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    • Parallel Computing

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    262 results for "parallel computing"

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      University of Colorado Boulder

      Introduction to High-Performance and Parallel Computing

      Skills you'll gain: Computer Programming, Computer Architecture, Distributed Computing Architecture, Linux, Operating Systems, Software Engineering, Computational Thinking, Computer Programming Tools, Data Analysis, Programming Principles, Software Architecture, Software Testing, Theoretical Computer Science

      3.1

      (67 reviews)

      Beginner · Course · 1-4 Weeks

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      Rice University

      Parallel, Concurrent, and Distributed Programming in Java

      Skills you'll gain: Computer Programming, Theoretical Computer Science, Algorithms, Computer Science, Java Programming, Computational Thinking, Computer Architecture, Distributed Computing Architecture, Mobile Development, Computational Logic, Data Management, Data Structures, Operating Systems, Other Programming Languages, System Programming, Applied Machine Learning, Machine Learning, Programming Principles, Software Architecture, Software Engineering

      4.6

      (1.5k reviews)

      Intermediate · Specialization · 3-6 Months

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      École Polytechnique Fédérale de Lausanne

      Parallel programming

      Skills you'll gain: Computer Programming, Computer Science, Other Programming Languages, Algorithms, Theoretical Computer Science, Data Science, Machine Learning, Machine Learning Algorithms, Scala Programming, Computational Thinking, Data Management

      4.4

      (1.8k reviews)

      Intermediate · Course · 1-4 Weeks

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      Rice University

      Parallel Programming in Java

      Skills you'll gain: Computer Science, Computer Programming, Java Programming, Algorithms, Theoretical Computer Science, Computational Logic, Operating Systems, System Programming, Applied Machine Learning, Computational Thinking, Machine Learning, Mobile Development, Programming Principles, Software Architecture, Software Engineering

      4.6

      (1.2k reviews)

      Intermediate · Course · 1-3 Months

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      Rice University

      Distributed Programming in Java

      Skills you'll gain: Computer Architecture, Computer Programming, Distributed Computing Architecture, Theoretical Computer Science, Computational Thinking, Data Management, Data Structures

      4.6

      (477 reviews)

      Intermediate · Course · 1-3 Months

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      École Polytechnique Fédérale de Lausanne

      Functional Programming in Scala Capstone

      Skills you'll gain: Data Mining, Scala Programming

      4.4

      (538 reviews)

      Mixed · Course · 1-3 Months

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      École Polytechnique Fédérale de Lausanne

      Parallel programming (Scala 2 version)

      Skills you'll gain: Computer Programming, Theoretical Computer Science, Algorithms

      Intermediate · Course · 1-4 Weeks

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      École Polytechnique Fédérale de Lausanne

      Effective Programming in Scala

      Skills you'll gain: Computer Programming, Programming Principles, Scala Programming, Software Engineering, Theoretical Computer Science, Computational Logic, Software Testing

      4.7

      (130 reviews)

      Intermediate · Course · 1-3 Months

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      École Polytechnique Fédérale de Lausanne

      Functional Programming in Scala

      Skills you'll gain: Computer Programming, Other Programming Languages, Computer Science, Scala Programming, Theoretical Computer Science, Apache, Big Data, Data Management, Programming Principles, Algorithms, Computational Thinking, Data Science, Machine Learning, Machine Learning Algorithms, Computational Logic, Computer Programming Tools, Data Analysis, Data Analysis Software, Data Mining, Data Structures, Mathematical Theory & Analysis, Mathematics, SQL

      4.7

      (10.5k reviews)

      Intermediate · Specialization · 3-6 Months

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      Johns Hopkins University

      GPU Programming

      Skills you'll gain: Computer Programming, C++ Programming, Theoretical Computer Science, C Programming Language Family, Computational Thinking, Computer Architecture, Computer Graphic Techniques, Computer Graphics, Distributed Computing Architecture, Python Programming, Statistical Programming, Algorithms, Other Programming Languages, Software Architecture, Software Engineering, Data Science, Linear Algebra, Machine Learning

      2.9

      (25 reviews)

      Intermediate · Specialization · 3-6 Months

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      Free

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      Ludwig-Maximilians-Universität München (LMU)

      Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python

      Skills you'll gain: Mathematics, Differential Equations, Mathematical Theory & Analysis, Applied Mathematics, Calculus, Computational Thinking, Computer Graphic Techniques, Computer Graphics, Computer Programming, Linear Algebra, Operations Research, Research and Design, Strategy and Operations, Theoretical Computer Science

      4.7

      (311 reviews)

      Intermediate · Course · 1-3 Months

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      Free

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      Intel

      Introduction to OpenCL on FPGAs

      Skills you'll gain: Computational Thinking, Computer Programming, Theoretical Computer Science, Computer Architecture, Microarchitecture, Computer Graphic Techniques, Computer Graphics

      4.0

      (104 reviews)

      Beginner · Course · 1-3 Months

    Searches related to parallel computing

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

    • Introduction to High-Performance and Parallel Computing: University of Colorado Boulder
    • Parallel, Concurrent, and Distributed Programming in Java: Rice University
    • Parallel programming: École Polytechnique Fédérale de Lausanne
    • Parallel Programming in Java: Rice University
    • Distributed Programming in Java: Rice University
    • Functional Programming in Scala Capstone: École Polytechnique Fédérale de Lausanne
    • Parallel programming (Scala 2 version): École Polytechnique Fédérale de Lausanne
    • Effective Programming in Scala: École Polytechnique Fédérale de Lausanne
    • Functional Programming in Scala: École Polytechnique Fédérale de Lausanne
    • GPU Programming: Johns Hopkins University

    Skills you can learn in Software Development

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    Google Cloud Platform (18)
    Application Programming Interfaces (17)
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    Problem Solving (14)
    Object-oriented Programming (13)
    Kubernetes (10)
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    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.‎

    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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