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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
      I

      IBM

      IBM Systems Analyst

      Skills you'll gain: Data Storytelling, Business Analysis, Systems Development Life Cycle, Business Process Modeling, Process Optimization, Requirements Management, Business Requirements, Stakeholder Management, Stakeholder Engagement, Systems Analysis, Risk Analysis, Requirements Analysis, Data Visualization Software, Information Technology, Dashboard, Business Systems Analysis, IBM Cognos Analytics, Computer Hardware, Cloud Computing, Network Troubleshooting

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4.4K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • H

      Hebrew University of Jerusalem

      Build a Modern Computer from First Principles: Nand to Tetris Part II (project-centered course)

      Skills you'll gain: Computer Science, Computer Engineering, Computer Architecture, Computer Programming, System Software, Virtual Machines, Operating Systems, Software Architecture, Algorithms, Software Design, Program Development, Object Oriented Programming (OOP), Data Structures, System Implementation, Computer Graphics

      4.9
      Rating, 4.9 out of 5 stars
      ·
      525 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free
      Free
      U

      University of Maryland, College Park

      Exploring Quantum Physics

      Skills you'll gain: Physics, Quantitative Research, Science and Research, Mechanics, Physical Science, Chemistry, Advanced Mathematics, Linear Algebra, Calculus, Mathematical Modeling, Engineering Analysis, Differential Equations

      4.2
      Rating, 4.2 out of 5 stars
      ·
      67 reviews

      Mixed · Course · 1 - 3 Months

    • G

      Georgia Institute of Technology

      System Issues in Cloud Computing

      Skills you'll gain: Cloud Applications, Cloud Development, Cloud-Native Computing, Software-Defined Networking, Cloud Computing, Cloud Infrastructure, Distributed Computing, Application Development, Cloud Management, Virtualization, Virtual Machines, Cloud Computing Architecture, Network Performance Management, Data Store, Network Architecture, Multi-Tenant Cloud Environments, Network Monitoring, Network Infrastructure, Computer Networking, Data Centers

      4.5
      Rating, 4.5 out of 5 stars
      ·
      396 reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Unsupervised Learning, Recommenders, Reinforcement Learning

      Skills you'll gain: Unsupervised Learning, Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Data Ethics, Machine Learning, Machine Learning Algorithms, Supervised Learning, Reinforcement Learning, Statistical Machine Learning, Artificial Neural Networks, Deep Learning, Anomaly Detection, Dimensionality Reduction, Algorithms, Collaborative Software

      4.9
      Rating, 4.9 out of 5 stars
      ·
      4.7K reviews

      Beginner · Course · 1 - 4 Weeks

    • D

      DeepLearning.AI

      Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

      Skills you'll gain: Tensorflow, Computer Vision, Image Analysis, Keras (Neural Network Library), Deep Learning, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      20K reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Problem Solving Using Computational Thinking

      Skills you'll gain: Computational Thinking, Programming Principles, Computer Science, Disaster Recovery, Algorithms, Design Thinking, Simulations

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

      Beginner · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      The Data Scientist’s Toolbox

      Skills you'll gain: Rmarkdown, Version Control, Data Science, Big Data, Git (Version Control System), GitHub, Data Analysis, R Programming, Statistical Programming, Development Environment, Integrated Development Environments, Software Installation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      34K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: AI skills
      AI skills
      M

      Microsoft

      Microsoft Cybersecurity Analyst

      Skills you'll gain: Threat Modeling, MITRE ATT&CK Framework, Penetration Testing, Azure Active Directory, Network Security, Computer Systems, Security Information and Event Management (SIEM), Security Testing, Encryption, Cybersecurity, System Testing, Cloud Security, Threat Management, Vulnerability Scanning, Cloud Computing, Business Software, Cyber Attacks, Authentications, Active Directory, Data Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.5K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      University of Washington

      Data Manipulation at Scale: Systems and Algorithms

      Skills you'll gain: Big Data, Relational Databases, Database Systems, Dataflow, Data Science, Data Manipulation, Data Processing, NoSQL, Apache Spark, Analytics, Distributed Computing, Apache Hadoop, SQL, Data Analysis, Query Languages, Cloud Computing, Scalability, Graph Theory, Algorithms

      4.3
      Rating, 4.3 out of 5 stars
      ·
      767 reviews

      Mixed · Course · 1 - 3 Months

    • M

      Microsoft

      Introduction to Microsoft Azure Cloud Services

      Skills you'll gain: Microsoft Azure, Cloud Services, Virtualization, Cloud Computing, Virtual Machines, Cloud Platforms, Cloud Storage, Cloud Infrastructure, Virtual Private Networks (VPN), Public Cloud, General Networking, Database Management Systems, Scalability

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

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Genomic Data Science

      Skills you'll gain: Bioinformatics, Unix Commands, Biostatistics, Exploratory Data Analysis, Statistical Analysis, Unix, Data Science, Data Management, Statistical Methods, Molecular Biology, Command-Line Interface, Statistical Hypothesis Testing, Linux Commands, Data Analysis Software, Statistical Modeling, Data Structures, Data Analysis, R Programming, Computational Thinking, Jupyter

      4.5
      Rating, 4.5 out of 5 stars
      ·
      6.6K reviews

      Intermediate · Specialization · 3 - 6 Months

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    1…101112…282

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

    • IBM Systems Analyst: IBM
    • Build a Modern Computer from First Principles: Nand to Tetris Part II (project-centered course): Hebrew University of Jerusalem
    • Exploring Quantum Physics: University of Maryland, College Park
    • System Issues in Cloud Computing: Georgia Institute of Technology
    • Unsupervised Learning, Recommenders, Reinforcement Learning: DeepLearning.AI
    • Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning: DeepLearning.AI
    • Problem Solving Using Computational Thinking: University of Michigan
    • The Data Scientist’s Toolbox: Johns Hopkins University
    • Microsoft Cybersecurity Analyst: Microsoft
    • Data Manipulation at Scale: Systems and Algorithms: University of Washington

    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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