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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: Free Trial
      Free Trial
      I

      IBM

      NoSQL, Big Data, and Spark Foundations

      Skills you'll gain: NoSQL, Apache Hadoop, Apache Spark, MongoDB, PySpark, Apache Hive, Databases, Apache Cassandra, Big Data, Machine Learning, Generative AI, IBM Cloud, Applied Machine Learning, Kubernetes, Supervised Learning, Distributed Computing, Docker (Software), Database Management, Data Pipelines, Scalability

      4.5
      Rating, 4.5 out of 5 stars
      ·
      764 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Introduction to Parallel Programming with CUDA

      Skills you'll gain: Performance Tuning, OS Process Management, Data Structures, Performance Testing, Distributed Computing, System Programming, Data Access, Hardware Architecture, C (Programming Language), C++ (Programming Language), Algorithms, Computer Architecture, Data Storage, Development Environment, Program Development, Debugging

      2.9
      Rating, 2.9 out of 5 stars
      ·
      50 reviews

      Intermediate · Course · 1 - 3 Months

    • N

      NVIDIA

      AI Infrastructure and Operations Fundamentals

      Skills you'll gain: Generative AI, Large Language Modeling, MLOps (Machine Learning Operations), Artificial Intelligence, Cloud Computing, Cloud Infrastructure, IT Infrastructure, Deep Learning, Network Infrastructure, Tensorflow, Hardware Architecture, Machine Learning, PyTorch (Machine Learning Library), Data Centers, Computer Architecture, Data Storage

      4.6
      Rating, 4.6 out of 5 stars
      ·
      357 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Advanced Machine Learning on Google Cloud

      Skills you'll gain: Natural Language Processing, MLOps (Machine Learning Operations), Tensorflow, Large Language Modeling, Reinforcement Learning, Computer Vision, Google Cloud Platform, Keras (Neural Network Library), Systems Design, Image Analysis, Hybrid Cloud Computing, Applied Machine Learning, Systems Architecture, Performance Tuning, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Artificial Neural Networks, Machine Learning, Machine Learning Algorithms, Distributed Computing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.5K reviews

      Advanced · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Inferential Statistics

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Inference, Statistical Reporting, Statistical Methods, R Programming, Statistical Software, Statistical Analysis, Probability & Statistics, Data Literacy, Sampling (Statistics), Probability Distribution, Software Installation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.7K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Pennsylvania

      Cryptocurrency and Blockchain: An Introduction to Digital Currencies

      Skills you'll gain: Blockchain, Cryptography, Digital Assets, Investments, Portfolio Management, FinTech, Financial Analysis, Financial Market, Emerging Technologies, Transaction Processing, Distributed Computing, Risk Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.5K reviews

      Mixed · Course · 1 - 4 Weeks

    • I

      IBM

      Introduction to Computer Vision and Image Processing

      Skills you'll gain: Computer Vision, Image Analysis, Artificial Neural Networks, IBM Cloud, Keras (Neural Network Library), Cloud Applications, Deep Learning, Tensorflow, Visualization (Computer Graphics), PyTorch (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Computer Programming, Application Deployment, Augmented Reality, Machine Learning, Data Processing

      4.3
      Rating, 4.3 out of 5 stars
      ·
      1.4K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Automating Real-World Tasks with Python

      Skills you'll gain: Web Services, Python Programming, Restful API, Professional Development, Automation, Scripting, Application Programming Interface (API), Stress Management, JSON, Debugging

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.9K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Build Basic Generative Adversarial Networks (GANs)

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

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Exploratory Data Analysis

      Skills you'll gain: Exploratory Data Analysis, Data Visualization, Plot (Graphics), Ggplot2, Dimensionality Reduction, Data Visualization Software, R Programming, Scatter Plots, Graphing, Box Plots, Data Analysis, Histogram, Statistical Analysis, Unsupervised Learning, Color Theory

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.1K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Elastic Google Cloud Infrastructure: Scaling and Automation

      Skills you'll gain: Google Cloud Platform, Cloud Infrastructure, Load Balancing, Infrastructure as Code (IaC), Cloud Computing, Managed Services, Solution Architecture, IT Automation, Virtual Machines, Network Infrastructure, Virtual Private Networks (VPN), Scalability

      4.7
      Rating, 4.7 out of 5 stars
      ·
      9.2K reviews

      Intermediate · Course · 1 - 3 Months

    • C

      Coursera Instructor Network

      Introduction to Cybersecurity Fundamentals

      Skills you'll gain: Computer Security Awareness Training, Cybersecurity, Security Awareness, Cyber Attacks, Data Security, Personally Identifiable Information, Malware Protection, Threat Management, Email Security

      4.6
      Rating, 4.6 out of 5 stars
      ·
      835 reviews

      Beginner · Course · 1 - 4 Weeks

    Parallel Computing learners also search

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    1…343536…285

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

    • NoSQL, Big Data, and Spark Foundations: IBM
    • Introduction to Parallel Programming with CUDA: Johns Hopkins University
    • AI Infrastructure and Operations Fundamentals: NVIDIA
    • Advanced Machine Learning on Google Cloud: Google Cloud
    • Inferential Statistics: Duke University
    • Cryptocurrency and Blockchain: An Introduction to Digital Currencies: University of Pennsylvania
    • Introduction to Computer Vision and Image Processing: IBM
    • Automating Real-World Tasks with Python: Google
    • Build Basic Generative Adversarial Networks (GANs): DeepLearning.AI
    • Exploratory Data Analysis: Johns Hopkins University

    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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