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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
      I

      Imperial College London

      Statistical Analysis with R for Public Health

      Skills you'll gain: Analytical Skills, Correlation Analysis, Regression Analysis, Sampling (Statistics), Statistical Hypothesis Testing, Data Literacy, Data Analysis, R Programming, Descriptive Statistics, Statistical Software, Biostatistics, Exploratory Data Analysis, Statistical Analysis, Statistical Programming, Statistics, Statistical Methods, Public Health, Probability & Statistics, Epidemiology, Statistical Modeling

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

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Illinois Urbana-Champaign

      Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud

      Skills you'll gain: Big Data, Apache Spark, Data Storage Technologies, Apache Hadoop, Distributed Computing, Data Storage, Data Processing, NoSQL, Apache Kafka, Real Time Data, Cloud Computing, Databases, Analytics, Deep Learning, Scalability, Machine Learning Algorithms, Graph Theory, Live Streaming

      4.3
      Rating, 4.3 out of 5 stars
      ·
      342 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      R

      Rice University

      Algorithmic Thinking (Part 1)

      Skills you'll gain: Graph Theory, Algorithms, Computational Thinking, Data Analysis, Data Structures, Theoretical Computer Science, Network Analysis, Analysis, Python Programming, Computer Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      382 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      Interactive Brokers

      Practical Guide to Trading

      Skills you'll gain: Derivatives, Equities, Futures Exchange, Risk Analysis, Financial Trading, International Finance, Investments, Securities Trading, Financial Market, Risk Management, Financial Statement Analysis, Financial Analysis, Market Analysis, Analysis, Capital Markets, Tax, Balance Sheet, Financial Regulations, Market Data, Technical Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      755 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Decentralized Finance (DeFi): The Future of Finance

      Skills you'll gain: Blockchain, Loans, FinTech, Lending and Underwriting, Cyber Risk, Operational Risk, Scalability, Security Testing, Regulatory Compliance, Interoperability, Commercial Lending, Payment Systems, General Lending, Risk Management, Derivatives, Key Management, Cryptography, Emerging Technologies, Financial Regulations, Digital Assets

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    • A

      Atlassian

      Version Control with Git

      Skills you'll gain: Git (Version Control System), Version Control, GitHub, Bitbucket, Software Configuration Management, Command-Line Interface, Code Review, Collaborative Software, Graphical Tools

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Developing APIs with Google Cloud's Apigee API Platform

      Skills you'll gain: OAuth, API Design, Restful API, API Gateway, Application Programming Interface (API), Cloud API, Continuous Deployment, CI/CD, Application Deployment, Google Cloud Platform, Application Lifecycle Management, Security Controls, Proxy Servers, Continuous Integration, Application Security, Software Design Documents, Middleware, Software Documentation, Network Security, Application Performance Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Generative AI Engineering with LLMs

      Skills you'll gain: Prompt Engineering, Large Language Modeling, Generative AI, Natural Language Processing, PyTorch (Machine Learning Library), Generative AI Agents, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Text Mining, Artificial Neural Networks, Deep Learning, Application Development, Artificial Intelligence, Feature Engineering, Document Management, Machine Learning Methods, Data Processing, Performance Tuning, Reinforcement Learning, Unstructured Data

      4.5
      Rating, 4.5 out of 5 stars
      ·
      438 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Reliable Google Cloud Infrastructure: Design and Process

      Skills you'll gain: Application Deployment, Cloud Infrastructure, CI/CD, Cloud Security, Service Level Agreement, Microservices, Service Level, Google Cloud Platform, Network Architecture, API Design, Site Reliability Engineering, Cloud Computing Architecture, Kubernetes, Restful API, Cloud Storage, Cloud Applications, Key Performance Indicators (KPIs), DevOps, Data Storage, System Design and Implementation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.2K reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      PostgreSQL for Everybody

      Skills you'll gain: Stored Procedure, Database Design, SQL, Relational Databases, NoSQL, PostgreSQL, Database Architecture and Administration, Database Theory, Database Management Systems, Data Modeling, JSON, Scalability, Database Management, Query Languages, Cloud Applications, Data Manipulation, Text Mining, Databases, Data Integrity, Data Import/Export

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.3K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Elastic Google Cloud Infrastructure: Scaling and Automation

      Skills you'll gain: Google Cloud Platform, Cloud Infrastructure, Load Balancing, Infrastructure as Code (IaC), Cloud Computing, Managed Services, Solution Architecture, IT Automation, Virtual Machines, Network Infrastructure, Virtual Private Networks (VPN), Scalability

      4.7
      Rating, 4.7 out of 5 stars
      ·
      9.2K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      R

      Rice University

      Algorithmic Thinking (Part 2)

      Skills you'll gain: Computational Thinking, Algorithms, Bioinformatics, Data Structures, Big Data, Python Programming, Data Analysis, Machine Learning Algorithms, Unsupervised Learning, Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      216 reviews

      Intermediate · Course · 1 - 4 Weeks

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

    • Statistical Analysis with R for Public Health: Imperial College London
    • Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud: University of Illinois Urbana-Champaign
    • Algorithmic Thinking (Part 1): Rice University
    • Practical Guide to Trading: Interactive Brokers
    • Decentralized Finance (DeFi): The Future of Finance: Duke University
    • Version Control with Git: Atlassian
    • Developing APIs with Google Cloud's Apigee API Platform: Google Cloud
    • Generative AI Engineering with LLMs: IBM
    • Reliable Google Cloud Infrastructure: Design and Process: Google Cloud
    • PostgreSQL for Everybody: University of Michigan

    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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