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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
      G

      Google Cloud

      Smart Analytics, Machine Learning, and AI on Google Cloud

      Skills you'll gain: Google Cloud Platform, MLOps (Machine Learning Operations), Tensorflow, Unstructured Data, Applied Machine Learning, Data Pipelines, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Machine Learning, Jupyter, Natural Language Processing

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

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Production Machine Learning Systems

      Skills you'll gain: MLOps (Machine Learning Operations), Systems Design, Tensorflow, Hybrid Cloud Computing, Google Cloud Platform, Systems Architecture, Performance Tuning, Applied Machine Learning, Machine Learning, Distributed Computing, Scalability, Data Pipelines

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1K reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      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

    • Status: Free Trial
      Free Trial
      Status: AI skills
      AI skills
      G

      Google Cloud

      Google Cloud Data Analytics

      Skills you'll gain: Data Lakes, Data Storytelling, Data Governance, Data Presentation, Data Architecture, Data Pipelines, Data Visualization Software, Dashboard, Data Management, Cloud Infrastructure, Generative AI, Data Cleansing, Cloud Storage, Data Transformation, Cloud Computing, Google Cloud Platform, Database Management, Data Ethics, Data Analysis, Analytics

      4.4
      Rating, 4.4 out of 5 stars
      ·
      168 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      TensorFlow 2 for Deep Learning

      Skills you'll gain: Tensorflow, Generative AI, Data Pipelines, Keras (Neural Network Library), Deep Learning, Image Analysis, Computer Programming, Bayesian Statistics, Supervised Learning, Natural Language Processing, Data Processing, Computer Vision, Machine Learning Methods, Artificial Neural Networks, Machine Learning, Unsupervised Learning, Probability & Statistics, Time Series Analysis and Forecasting, Jupyter, Dimensionality Reduction

      4.8
      Rating, 4.8 out of 5 stars
      ·
      709 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Microsoft Azure Developer Associate (AZ-204) Exam Prep

      Skills you'll gain: Cloud Development, Microsoft Azure, Cloud Storage, Data Storage, Serverless Computing, Software Development, Cloud Security, Virtual Machines, Data Storage Technologies, CI/CD, Continuous Deployment, Development Environment, Cloud Management, Application Deployment, Cloud Applications, Data Security, Cloud Computing, Microsoft Power Automate/Flow, Event-Driven Programming, C# (Programming Language)

      4.6
      Rating, 4.6 out of 5 stars
      ·
      259 reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Big Data Integration and Processing

      Skills you'll gain: Apache Spark, Apache Hadoop, Data Integration, Big Data, Data Pipelines, Data Processing, Data Management, NoSQL, Analytics, Splunk, Database Systems, MongoDB, Pandas (Python Package), SQL, PostgreSQL

      4.4
      Rating, 4.4 out of 5 stars
      ·
      2.4K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Santa Cruz

      C for Everyone: Structured Programming

      Skills you'll gain: C (Programming Language), Debugging, C++ (Programming Language), Data Structures, Computer Programming, Command-Line Interface, Algorithms, Integrated Development Environments, Program Development, File Systems

      4.6
      Rating, 4.6 out of 5 stars
      ·
      769 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Alberta

      Prediction and Control with Function Approximation

      Skills you'll gain: Reinforcement Learning, Deep Learning, Machine Learning Algorithms, Machine Learning, Supervised Learning, Artificial Neural Networks, Pseudocode, Linear Algebra, Probability Distribution

      4.8
      Rating, 4.8 out of 5 stars
      ·
      836 reviews

      Intermediate · Course · 1 - 3 Months

    • I

      ISC2

      ISC2 Systems Security Certified Practitioner (SSCP)

      Skills you'll gain: Incident Response, Security Controls, Cryptography, Malware Protection, Key Management, Vulnerability Assessments, Risk Management, Continuous Monitoring, Public Key Infrastructure, Endpoint Security, Disaster Recovery, Computer Security Incident Management, OSI Models, Network Security, Encryption, Authentications, Mobile Security, Operational Risk, Security Awareness, Authorization (Computing)

      4.7
      Rating, 4.7 out of 5 stars
      ·
      215 reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Advanced Computer Vision with TensorFlow

      Skills you'll gain: Computer Vision, Tensorflow, Image Analysis, Applied Machine Learning, Deep Learning, Feature Engineering, Artificial Neural Networks, Visualization (Computer Graphics), Data Processing, Network Architecture

      4.7
      Rating, 4.7 out of 5 stars
      ·
      521 reviews

      Intermediate · Course · 1 - 4 Weeks

    • P

      Pohang University of Science and Technology(POSTECH)

      Introduction and Programming with IoT Boards

      Skills you'll gain: Internet Of Things, Wireless Networks, General Networking, Emerging Technologies, Electronic Hardware, Embedded Systems, Information Technology Architecture, Infrastructure Architecture, Software Architecture, Computer Hardware, Computer Programming Tools, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.8K reviews

      Beginner · Course · 1 - 3 Months

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    1…293031…284

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

    • Smart Analytics, Machine Learning, and AI on Google Cloud: Google Cloud
    • Production Machine Learning Systems: Google Cloud
    • Computer Simulations: University of California, Davis
    • Google Cloud Data Analytics: Google Cloud
    • TensorFlow 2 for Deep Learning: Imperial College London
    • Microsoft Azure Developer Associate (AZ-204) Exam Prep: Microsoft
    • Big Data Integration and Processing: University of California San Diego
    • C for Everyone: Structured Programming: University of California, Santa Cruz
    • Prediction and Control with Function Approximation: University of Alberta
    • ISC2 Systems Security Certified Practitioner (SSCP): 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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