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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
      U

      University of California, Santa Cruz

      Go and C++: Programming in Two Successor Languages of C

      Skills you'll gain: C++ (Programming Language), Go (Programming Language), Data Structures, Object Oriented Programming (OOP), Software Design Patterns, Debugging, Object Oriented Design, Programming Principles, Unit Testing, Algorithms, C (Programming Language), Program Development, Integrated Development Environments, Computer Programming, Software Testing, Computer Science, Graph Theory, File Management, Artificial Intelligence, Integration Testing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      2.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Virginia Darden School Foundation

      IBM & Darden Digital Strategy

      Skills you'll gain: Strategic Thinking, Digital Transformation, Business Strategy, Cloud Computing Architecture, Competitive Analysis, Cloud Services, Large Language Modeling, Artificial Intelligence, Business Transformation, Cloud Security, Cloud Technologies, Cloud Infrastructure, Big Data, Cloud Platforms, Data Analysis, Statistical Analysis, Cloud Hosting, Generative AI, Product Lifecycle Management, Business Technologies

      4.7
      Rating, 4.7 out of 5 stars
      ·
      45K reviews

      Beginner · Specialization · 3 - 6 Months

    • L

      LearnQuest

      Cloud Computing Basics (Cloud 101)

      Skills you'll gain: Cloud Computing, Cloud Services, Cloud Technologies, Cloud Infrastructure, Cloud Computing Architecture, Public Cloud, Infrastructure As A Service (IaaS), Serverless Computing, Amazon Web Services, Virtual Machines, Hybrid Cloud Computing, Software As A Service, Private Cloud, Microsoft Azure, Platform As A Service (PaaS), Scalability

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.5K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Introduction to Generative AI Learning Path

      Skills you'll gain: Large Language Modeling, Generative AI, Prompt Engineering, Data Ethics, Google Cloud Platform, Business Ethics, Application Development, Artificial Intelligence, Accountability, Compliance Training, Ethical Standards And Conduct, Artificial Intelligence and Machine Learning (AI/ML), Governance, Organizational Effectiveness, Machine Learning Methods, Decision Making, Corporate Strategy

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9.1K reviews

      Intermediate · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      DeepLearning.AI TensorFlow Developer

      Skills you'll gain: Tensorflow, Computer Vision, Image Analysis, Keras (Neural Network Library), Natural Language Processing, Time Series Analysis and Forecasting, Deep Learning, Artificial Neural Networks, Generative AI, Applied Machine Learning, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Text Mining, Forecasting, Data Processing, Supervised Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      25K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      A

      Amazon Web Services

      AWS Fundamentals

      Skills you'll gain: AWS Identity and Access Management (IAM), Amazon CloudWatch, Amazon DynamoDB, Amazon Web Services, Serverless Computing, Cloud Computing, Amazon S3, Scalability, Amazon Elastic Compute Cloud, Event-Driven Programming, Solution Architecture, Cloud Computing Architecture, Data Migration, Cloud Storage, API Gateway, Hybrid Cloud Computing, Cloud Management, Cloud Infrastructure, Cloud Security, Data Import/Export

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6.4K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      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 Trial
      Free Trial
      A

      Amazon Web Services

      AWS Cloud Technical Essentials

      Skills you'll gain: AWS Identity and Access Management (IAM), Amazon CloudWatch, Amazon DynamoDB, Amazon Web Services, Cloud Computing, Amazon S3, Scalability, Amazon Elastic Compute Cloud, Cloud Security, Serverless Computing, Cloud Storage, Databases, Virtual Private Networks (VPN), Load Balancing, General Networking, Containerization

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google

      System Administration and IT Infrastructure Services

      Skills you'll gain: Systems Administration, Cloud Infrastructure, IT Infrastructure, Lightweight Directory Access Protocols, Active Directory, Disaster Recovery, Server Administration, Data Storage Technologies, Cloud Computing, Servers, System Configuration, Technical Support and Services, Virtualization, User Accounts

      4.8
      Rating, 4.8 out of 5 stars
      ·
      26K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Data Analysis with R Programming

      Skills you'll gain: Rmarkdown, Ggplot2, R Programming, Data Analysis, Tidyverse (R Package), Statistical Programming, Data Visualization Software, Data Cleansing, Data Manipulation, Exploratory Data Analysis, Data Import/Export, Package and Software Management, Data Structures

      4.8
      Rating, 4.8 out of 5 stars
      ·
      11K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      P

      Packt

      The Complete Quantum Computing Course for Beginners

      Skills you'll gain: Object Oriented Programming (OOP), Python Programming, Data Structures, Data Manipulation, Computer Programming, Applied Mathematics, Algorithms, Mathematics and Mathematical Modeling, Data Processing, Scripting, Linear Algebra, Probability, Mathematical Modeling, IBM Cloud, Computer Science, Algebra, Software Installation, Probability & Statistics, Theoretical Computer Science, Artificial Intelligence and Machine Learning (AI/ML)

      4.2
      Rating, 4.2 out of 5 stars
      ·
      32 reviews

      Beginner · Specialization · 3 - 6 Months

    • F

      Fractal Analytics

      Quantum Computing For Everyone - An Introduction

      Skills you'll gain: Computer Science, IBM Cloud, Algorithms, Data Ethics, Computational Thinking, Linear Algebra, Emerging Technologies, Cryptography, Physics, Applied Mathematics

      4
      Rating, 4 out of 5 stars
      ·
      66 reviews

      Beginner · Course · 1 - 4 Weeks

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

    • Go and C++: Programming in Two Successor Languages of C: University of California, Santa Cruz
    • IBM & Darden Digital Strategy: University of Virginia Darden School Foundation
    • Cloud Computing Basics (Cloud 101): LearnQuest
    • Introduction to Generative AI Learning Path: Google Cloud
    • DeepLearning.AI TensorFlow Developer: DeepLearning.AI
    • AWS Fundamentals: Amazon Web Services
    • Fundamentals of Computing: Rice University
    • AWS Cloud Technical Essentials: Amazon Web Services
    • System Administration and IT Infrastructure Services: Google
    • Data Analysis with R Programming: Google

    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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