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Bundle Multi (2-in-1) - R Programming
Uplatz

Self-paced videos, Lifetime access, Study material, Certification prep, Technical support, Course Completion Certificate

Summary

Price
£200 inc VAT
Or £66.67/mo. for 3 months...
Study method
Online, On Demand
Duration
29.4 hours · Self-paced
Qualification
No formal qualification
Certificates
  • Reed Courses Certificate of Completion - Free
  • Uplatz Certificate of Completion - Free

Overview

Uplatz offers this comprehensive 2-in-1 multi bundle course on R Programming. It is a self-paced course with video lectures. You will be awarded Course Completion Certificate at the end of the course.

R is a programming language for statistical computing and graphics supported by the R Core Team and the R Foundation for Statistical Computing. Created by statisticians Ross Ihaka and Robert Gentleman, R is used among data miners, bioinformaticians and statisticians for data analysis and developing statistical software. Users have created packages to augment the functions of the R language. R is a language and environment for statistical computing and graphics.

R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.

One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.

R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes

an effective data handling and storage facility,
a suite of operators for calculations on arrays, in particular matrices,
a large, coherent, integrated collection of intermediate tools for data analysis,
graphical facilities for data analysis and display either on-screen or on hardcopy, and
a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.

In this R Programming course by Uplatz you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.

Certificates

Reed Courses Certificate of Completion

Digital certificate - Included

Will be downloadable when all lectures have been completed.

Uplatz Certificate of Completion

Digital certificate - Included

Course Completion Certificate by Uplatz

Curriculum

2
sections
64
lectures
29h 26m
total

    • 1: Introduction to R Language 14:34
    • 2: R Installation Preview 08:50
    • 3: R Data Structures 07:10
    • 4: R Data Types - part 1 04:41
    • 5: R Data Types - part 2 19:10
    • 6: R Packages Preview 11:25
    • 7: Simple Calculator using R 22:33
    • 8: R as a Calculator 18:48
    • 9: Condition Statements in R - part 1 28:48
    • 10: Condition Statements in R - part 2 16:15
    • 11: Looping in R 25:02
    • 12: Repeat Statement in R 15:32
    • 13: Sum of N Natural Numbers 07:17
    • 14: Episode 12 - Sum Recursion 05:52
    • 15: Switch Statement in R 33:57
    • 16: Data Pre-processing 1:01:55
    • 17: Functions in R 37:44
    • 18: Factors in R 37:01
    • 19: Data Frames in R 37:47
    • 20: Merging Data Frame in R 20:37
    • 21: Data Reshaping - part 1 25:10
    • 22: Data Reshaping - part 2 23:49
    • 23: Data Reshaping - part 3 10:08
    • 24: R Math built-in Functions 14:32
    • 25: Melting and Casting in R 11:35

    • 26: Introduction to R Programming 16:58
    • 27: Setup of R Language 24:13
    • 28: Variables and Data Types - part 1 31:36
    • 29: Variables and Data Types - part 2 29:16
    • 30: Input-Output Features - part 1 38:05
    • 31: Input-Output Features - part 2 25:43
    • 32: Operators in R - part 1 34:16
    • 33: Operators in R - part 2 29:19
    • 34: Vectors - Data Structure - part 1 32:29
    • 35: Vectors - Data Structure - part 2 30:29
    • 36: List - Data Structure - part 1 33:47
    • 37: List - Data Structure - part 2 29:10
    • 38: Matrix - Data Structure - part 1 43:57
    • 39: Matrix - Data Structure - part 2 34:52
    • 40: Arrays - Data Structure - part 1 31:56
    • 41: Arrays - Data Structure - part 2 38:35
    • 42: Data Frame - Data Structure - part 1 43:06
    • 43: Data Frame - Data Structure - part 2 33:59
    • 44: Data Frame - Data Structure - part 3 50:54
    • 45: Factors - Data Structure - part 1 34:09
    • 46: Factors - Data Structure - part 2 17:14
    • 47: Decision Making in R - part 1 32:52
    • 48: Decision Making in R - part 2 45:55
    • 49: Loops in R - part 1 28:28
    • 50: Loops in R - part 2 32:03
    • 51: Loops in R - part 3 25:29
    • 52: Functions in R - part 1 37:42
    • 53: Functions in R - part 2 34:11
    • 54: Strings in R - part 1 25:18
    • 55: Strings in R - part 2 26:51
    • 56: Packages in R 35:17
    • 57: Data and File Management in R - part 1 32:45
    • 58: Data and File Management in R - part 2 23:18
    • 59: Line chart in R 33:06
    • 60: Scatter plot in R Preview 26:38
    • 61: Pie chart in R 33:32
    • 62: Bar chart in R 39:32
    • 63: Histogram in R 26:34
    • 64: Boxplots in R 21:49

Course media

Description

R programming is a language and environment for statistical computing and graphics. It was developed by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and was first released in 1995. R provides a wide variety of statistical and graphical techniques, and it is widely used by statisticians, data scientists, and researchers for data analysis, visualization, and modeling.

Here are some key features of R programming:

  1. Data Manipulation: R provides extensive tools for data manipulation, including functions for filtering, sorting, aggregating, merging, and reshaping data.

  2. Statistical Analysis: R offers a rich set of statistical functions and packages for performing various statistical analyses, such as hypothesis testing, regression analysis, time series analysis, and clustering.

  3. Data Visualization: R has powerful graphical capabilities, allowing users to create a wide range of high-quality data visualizations, including scatter plots, bar plots, histograms, line plots, and more. The "ggplot2" package is particularly popular for creating sophisticated and customizable plots.

  4. Extensibility: R is highly extensible, allowing users to create their own functions and packages to extend its capabilities. There is a vast collection of packages available on the Comprehensive R Archive Network (CRAN) and other repositories, covering diverse domains and analysis techniques.

  5. Reproducible Research: R facilitates reproducible research by providing tools for documenting code, generating reports, and creating interactive documents. Packages like R Markdown and knitr enable the integration of code, analysis, and results in a single document.

  6. Integration: R can be easily integrated with other programming languages like Python, Java, and C++, allowing users to leverage existing libraries and tools for specific tasks. Additionally, R has connectors to various databases, making it convenient for data extraction and manipulation.

Who is this course for?

Everyone

Requirements

Passion & determination to achieve big goals in life!

Career path

  • Software Engineer
  • R Programmer
  • Data Scientist
  • Data Analyst
  • Machine Learning Engineer
  • Data Consultant
  • Software Developer
  • Business Analyst
  • Financial Analyst

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Legal information

This course is advertised on Reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.

FAQs

Study method describes the format in which the course will be delivered. At Reed Courses, courses are delivered in a number of ways, including online courses, where the course content can be accessed online remotely, and classroom courses, where courses are delivered in person at a classroom venue.

CPD stands for Continuing Professional Development. If you work in certain professions or for certain companies, your employer may require you to complete a number of CPD hours or points, per year. You can find a range of CPD courses on Reed Courses, many of which can be completed online.

A regulated qualification is delivered by a learning institution which is regulated by a government body. In England, the government body which regulates courses is Ofqual. Ofqual regulated qualifications sit on the Regulated Qualifications Framework (RQF), which can help students understand how different qualifications in different fields compare to each other. The framework also helps students to understand what qualifications they need to progress towards a higher learning goal, such as a university degree or equivalent higher education award.

An endorsed course is a skills based course which has been checked over and approved by an independent awarding body. Endorsed courses are not regulated so do not result in a qualification - however, the student can usually purchase a certificate showing the awarding body's logo if they wish. Certain awarding bodies - such as Quality Licence Scheme and TQUK - have developed endorsement schemes as a way to help students select the best skills based courses for them.
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