Udemy - Data Science And Machine Learning With R - A Complete Masterc

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[ WebToolTip.com ] Udemy - Data Science And Machine Learning With R - A Complete Masterc
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here !
    • 1 - Data science and ml with r course overview.mp4 (12.0 MB)
    • 10 - R tidyverse.mp4 (57.6 MB)
    • 11 - R Studio.mp4 (19.7 MB)
    • 12 - R Resources.mp4 (13.7 MB)
    • 13 - Data types and structures section intro.mp4 (25.0 MB)
    • 14 - Basic types.mp4 (18.1 MB)
    • 15 - Vectors part one.mp4 (17.4 MB)
    • 16 - Vectors part two.mp4 (14.5 MB)
    • 17 - Vectors missing values.mp4 (18.1 MB)
    • 18 - Vectors coercion.mp4 (10.2 MB)
    • 19 - Vectors naming.mp4 (11.7 MB)
    • 2 - What is data science.mp4 (83.0 MB)
    • 20 - Vectors misc.mp4 (13.6 MB)
    • 21 - Creating matrices.mp4 (10.7 MB)
    • 22 - Working with lists.mp4 (20.0 MB)
    • 23 - Introduction to data frames.mp4 (18.7 MB)
    • 24 - Creating data frames.mp4 (32.4 MB)
    • 25 - Data frames helper functions.mp4 (27.1 MB)
    • 26 - Data frames tibbles.mp4 (19.7 MB)
    • 27 - Intermediate r section intro.mp4 (44.4 MB)
    • 28 - Relational operators.mp4 (23.3 MB)
    • 29 - Logical operators.mp4 (22.6 MB)
    • 3 - Machine learning overview.mp4 (38.9 MB)
    • 30 - Conditional statements.mp4 (16.8 MB)
    • 31 - Loops.mp4 (15.2 MB)
    • 32 - Functions.mp4 (18.7 MB)
    • 33 - Packages.mp4 (23.6 MB)
    • 34 - Factors.mp4 (13.1 MB)
    • 35 - Dates and times.mp4 (17.7 MB)
    • 36 - Functional programming.mp4 (12.6 MB)
    • 37 - Data importexport.mp4 (18.6 MB)
    • 38 - Databases.mp4 (16.7 MB)
    • 39 - Data manipulation in r section intro.mp4 (44.0 MB)
    • 4 - Data science and machine learning marketplace.mp4 (17.5 MB)
    • 40 - Tidy data.mp4 (52.7 MB)
    • 41 - The pipe operator.mp4 (21.6 MB)
    • 42 - The filter verb.mp4 (12.3 MB)
    • 43 - The select verb.mp4 (13.3 MB)
    • 44 - The mutate verb.mp4 (22.6 MB)
    • 45 - The arrange verb.mp4 (30.2 MB)
    • 46 - The summarize verb.mp4 (20.6 MB)
    • 47 - Data pivoting.mp4 (20.4 MB)
    • 48 - String manipulation.mp4 (33.4 MB)
    • 49 - Web scraping.mp4 (12.3 MB)
    • 5 - Dsand ml job opportunities.mp4 (12.3 MB)
    • 50 - Json parsing.mp4 (70.6 MB)
    • 51 - Data visualization in r intro.mp4 (43.9 MB)
    • 52 - Aesthetics mappings.mp4 (19.8 MB)
    • 53 - Single variable plots.mp4 (13.9 MB)
    • 54 - Two variable plots.mp4 (19.2 MB)
    • 55 - Fcets layering and coordinate systems.mp4 (29.7 MB)
    • 56 - Styling and saving.mp4 (16.5 MB)
    • 57 - Intro to r markdown.mp4 (20.0 MB)
    • 58 - Intro to r shiny.mp4 (36.1 MB)
    • 59 - A basic webapp.mp4 (15.7 MB)
    • 6 - Data science job roles.mp4 (15.3 MB)
    • 60 - Other webapp examples.mp4 (25.8 MB)
    • 61 - Intro to machine learning Part 1.mp4 (43.8 MB)
    • 62 - Intro to machine learning Part 2.mp4 (43.4 MB)
    • 63 - Data preprocessing Intro.mp4 (44.3 MB)
    • 64 - Data preprocessing.mp4 (69.7 MB)
    • 65 - Linear regression a simple model Intro.mp4 (43.3 MB)
    • 66 - Linear regression a simple model.mp4 (22.8 MB)
    • 67 - Exploratory data analysis intro.mp4 (35.9 MB)
    • 68 - Hands on exploratory data analysis.mp4 (62.5 MB)
    • 69 - Linear regression a real model intro.mp4 (43.6 MB)
    • 7 - Getting started with r.mp4 (68.4 MB)
    • 70 - Llinear regression a real model.mp4 (18.3 MB)
    • 71 - Logistic regression intro.mp4 (43.9 MB)
    • 72 - Logistic regression in r.mp4 (24.6 MB)
    • 73 - Starting a data science career.mp4 (10.7 MB)
    • 74 - Creating a data science resume.mp4 (13.7 MB)
    • 75 - Getting started with freelancing.mp4 (17.8 MB)
    • 8 - R basics.mp4 (20.3 MB)
    • 9 - R files.mp4 (19.2 MB)
    • Bonus Resources.txt (0.1 KB)

Description

Data Science And Machine Learning With R: A Complete Masterc

https://WebToolTip.com

Published 2/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.96 GB | Duration: 5h 51m

Learn Data Science, Data Analysis, and Machine Learning with R. Master Data Manipulation, Visualization, and Predictive

What you'll learn
Master R Programming – Learn the fundamentals of R, including data structures, functions, and packages for efficient data analysis.
Perform Data Manipulation and Visualization – Clean, transform, and visualize data using powerful R libraries like dplyr and ggplot2.
Build Machine Learning Models – Implement regression and classification models, perform data preprocessing, and conduct exploratory data analysis (EDA).
Develop Real-World Data Science Skills – Work with databases, web scraping, JSON parsing, and create interactive dashboards with R Shiny.

Requirements
No prior experience in Data Science or Machine Learning is required. This course is designed for beginners and professionals alike.
Basic computer skills and familiarity with using software applications.
A willingness to learn and explore R programming for data analysis.
Access to a computer with an internet connection to install R and RStudio (guidance provided in the course).



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Udemy - Data Science And Machine Learning With R - A Complete Masterc

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