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Data Science with R - Beginner
Rated 4.0/5 based on 22 Votes customer reviews

Data science with R Training-Beginners

Learn the basics of R programming language and understand its core principles. Create R visualizations that helps in handling and analysing large data sets.

  • 24 hours of Instructor-led classes
  • Beginner level
  • Immersive hands-on training
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Modes of Delivery

Key Features

24 hours of Instructor-led training
Immersive hands-on classes
Understand the basics of R language including core programming principles
Learn to use its inbuilt functions and libraries to create apps and programs for data science
Create R visualizations & programs for analyzing large and complex data
Our R experts will help students in future implementation of the technology

Description

R is every statistician’s first programming choice for data analysis. Its user friendliness, flexibility and robustness have made it very popular for data analysis in the field of academics and research and in the enterprise context too. And if data visualization is what you want then R will get the job done for you. The programs written in R will help you tell stories with your data and turn numbers into useful information.

Zeolearn brings you a comprehensive beginner’s course on Data Science with R that will allow you to master R and use its inbuilt functions and libraries for creating applications and programs for data science. With a perfect blend of theory and practical, you will be able to master the language and ensure that you are competitive and skilled enough to fulfil the growing demand for data scientists. Our industry scale project will also give the hands on skills needed to understand the real world demands of R in data analysis.

What you will learn!

  • Basics of R including functions, vectors, variables and core principles of programming
  • To create R programs that will help discover and interpret relationships in complex information and solve real world problems
  • To  create R visualizations that will help analyse and handle large data sets
  • How to work with statistical, financial, and sports data

Is this course right for you?

This Data Science with R training is a beginner’s course and is well suited for programmers with or without experience. Students who wish to pursue a career in data science will also find this course beneficial.

Prerequisites:

Participants are expected to have:

  • Basic computer knowledge
  • Knowledge of basic arithmetic, algebra (and good to know trigonometry and calculus) like set theory, probability and statistics, logic, matrices, vectors etc.,

Curriculum

  • Welcome to the R Programming Course!
  • Installing R and R Studio (MAC & Windows)
  • Exercise - Get Excited!
  • BONUS: Using R in The Real World
  • Types of variables
  • Using Variables
  • Logical Variables and Operators
  • The "While" Loop
  • Using the console
  • The "For" Loop
  • The "If" statement
  • Section Recap
  • HOMEWORK: Law of Large Numbers
  • What is a Vector?
  • Let's create some vectors
  • Using the [] brackets
  • Vectorised operations
  • The power of vectorised operations
  • Functions in R
  • Packages in R
  • Section Recap
  • HOMEWORK: Financial Statement Analysis
  • Project Brief: Basketball Trends
  • Matrices
  • Building Your First Matrix
  • Naming Dimensions
  • Colnames() and Rownames()
  • Matrix Operations
  • Visualizing With Matplot()
  • Sub setting
  • Visualizing Subsets
  • Creating Your First Function
  • Basketball Insights
  • Section Recap
  • HOMEWORK: Basketball Free Throws
  • Project Brief: Demographic Analysis
  • Importing data into R
  • Exploring your dataset
  • Using the $ sign
  • Basic operations with a Data Frame
  • Filtering a Data Frame
  • Introduction to qplo
  • Visualizing With Qplot: Part I
  • Building Data Frames
  • Merging Data Frames
  • Visualizing With Qplot: Part II
  • Section Recap
  • HOMEWORK: World Trends
  • Project Brief: Movie Ratings
  • Grammar Of Graphics - GGPlot
  • What is a Factor?
  • Aesthetics
  • Plotting With Layers
  • Overriding Aesthetics
  • Mapping vs Setting
  • Histograms and Density Charts
  • Starting Layer Tips
  • Statistical Transformations
  • Using Facets
  • Coordinates
  • Perfecting By Adding Themes
  • Section Recap
  • Project work: Movie Domestic % Gross

Frequently Asked Questions

R is among the most widely used program for data analysis with more and more users growing each day. It’s a powerful language that helps build programs to analyse huge data sets and use visualization techniques to interpret data. Zeolearn academy recognizes the growing demand for R programmers and hence brings this course that is aimed at giving you the expertise needed to understand the language and leverage it to create outstanding programs for data analysis. This course is all about empowering participants with real time, practical skills that will help them land lucrative job roles. This course will help you gain hands on expertise through the numerous examples, exercises and project work conducted through the course of the workshop. You will also work on an industry-level project that will make you a master in R. Enrol now and get set for a glittering career.

On completing the course, you will:

  • Learn to program in R
  • Learn how to use R Studio
  • Learn the core principles of programming
  • Learn how to create vectors in R
  • Learn how to create variables
  • Learn about integer, double, logical, character and other types in R
  • Learn how to create a while() loop and a for() loop in R
  • Learn how to build and use matrices in R
  • Learn the matrix() function, learn rbind() and cbind()
  • Learn how to install packages in R
  • Learn how to customize R studio to suit your preferences
  • Understand the Law of Large Numbers
  • Understand the Normal distribution
  • Practice working with statistical data in R
  • Practice working with financial data in R
  • Practice working with sports data in R

Zeolearn brings you mentor driven courses that not only helps professionals gain theoretical expertise but also the practical experience in a wide variety of courses including courses on Programming such as Scala and C#, which are very popular. The fact that our workshops are mentor driven gives us an edge over other training institutes since you can learn from industry experts about the application and challenges of upcoming technologies. We have so far trained thousands of professionals with the skills needed to land lucrative jobs and you could be next!

You will receive Data Science with R certification in the form of a course completion certificate.

Towards the end of the course, all participants will be required to work on a project to get hands on familiarity with the concepts learnt. You will be working with statistical data, financial data and sports data in R. This project, which can also be a live industry project, will be reviewed by our instructors and industry experts. On successful completion, you will be awarded a certification.

Classes are held on weekdays and weekends. You can check available schedules and choose the batch timings which are convenient for you.

You may be required to put in 10 to 12 hours of effort every week, including the classroom sessions/live class, self study and assignments.

We offer classes in classroom and online format. While classroom sessions are held in specific venues in your city, for online sessions all you need is a Windows computer with good internet connection and you can access the class anywhere, at anytime. A headset with microphone is also recommended.

You may also attend these classes from your smart phone or tablet.

Don’t worry, you can always access your class recording or opt to attend the missed session again in any other live batch.

This course is apt for programmers with or without experience. Students who wish to pursue a career in data science will also find this course beneficial. 

  • Any working Laptop/desktop/PC with any OS (Windows, MAC, Ubuntu or Linux)
  • Lab requirements: We will use a virtual development environment and create a webserver interface to build,deploy and host our applications.

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