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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
      J

      Johns Hopkins University

      Introduction to Concurrent Programming with GPUs

      Skills you'll gain: C and C++, System Programming, Computer Hardware, Computer Architecture, Software Development, Computer Programming, Algorithms, Python Programming, Development Environment, Debugging

      2.6
      Rating, 2.6 out of 5 stars
      ·
      111 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Introduction to Genomic Technologies

      Skills you'll gain: Bioinformatics, Data Science, Molecular Biology, Data Analysis, Programming Principles, Computer Science, Statistical Analysis, Computational Thinking, Big Data, Software Engineering, Algorithms, Biology

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.7K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Introduction to Big Data

      Skills you'll gain: Big Data, Apache Hadoop, Scalability, Data Processing, Data Science, Distributed Computing, Unstructured Data, Data Analysis, Real Time Data, Data Storage

      4.6
      Rating, 4.6 out of 5 stars
      ·
      11K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Introduction to Data Engineering

      Skills you'll gain: Data Store, Extract, Transform, Load, Data Architecture, Data Pipelines, Big Data, Data Warehousing, Data Governance, Apache Hadoop, Relational Databases, Apache Spark, Data Lakes, Databases, SQL, NoSQL, Data Security

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.2K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Introduction to Large Language Models

      Skills you'll gain: Large Language Modeling, Prompt Engineering, Generative AI, Google Cloud Platform, Artificial Intelligence and Machine Learning (AI/ML)

      4.4
      Rating, 4.4 out of 5 stars
      ·
      988 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      D
      A

      Multiple educators

      DeepLearning.AI Data Engineering

      Skills you'll gain: Apache Airflow, Data Modeling, Data Pipelines, Data Storage, Data Storage Technologies, Data Architecture, Data Transformation, Requirements Analysis, Data Processing, Data Warehousing, Query Languages, Apache Hadoop, Extract, Transform, Load, Data Lakes, Amazon Web Services, Apache Spark, Database Systems, Data Integration, Infrastructure as Code (IaC), Terraform

      4.8
      Rating, 4.8 out of 5 stars
      ·
      449 reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      TensorFlow: Advanced Techniques

      Skills you'll gain: Generative AI, Tensorflow, Computer Vision, Image Analysis, Deep Learning, Keras (Neural Network Library), Applied Machine Learning, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Feature Engineering, Distributed Computing, Computer Graphics, Unsupervised Learning, Network Model, Visualization (Computer Graphics), Network Architecture, Performance Tuning, Machine Learning Methods, API Design, Object Oriented Programming (OOP)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.7K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Mathematics for Machine Learning: Multivariate Calculus

      Skills you'll gain: Regression Analysis, Calculus, Machine Learning Methods, Advanced Mathematics, Statistical Analysis, Linear Algebra, Artificial Neural Networks, Python Programming, Derivatives, Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.7K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      AI for Medical Diagnosis

      Skills you'll gain: Image Analysis, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Data Processing, Applied Machine Learning, Medical Imaging, Machine Learning Algorithms, Computer Vision, Deep Learning, Natural Language Processing, Medical Science and Research, Radiology, Artificial Neural Networks, Probability & Statistics

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

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Essential Google Cloud Infrastructure: Core Services

      Skills you'll gain: Identity and Access Management, Google Cloud Platform, Cloud Infrastructure, Infrastructure As A Service (IaaS), Cloud Computing, Cloud Services, Data Storage Technologies, Cloud Storage, Cloud Security, Databases, System Monitoring

      4.7
      Rating, 4.7 out of 5 stars
      ·
      11K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Illinois Urbana-Champaign

      Cloud Computing Concepts: Part 2

      Skills you'll gain: Distributed Computing, File Systems, Cloud Computing, Operating Systems, Transaction Processing, Network Security, Data Centers, Authorization (Computing), Apache Hadoop, Data Store, Authentications, Cryptography, NoSQL, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      319 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      AI Product Management

      Skills you'll gain: Deep Learning, MLOps (Machine Learning Operations), Data Ethics, Data Management, Unsupervised Learning, Human Computer Interaction, User Experience Design, Classification And Regression Tree (CART), Data Quality, Human Centered Design, Machine Learning, Human Factors, Regression Analysis, Technical Management, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Artificial Neural Networks, Decision Tree Learning, Data Processing, Personally Identifiable Information

      4.7
      Rating, 4.7 out of 5 stars
      ·
      791 reviews

      Beginner · Specialization · 3 - 6 Months

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

    • Introduction to Concurrent Programming with GPUs: Johns Hopkins University
    • Introduction to Genomic Technologies: Johns Hopkins University
    • Introduction to Big Data: University of California San Diego
    • Introduction to Data Engineering: IBM
    • Introduction to Large Language Models: Google Cloud
    • DeepLearning.AI Data Engineering: DeepLearning.AI
    • TensorFlow: Advanced Techniques: DeepLearning.AI
    • Mathematics for Machine Learning: Multivariate Calculus: Imperial College London
    • AI for Medical Diagnosis: DeepLearning.AI
    • Essential Google Cloud Infrastructure: Core Services: Google Cloud

    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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