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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

    • Status: New
      New
      Status: Free
      Free
      G

      Google Quantum AI

      Hands-on quantum error correction with Google Quantum AI

      Skills you'll gain: Debugging, Emerging Technologies, Hardware Architecture, Failure Analysis, Simulation and Simulation Software, Theoretical Computer Science, Mathematical Modeling, Computer Architecture, Simulations, Linear Algebra, Computer Science

      4.5
      Rating, 4.5 out of 5 stars
      ·
      98 reviews

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Exploring Data Transformation with Google Cloud

      Skills you'll gain: Data Governance, Digital Transformation, Real Time Data, Google Cloud Platform, Data Management, Data Warehousing, Big Data, Looker (Software), Cloud Storage, Analytics, Business Intelligence, Data Processing, Dataflow, Database Systems, Data Migration

      4.8
      Rating, 4.8 out of 5 stars
      ·
      895 reviews

      Beginner · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Data Visualization & Dashboarding with R

      Skills you'll gain: Rmarkdown, Shiny (R Package), Ggplot2, Tidyverse (R Package), Spatial Data Analysis, Data Visualization, Statistical Visualization, Scatter Plots, Plot (Graphics), Dashboard, Data Import/Export, Interactive Data Visualization, R Programming, Data Visualization Software, Data Literacy, Data Manipulation, Plotly, Storyboarding, Data Storytelling, Heat Maps

      4.8
      Rating, 4.8 out of 5 stars
      ·
      429 reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of California San Diego

      Machine Learning With Big Data

      Skills you'll gain: Exploratory Data Analysis, Apache Spark, Big Data, Regression Analysis, Data Mining, Applied Machine Learning, Statistical Analysis, Machine Learning, Data Analysis, Unsupervised Learning, Data Transformation, Predictive Modeling, Data Cleansing, Supervised Learning, Decision Tree Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.5K reviews

      Mixed · Course · 1 - 3 Months

    • G

      Google Cloud

      Architecting with Google Compute Engine en Español

      Skills you'll gain: Cloud Infrastructure, Cloud Applications, Identity and Access Management, Google Cloud Platform, Application Deployment, Google App Engine, Infrastructure As A Service (IaaS), Microservices, Terraform, Kubernetes, Cloud Security, CI/CD, Cloud Computing, Load Balancing, Cloud Services, Cloud Computing Architecture, Network Architecture, Public Cloud, Data Storage, Infrastructure as Code (IaC)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.6K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Washington

      Machine Learning: Classification

      Skills you'll gain: Classification And Regression Tree (CART), Applied Machine Learning, Supervised Learning, Predictive Modeling, Text Mining, Machine Learning Algorithms, Data Cleansing, Scalability, Machine Learning, Natural Language Processing, Big Data, Probability & Statistics, Algorithms

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

      Mixed · Course · 1 - 3 Months

    • G

      Google Cloud

      Architecting with Google Kubernetes Engine en Español

      Skills you'll gain: Kubernetes, Cloud Infrastructure, Cloud Applications, CI/CD, Containerization, Identity and Access Management, Cloud-Native Computing, Infrastructure As A Service (IaaS), Google Cloud Platform, Cloud Services, Application Deployment, Public Cloud, Cloud Computing, Cloud Computing Architecture, Cloud Management, Role-Based Access Control (RBAC), Network Infrastructure, Docker (Software), Cloud Storage, Platform As A Service (PaaS)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Build Better Generative Adversarial Networks (GANs)

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Data Ethics, Deep Learning, Machine Learning, Image Analysis, Artificial Neural Networks, Performance Testing, Machine Learning Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      680 reviews

      Intermediate · Course · 1 - 4 Weeks

    • P

      Politecnico di Milano

      Technologies and platforms for Artificial Intelligence

      Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Cloud Platforms, Deep Learning, Hardware Architecture, Information Technology Architecture, Information Technology, Internet Of Things, Cloud Computing, Embedded Systems, Cloud Computing Architecture, Emerging Technologies, Data Centers, Application Development

      4.7
      Rating, 4.7 out of 5 stars
      ·
      55 reviews

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Building Resilient Streaming Analytics Systems on Google Cloud

      Skills you'll gain: Real Time Data, Data Pipelines, Google Cloud Platform, Data Processing, Big Data, Analytics, SQL, Data Transformation, Performance Tuning, Scalability

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.3K reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of California, Davis

      Computer Simulations

      Skills you'll gain: Simulations, Social Sciences, Systems Thinking, Agentic systems, Network Analysis, Computational Thinking, Sociology, Economics, Artificial Intelligence and Machine Learning (AI/ML), Computer Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      80 reviews

      Beginner · Course · 1 - 4 Weeks

    • A

      Amazon Web Services

      Getting Started with Data Analytics on AWS

      Skills you'll gain: Descriptive Analytics, Analytics, Data Analysis, Dashboard, Data Literacy, AWS Identity and Access Management (IAM), Data Visualization, Amazon Web Services, Big Data, Amazon S3, Business Intelligence, Cloud Computing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      890 reviews

      Beginner · Course · 1 - 4 Weeks

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    1…282930…284

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

    • Hands-on quantum error correction with Google Quantum AI: Google Quantum AI
    • Exploring Data Transformation with Google Cloud: Google Cloud
    • Data Visualization & Dashboarding with R: Johns Hopkins University
    • Machine Learning With Big Data: University of California San Diego
    • Architecting with Google Compute Engine en Español: Google Cloud
    • Machine Learning: Classification: University of Washington
    • Architecting with Google Kubernetes Engine en Español: Google Cloud
    • Build Better Generative Adversarial Networks (GANs): DeepLearning.AI
    • Technologies and platforms for Artificial Intelligence: Politecnico di Milano
    • Building Resilient Streaming Analytics Systems on Google Cloud: Google Cloud

    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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