Parallel Programming in R

Name: Parallel Programming in R
Brand: Careervira
Price: 149 USD
Availability: InStock
Rating: 5.0 (3 reviews)

DataCamp

(3)

Course Report

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Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

Video Content

4 hours

Course Description

Parallel processing is increasingly important due to the increasing number of data and complex algorithms available to scientists and practitioners. This is expected for packages that use time-consuming methods. This course will teach you R and help you solve important problems such as reproducibility and load balancing.

Highlights

Pedagogy

Top 10 Percentile

Rating & Reviews

Top 30 Percentile

Parameters

Pedagogy

Acquire all major R Programming skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in R Programming, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.

Rating & Reviews

This highly acclaimed course is among the top-rated in R Programming, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in R Programming.

Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Writing Efficient R Code

What You Will Learn

This course covers in detail the tools available in R for parallel computing

This course introduces you to concepts and tools available in R for parallel computing and provides solutions to a few important non-trivial issues in parallel processing like reproducibility, generating random numbers and load balancing

Course Content

Expand all sections

Module 1: Can I Run My Application in Parallel?

Module 2: The parallel Package

Module 3: foreach, future.apply and Load Balancing

Module 4: Random Numbers and Reproducibility

Course Instructors

Hana Sevcikova

Senior Research Scientist, University of Washington

Hana works as a senior research scientist at the University of Washington Center for Statistics and the Social Sciences, in the area of statistical computing. She also works as a data scientist at th...

Course Reviews

Average Rating Based on 3 reviews

5.0

100%