infrastructure, Docker (Software)

      4.7
      Rating, 4.7 out of 5 stars
      ·
      59K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • I

      IBM

      IBM Back-end JavaScript Developer

      Skills you'll gain: Istio, Node.JS, Software Development Life Cycle, Containerization, Server Side, MongoDB, Application Deployment, Cloud-Native Computing, NoSQL, Kubernetes, Restful API, OpenShift, Git (Version Control System), Cloud Applications, GitHub, Serverless Computing, Back-End Web Development, HTML and CSS, Ajax, Interviewing Skills

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.8K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      University of Pennsylvania

      Computational Thinking for Problem Solving

      Skills you'll gain: Computational Thinking, Algorithms, Pseudocode, Python Programming, Data Structures, Computer Hardware, Computer Programming, Analysis, Debugging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      IT Fundamentals for Cybersecurity

      Skills you'll gain: IT Service Management, Cloud Computing, Information Technology Infrastructure Library, Malware Protection, Identity and Access Management, Linux, Incident Response, Networking Hardware, TCP/IP, Cybersecurity, Linux Administration, Network Security, Network Protocols, Computer Security Incident Management, Cloud Security, Operating Systems, Endpoint Detection and Response, Cyber Risk, Data Ethics, Cyber Governance

      4.6
      Rating, 4.6 out of 5 stars
      ·
      22K reviews

      Beginner · Specialization · 3 - 6 Months

    • É

      École Polytechnique Fédérale de Lausanne

      Big Data Analysis with Scala and Spark

      Skills you'll gain: Apache Spark, Apache Hadoop, Scala Programming, Distributed Computing, Big Data, Data Manipulation, Data Processing, Performance Tuning, Functional Design, Data Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.6K reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      Key Technologies for Business

      Skills you'll gain: Cloud Computing Architecture, Cloud Services, Large Language Modeling, Cloud Security, Data Literacy, Cloud Infrastructure, Data Mining, Cloud Platforms, Cloud Computing, Artificial Intelligence, Generative AI, Cloud Development, Data Ethics, Cloud Storage, Artificial Intelligence and Machine Learning (AI/ML), Infrastructure As A Service (IaaS), Big Data, Applied Machine Learning, Data Analysis, Data Science

      4.7
      Rating, 4.7 out of 5 stars
      ·
      100K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      IBM Front-End Developer

      Skills you'll gain: Bootstrap (Front-End Framework), Software Development Life Cycle, User Centered Design, Cloud-Native Computing, React Redux, NoSQL, Git (Version Control System), GitHub, Webpack, Application Development, MongoDB, React.js, Agile Methodology, HTML and CSS, Front-End Web Development, JavaScript Frameworks, Browser Compatibility, Development Environment, Version Control, Interviewing Skills

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

      Beginner · Professional Certificate · 3 - 6 Months

    • 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 Wrangling, Data Visualization, Plot (Graphics), Statistical Programming, Ggplot2, Big Data, Git (Version Control System), Data Integration, Knitr, Data Analysis, Data Sharing, Statistical Reporting

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

      Beginner · Specialization · 3 - 6 Months

    Parallel Computing learners also search

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    1…678…282

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

    • Information Technology (IT) and Cloud Fundamentals: IBM
    • Advanced Data Structures, RSA and Quantum Algorithms: University of Colorado Boulder
    • Quantum Computing For Everyone - An Introduction : Fractal Analytics
    • Introduction to Networking and Cloud Computing: Microsoft
    • Preparing for Google Cloud Certification: Cloud Engineer: Google Cloud
    • IBM Back-end JavaScript Developer: IBM
    • Computational Thinking for Problem Solving: University of Pennsylvania
    • IT Fundamentals for Cybersecurity: IBM
    • Big Data Analysis with Scala and Spark: École Polytechnique Fédérale de Lausanne
    • Key Technologies for Business: IBM

    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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