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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

    • B

      Birla Institute of Technology & Science, Pilani

      Introduction to Programming

      Skills you'll gain: Programming Principles, C (Programming Language), Computer Hardware, Computer Programming, Computer Architecture, Computational Thinking, Data Structures, Algorithms, File Management, Operating Systems, Program Development, Debugging

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      50 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Pennsylvania

      A Crash Course in Causality: Inferring Causal Effects from Observational Data

      Skills you'll gain: R Programming, Statistical Analysis, Statistical Methods, Statistical Software, Statistical Modeling, Statistical Inference, Data Analysis, Probability & Statistics, Regression Analysis, Research Design, Graph Theory

      4.7
      Rating, 4.7 out of 5 stars
      ·
      564 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Introduction to Statistics & Data Analysis in Public Health

      Skills you'll gain: Analytical Skills, Sampling (Statistics), Statistical Hypothesis Testing, Data Literacy, Data Analysis, Statistical Software, R Programming, Statistics, Public Health, Descriptive Statistics, Probability Distribution, Data Import/Export

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.5K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      A

      Amazon Web Services

      Architecting Solutions on AWS

      Skills you'll gain: Serverless Computing, AWS Identity and Access Management (IAM), Event-Driven Programming, Solution Architecture, Cloud Computing Architecture, Amazon Web Services, API Gateway, Hybrid Cloud Computing, Multi-Tenant Cloud Environments, Information Technology Architecture, Cloud Computing, Performance Tuning, Amazon DynamoDB, Amazon S3, Cloud Security, Amazon CloudWatch, AWS Kinesis, Containerization

      4.8
      Rating, 4.8 out of 5 stars
      ·
      500 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      N

      New York University

      Machine Learning and Reinforcement Learning in Finance

      Skills you'll gain: Supervised Learning, Reinforcement Learning, Applied Machine Learning, Machine Learning, Statistical Methods, Dimensionality Reduction, Unsupervised Learning, Machine Learning Algorithms, Artificial Neural Networks, Decision Tree Learning, Predictive Modeling, Financial Trading, Financial Market, Derivatives, Scikit Learn (Machine Learning Library), Markov Model, Regression Analysis, Deep Learning, Market Liquidity, Financial Services

      3.7
      Rating, 3.7 out of 5 stars
      ·
      814 reviews

      Intermediate · Specialization · 3 - 6 Months

    • E

      Eindhoven University of Technology

      Improving your statistical inferences

      Skills you'll gain: Statistical Inference, Scientific Methods, Statistical Hypothesis Testing, Quantitative Research, Bayesian Statistics, Statistical Analysis, Statistical Methods, Probability & Statistics, Sample Size Determination, Research, Data Collection, R Programming, Data Sharing, Probability Distribution

      4.9
      Rating, 4.9 out of 5 stars
      ·
      796 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      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

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      API Design and Fundamentals of Google Cloud's Apigee API Platform

      Skills you'll gain: API Design, Restful API, API Gateway, Application Programming Interface (API), Cloud API, Application Lifecycle Management, Proxy Servers, Software Design Documents, Software Documentation, Authentications

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.4K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Microsoft Full-Stack Developer

      Skills you'll gain: CI/CD, GitHub, C# (Programming Language), HTML and CSS, Load Balancing, Continuous Integration, Git (Version Control System), Role-Based Access Control (RBAC), Scalability, Object Oriented Programming (OOP), Authentications, ASP.NET, Full-Stack Web Development, Web Development, Debugging, SQL, Application Deployment, Microsoft Azure, Microsoft Copilot, Graph Theory

      4.4
      Rating, 4.4 out of 5 stars
      ·
      152 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado System

      Computational Thinking with Beginning C Programming

      Skills you'll gain: Computational Thinking, Data Collection, Simulations, Data Analysis, Microsoft Visual Studio, C (Programming Language), Statistical Analysis, Automation, Program Development, Data Structures, Programming Principles, Algorithms, Computer Programming, Development Environment, Descriptive Statistics, Problem Management, File Management, Distributed Computing, Debugging, Data Storage

      4.6
      Rating, 4.6 out of 5 stars
      ·
      432 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      Status: AI skills
      AI skills
      G

      Google Cloud

      Google Cloud Data Analytics

      Skills you'll gain: Data Lakes, Data Storytelling, Data Governance, Data Presentation, Data Architecture, Data Pipelines, Data Visualization Software, Dashboard, Data Management, Cloud Infrastructure, Generative AI, Data Cleansing, Cloud Storage, Data Transformation, Cloud Computing, Google Cloud Platform, Database Management, Data Ethics, Data Analysis, Analytics

      4.4
      Rating, 4.4 out of 5 stars
      ·
      172 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Reproducible Research

      Skills you'll gain: Rmarkdown, Knitr, Data Sharing, Statistical Reporting, Data Analysis, Statistical Analysis, Data Validation, R Programming, Verification And Validation, Technical Documentation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.2K reviews

      Mixed · Course · 1 - 4 Weeks

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

    • Introduction to Programming: Birla Institute of Technology & Science, Pilani
    • A Crash Course in Causality: Inferring Causal Effects from Observational Data: University of Pennsylvania
    • Introduction to Statistics & Data Analysis in Public Health: Imperial College London
    • Architecting Solutions on AWS: Amazon Web Services
    • Machine Learning and Reinforcement Learning in Finance: New York University
    • Improving your statistical inferences: Eindhoven University of Technology
    • Managing Big Data in Clusters and Cloud Storage: Cloudera
    • API Design and Fundamentals of Google Cloud's Apigee API Platform: Google Cloud
    • Microsoft Full-Stack Developer: Microsoft
    • Computational Thinking with Beginning C Programming: University of Colorado System

    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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