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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

    • U

      University of California San Diego

      Finding Hidden Messages in DNA (Bioinformatics I)

      Skills you'll gain: Bioinformatics, Molecular Biology, Data Analysis, Computational Thinking, Biochemistry, Biology, Life Sciences, Algorithms, Probability & Statistics

      4.3
      Rating, 4.3 out of 5 stars
      ·
      1K reviews

      Intermediate · Course · 1 - 3 Months

    • P

      Palo Alto Networks

      Palo Alto Networks Cybersecurity

      Skills you'll gain: Network Security, Cloud Security, DevSecOps, Cybersecurity, Cloud-Native Computing, General Networking, TCP/IP, Zero Trust Network Access, Cryptography, Endpoint Security, Cyber Threat Intelligence, Cloud Computing Architecture, Malware Protection, Firewall, Cloud Computing, Encryption, Network Infrastructure, Security Information and Event Management (SIEM), Application Security, Infrastructure Security

      4.6
      Rating, 4.6 out of 5 stars
      ·
      773 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • G

      Google Cloud

      Build, Train and Deploy ML Models with Keras on Google Cloud

      Skills you'll gain: Tensorflow, Keras (Neural Network Library), Google Cloud Platform, Data Pipelines, MLOps (Machine Learning Operations), Application Deployment, Deep Learning, Artificial Neural Networks, Data Processing, Scalability, Applied Machine Learning, Machine Learning, Data Transformation

      4.4
      Rating, 4.4 out of 5 stars
      ·
      2.8K reviews

      Intermediate · Course · 1 - 3 Months

    • C

      ConsenSys Academy

      Blockchain: Foundations and Use Cases

      Skills you'll gain: Blockchain, Cryptography, Interoperability, FinTech, Emerging Technologies, Ledgers (Accounting), Business Modeling, Distributed Computing, Digital Assets, Data Sharing, Data Integrity, Transaction Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      842 reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      Introduction to Neural Networks and PyTorch

      Skills you'll gain: PyTorch (Machine Learning Library), Artificial Neural Networks, Deep Learning, Predictive Modeling, Probability & Statistics, Machine Learning, Regression Analysis, Data Manipulation, Linear Algebra

      4.4
      Rating, 4.4 out of 5 stars
      ·
      1.8K reviews

      Intermediate · Course · 1 - 3 Months

    • D

      Duke University

      Linear Regression and Modeling

      Skills you'll gain: Regression Analysis, Data Analysis Software, Statistical Analysis, R Programming, Statistical Modeling, Statistical Inference, Correlation Analysis, Statistical Methods, Exploratory Data Analysis, Mathematical Modeling, Predictive Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.8K reviews

      Beginner · Course · 1 - 4 Weeks

    • L

      LearnQuest

      Introduction to Java

      Skills you'll gain: Eclipse (Software), Java, Java Programming, Integrated Development Environments, Development Environment, Software Installation, Computer Programming, Programming Principles, Program Development, Object Oriented Programming (OOP)

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.1K reviews

      Beginner · Course · 1 - 4 Weeks

    • D

      Duke University

      Machine Learning Foundations for Product Managers

      Skills you'll gain: Deep Learning, Unsupervised Learning, Classification And Regression Tree (CART), Machine Learning, Regression Analysis, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Decision Tree Learning, Computer Vision, Supervised Learning, Natural Language Processing, Random Forest Algorithm, Algorithms, Performance Metric

      4.7
      Rating, 4.7 out of 5 stars
      ·
      550 reviews

      Intermediate · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      AI For Everyone (すべての人のためのAIリテラシー講座)

      Skills you'll gain: Artificial Intelligence, Artificial Neural Networks, Digital Transformation, Deep Learning, Team Building, Technical Management, Applied Machine Learning, Machine Learning, Data Ethics, Data Science

      4.7
      Rating, 4.7 out of 5 stars
      ·
      282 reviews

      Beginner · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Introduction to Data Engineering

      Skills you'll gain: Data Pipelines, Data Architecture, Requirements Analysis, Amazon Web Services, Data Warehousing, Data Processing, System Requirements, Extract, Transform, Load, Performance Tuning, Security Controls, Cloud Computing, Data Transformation, Scalability

      4.8
      Rating, 4.8 out of 5 stars
      ·
      370 reviews

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Introduction to Trading, Machine Learning & GCP

      Skills you'll gain: Machine Learning, Google Cloud Platform, Applied Machine Learning, Supervised Learning, Time Series Analysis and Forecasting, Financial Trading, Deep Learning, Statistical Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Securities Trading, Technical Analysis, Financial Forecasting, Quantitative Research, Financial Modeling, Forecasting, Regression Analysis

      4
      Rating, 4 out of 5 stars
      ·
      874 reviews

      Intermediate · Course · 1 - 4 Weeks

    • C

      Cloudera

      Managing Big Data in Clusters and Cloud Storage

      Skills you'll gain: Apache Hive, Database Management, SQL, Big Data, Databases, Data Management, Amazon S3, Apache Hadoop, Data Storage, Cloud Storage, Performance Tuning, Command-Line Interface

      4.7
      Rating, 4.7 out of 5 stars
      ·
      297 reviews

      Beginner · Course · 1 - 3 Months

    Parallel Computing learners also search

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    1…242526…284

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

    • Finding Hidden Messages in DNA (Bioinformatics I): University of California San Diego
    • Palo Alto Networks Cybersecurity: Palo Alto Networks
    • Build, Train and Deploy ML Models with Keras on Google Cloud: Google Cloud
    • Blockchain: Foundations and Use Cases: ConsenSys Academy
    • Introduction to Neural Networks and PyTorch: IBM
    • Linear Regression and Modeling : Duke University
    • Introduction to Java: LearnQuest
    • Machine Learning Foundations for Product Managers: Duke University
    • AI For Everyone (すべての人のためのAIリテラシー講座): DeepLearning.AI
    • Introduction to Data Engineering: DeepLearning.AI

    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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