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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

    • G

      Google Cloud

      Architecting with Google Kubernetes Engine

      Skills you'll gain: Kubernetes, Identity and Access Management, Cloud-Native Computing, Google Cloud Platform, CI/CD, Containerization, Application Deployment, Cloud Management, Scalability, Cloud Computing, Cloud Infrastructure, Load Balancing, Continuous Integration, DevOps, Continuous Delivery, YAML, Data Storage, Cloud Security, Cloud Services, Application Performance Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      5.1K reviews

      Beginner · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Introduction to Parallel Programming with CUDA

      Skills you'll gain: Performance Tuning, Data Structures, C and C++, Performance Testing, Distributed Computing, Computational Thinking, Data Access, Algorithms, Computer Hardware, Computer Architecture, Command-Line Interface, Data Storage, Program Development, Debugging

      2.8
      Rating, 2.8 out of 5 stars
      ·
      47 reviews

      Intermediate · Course · 1 - 3 Months

    • R

      Rice University

      Fundamentals of Computing

      Skills you'll gain: Computational Thinking, Event-Driven Programming, Algorithms, Combinatorics, Graph Theory, Programming Principles, Application Development, Object Oriented Programming (OOP), Data Structures, Probability, Computer Programming, Bioinformatics, Interactive Design, Program Development, Big Data, Python Programming, Mathematical Software, Data Analysis, Theoretical Computer Science, Computer Science

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.1K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      T

      The University of Sydney

      Blockchain Scalability and its Foundations in Distributed Systems

      Skills you'll gain: Blockchain, Distributed Computing, Security Engineering, Network Security, Scalability, Cryptography, Data Integrity, Transaction Processing, Algorithms

      4.5
      Rating, 4.5 out of 5 stars
      ·
      117 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University at Buffalo

      Blockchain Basics

      Skills you'll gain: Blockchain, Cryptography, Transaction Processing, Network Protocols, Encryption, Distributed Computing, FinTech, Virtual Environment, Data Integrity, Emerging Technologies, Virtual Machines, Verification And Validation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.7K reviews

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Organizational Change and Culture for Adopting Google Cloud

      Skills you'll gain: Business Transformation, Site Reliability Engineering, Innovation, Digital Transformation, Serverless Computing, DevOps, Application Programming Interface (API), Technology Strategies, Hybrid Cloud Computing, Safety Culture, Data Strategy, Organizational Change, Change Management, Cloud Infrastructure, Cloud Computing, Culture Transformation, Google Cloud Platform, People Management, Management Training And Development, CI/CD

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.7K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Generative Adversarial Networks (GANs)

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Image Analysis, Deep Learning, Artificial Neural Networks, Data Ethics, Applied Machine Learning, Computer Vision, Machine Learning, Unsupervised Learning, Artificial Intelligence, Information Privacy, Performance Testing, Machine Learning Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.4K reviews

      Intermediate · Specialization · 1 - 3 Months

    • U

      University of Colorado Boulder

      FPGA Design for Embedded Systems

      Skills you'll gain: Field-Programmable Gate Array (FPGA), Hardware Design, Electronic Hardware, Verification And Validation, Electronic Systems, Embedded Systems, Eclipse (Software), Application Specific Integrated Circuits, Electrical and Computer Engineering, Systems Design, Schematic Diagrams, Program Development, Integrated Development Environments, System Design and Implementation, Computer Architecture, Computational Logic, Hardware Architecture, Software Development, Development Testing, Test Case

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.7K reviews

      Intermediate · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Neuroscience and Neuroimaging

      Skills you'll gain: Magnetic Resonance Imaging, Neurology, Medical Imaging, Anatomy, Radiology, Image Analysis, Data Analysis, Analysis, Data Manipulation, Experimentation, R Programming, Statistical Analysis, Psychology, Network Analysis, Data Processing, Regression Analysis, Research Design, Scientific Visualization, Time Series Analysis and Forecasting, Matlab

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.3K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of California, Santa Cruz

      Bayesian Statistics: From Concept to Data Analysis

      Skills you'll gain: Bayesian Statistics, Statistical Inference, Data Analysis, Probability, Statistical Modeling, Statistical Analysis, Microsoft Excel, Probability Distribution, R Programming, Regression Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      ISC2

      Certified in Cybersecurity

      Skills you'll gain: Network Security, Incident Response, Security Controls, Business Continuity, Disaster Recovery, Information Assurance, Configuration Management, Cybersecurity, Security Management, Cyber Attacks, Computer Security Awareness Training, Data Security, Infrastructure Security, Risk Management Framework, Event Monitoring, Encryption, Threat Detection, Role-Based Access Control (RBAC), Authorization (Computing), Cyber Security Policies

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      Duke University

      Introduction to Machine Learning

      Skills you'll gain: PyTorch (Machine Learning Library), Reinforcement Learning, Image Analysis, Applied Machine Learning, Deep Learning, Machine Learning, Natural Language Processing, Supervised Learning, Unsupervised Learning, Artificial Neural Networks, Computer Vision, Medical Imaging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.7K reviews

      Intermediate · Course · 1 - 3 Months

    Parallel Computing learners also search

    Technology
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    GPU
    Kubernetes
    1…151617…282

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

    • Architecting with Google Kubernetes Engine: Google Cloud
    • Introduction to Parallel Programming with CUDA: Johns Hopkins University
    • Fundamentals of Computing: Rice University
    • Blockchain Scalability and its Foundations in Distributed Systems: The University of Sydney
    • Blockchain Basics: University at Buffalo
    • Organizational Change and Culture for Adopting Google Cloud: Google Cloud
    • Generative Adversarial Networks (GANs): DeepLearning.AI
    • FPGA Design for Embedded Systems: University of Colorado Boulder
    • Neuroscience and Neuroimaging: Johns Hopkins University
    • Bayesian Statistics: From Concept to Data Analysis: University of California, Santa Cruz

    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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