Data analysis is crucial to accurately predict the performance of an application. The course begins by getting you started with R, including basic programming and data import, data visualization, pivoting, merging, aggregating, and joins.
DurationData analysis is crucial to accurately predict the performance of an application. The course begins by getting you started with R, including basic programming and data import, data visualization, pivoting, merging, aggregating, and joins.
Once you are comfortable with the basics, you will read ahead and learn all about data visualization and graphics. You will learn data management techniques such as pivots, aggregations, and dealing with missing values.
With this various case studies and examples, this course gives you the knowledge to confidently start your career in the field of data science. This is a hands-on guide that walks you through concepts with examples using built-in R data.
Every topic is enriched with a supporting example that highlights the concept, followed by activities that will gradually build into a full data science project to showcase skills learned. You will perform an end-to-end analysis, starting a data science portfolio.
Audience
This course is for analysts who are looking to grow their data science skills beyond the tools they have used before, such as MS Excel and other statistical tools.
Objectives
The course begins by getting you started with R, including basic programming and data import, data visualization, pivoting, merging, aggregating, and joins. You will learn how to:
Use the basic programming concepts of R such as loading packages, arithmetic functions, data structures, and flow control
Import data to R from various formats, such as CSV, Excel, and SQL
Clean data by handling missing values and standardizing fields
Perform univariate and bivariate analysis using ggplot2
Create statistical summary and advanced plots, such as histograms, scatter plots, box plots, and interaction plots
Apply data management techniques, such as factors, pivots, aggregation, merging, and dealing with missing values, on the example data sets
Contents
Lesson 1: INTRODUCTION TO R
Using R, RStudio, and Installing Useful Packages
Variable Types and Data Structures
Basic Flow Control
Data Import and Export
Getting Help with R
Lesson 2: DATA VISUALIZATION AND GRAPHICS
Creating Base Plots
ggplot2
Interactive Plots
Lesson 3: DATA MANAGEMENT
Factor Variables
Summarizing data
Splitting, Combining, Merging, and Joining Datasets
Global Knowledge is a worldwide leader in IT and technology training, helping individuals and organizations build the skills they need to succeed in an ever-changing world.
With an international network of offices and training facilities, Global Knowledge has the unique flexibility to deliver a broad portfolio of courses on over 100 countries online, in classrooms, and through a worldwide partner network.
Established in 1995, Global Knowledge has over 1000 employees worldwide and enables the success of more than 200,000 tech professionals each year.
In June 2021, Global Knowledge merged with Skillsoft to create the world’s leading corporate learning company.
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The hyper-focused, specialty roles aren’t going anywhere—they’re more necessary than ever—but we also must account for the T-shaped skills. Thus, we train beyond the traditional IT topics and train more people than corporate IT.
Whether you’re managing mission critical technology initiatives, developing your technical talent pipeline or taking IT products and services to market, our innovative and flexible learning solutions equip you for success.
Why Global Knowledge? Impact.
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By providing access to subject matter experts, delivering authorized and industry-leading instruction through multiple delivery formats, we set the stage for your success by reducing skill gaps. You’ll also see impacts in onboarding and employee retention through improved skills and higher job satisfaction.
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Since 1995, we’ve grown to 15 offices and 1,500 employees. Our U.S.-based corporate headquarters is located in Cary, North Carolina (United States). Canadian headquarters are in Toronto, and our Europe, Middle East and Africa headquarters are in Wokingham, UK.
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Between our international locations and online capabilities, we deliver what you need, when and where you need it and to who needs it. And we do it every day.
Our R trainer has many years of experience and has written a number of books on R. This course is very hands-on. This means that there is plenty of time to experiment with what you are being taught, try things out for yourself and ask questions.
R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering etc.) and graphical techniques, and is highly extensible. It is available as free software.
Data Science is an arena of reconstructing unstructured data to a structured model and confer it into knowledge.
It covers the most essential topics you must learn to begin programming with R. With more than two million global users, the R language is rapidly turning into a top programming language specifically in the space of data science as well as statistics.
R is a programming language and software environment that can be used for graphic representation, statistical analysis, and reporting.
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