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Autor Tópico: Data Science with R - Beginners  (Lida 370 vezes)

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Data Science with R - Beginners
« em: 26 de Agosto de 2020, 14:34 »

Data Science with R - Beginners
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 44100 Hz, 2ch | Size: 1.77 GB
Genre: eLearning Video | Duration: 56 lectures (5 hour, 47 mins) | Language: English
 This training is an introduction to the concept of Data science and its application using R programming language

What you'll learn

    Learn R programming, Reproducible Analysis and Data Manipulation
    Master data visualization, Learn working with Large Datasets, Supervised Learning and Unsupervised Learning
    Learn Object oriented Programming, start building an R package. Know more on Testing and Package and checking Version Control and Profiling and Optimizing

Requirements

    No prior knowledge of machine learning required
    Basic knowledge of R

Description

This training is an introduction to the concept of Data science domain and its application using R programming language. The web is full of apps that are driven by data. All the e-commerce apps and websites are based on data in the complete sense. There is database behind a web front end and middleware that talks to a number of other databases and data services. But the mere use of data is not what comprises of data science. A data application gets its value from data and in the process creates value for itself. This means that data science enables the creation of products that are based on data. The tutorials will include the following;

    Introduction to R programming

    Reproducible Analysis

    Data Manipulation

    Visualizing Data

    Working with Large Datasets

    Supervised Learning

    Unsupervised Learning

    In depth R programming

    Object oriented Programming

    Building an R package

    Testing and Package Checking

    Version Control

    Profiling and Optimizing

 
Who this course is for:

    Anyone who wants to learn about data and analytics
    Data Engineers
    Analysts
    Architects
    Software Engineers
    IT operations
    Technical managers

Download link:
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