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R for Data Science Certification Training
Rated 4.5/5 based on 75 customer reviews

R for Data Science Certification Training

Get the boot camp training for R and make your future in data analyses

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Modes of Delivery

Online Classroom

Collaborative, enriching virtual sessions, led by world class instructors at time slots to suit your convenience.

Classroom

Our classroom training provides you the opportunity to interact with instructors and benefit from face-to-face instruction.

Team/Corporate Training

Our Corporate training is carefully structured to help executives keep ahead of rapidly evolving business environments.
Group Discount: 10.00% for 2 people 15.00% for 3 to 4 people 20.00% for 5 and above people

3 Months FREE Access to all our E-learning courses when you buy any course with us

Curriculum

Module1- Intro to R Programming

Learning Objectives: Get an idea of what is R. Why R is so popular tool among Data Scientists.

Topics

  • What is R?
  • Why is it in demand?

Hands-on:  No hands on

Module2-
Installing and Loading Libraries

Learning Objectives:Learn how to install R and its components.
Learn how to install and load libarries
Learn frequently used libraries

Topics

  • Installation of R - step by step
  • Installing Libraries
  • Getting to know important Libraries 
Hands-on:Know how to install R, R Studio and other libraries

Module3- Data Structures in R
Learning Objectives: Learn about data structures in R

Topics

  • List
  • Vectors
  • Arrays
  • Matrices
  • Factors
  • String
  • Data Frames
Hands-on:  Write R Code to understand and implement R Data Structures

Module4- Control & Loop Statements in R

Learning Objectives: Learn all about loops and control statements in R

Topics

  • For Loop
  • While Loop
  • Break Statement
  • Next Statements
  • Repeat Statement
  • if, if…else Statements
  • Switch Statement

Hands-on: Know how to install R, R Studio and other libraries

Module5- Functions in R

Learning Objectives:Learn how to write custom functions, nested functions and functions with arguments

Topics

  • Writing your own functions (UDF)
  • Calling R Functions
  • Nested Function Calls in R
  • Functions with Arguments
  • Calling R Functions by passing Arguments
Hands-on: Learn how to write custom functions, nested functions and functions with arguments

Module6- Loop Functions in R

Learning Objectives:Lean all about loop functions available in R which are efficient and can be written with single command

Topics

  • apply
  • lapply 
  • Sapply
  • mapply 
  • tapply

Hands-on: Lean all about loop functions available in R which are efficient and can be written with single command

Module7- String Manipulation & Regular Expression in R

Learning Objectives: Learn all about string manipulations and regular expressions. The funtions can be extremely useful for text or unstructured data manipulations

Topics

  • stringr()
  • grep() & grepl()
  • regexpr() & gregexpr()
  • regexec()
  • sub() & gsub()
Hands-on: Learn all about string manipulations and regular expressions. The funtions can be extremely useful for text or unstructured data manipulations

Module8- Working with Data in R

Learning Objectives:Learn how to import data from various sources in R. How to write files from R. How to connect to various databases from R

Topics

  • Reading data files in R
  • Reading data files from other Statistical Software
  • Writing files in R
  • Connecting to Databases from R
  • Data Manipulation & Analysis
Hands-on:  Learn how to import data from various sources in R. How to write files from R. How to connect to various databases from R

Module9- Data Manipulation using dplyr

Learning Objectives:Manipulate & learn to transform raw data using dplyr. Learn generating insights from your data

Topics

  • Clean & Prepare Datasets
  • Data Transformations
  • Encoding
Hands-on: Write R code to generate insights from data

Module10- Exploratory Data Analysis

Learning Objectives: Learn to summarize dataset through descriptive statistics. Use variety of measurements to better understand you data. Learn to treat missing values.Also, learn how to discover patterns in your data

Topics

  • Summarize Data
  • Statistical analysis of Data
  • Extensive Data Exploration for deeper insights
  • Missing value treatment
  • Quality Analysis
Hands-on: Write R code to better understand the data

Module11- Data Visualization in R

Learning Objectives: Learn visualization in R with base and ggplot libraries. Learn Grammar of Graphics in a very strctured easy-to-understand manner

Topics

  • Visualization with base R
  • ggplot2: Grammar of Graphics
  • Visualisation using ggplot2

Hands-on: Write R Code to implement ggplot for data visualization

Module11- Case Study

Learning Objectives:

Topics

  • Real-Life Case Study

Hands-on: Case Study: House Attributes and Sales Price data. Use this data to explore more. Deep Dive into advanced explorations. Analyze and Visualize missing data, treat missing data to missing value imputation. Visualize data with various libraries. Gain deep insights on your data

Projects

Covers Exploratory Data Analysis and Data Visualization

Key Features

22 hours of Instructor led Training
60+ hours of Assignments
Analyze and Visualize data with R libraries
Generate insights from data

Our Students See All

Attended a 2 day weekend course by Knowledgehut for the CSM certification. The instructor was very knowledgeable and engaging. Excellent experience.

Attended workshop in April 2018

The CSPO Training was awesome and great. The trainer Anderson made all the concepts look so easy and simple. Using his past experience as examples to explain various scenarios was a plus. Moreover, it was an active session with a lot of participant involvement which not only made it interactive but interesting as well. Would definitely recommend this Training.

Attended workshop in July 2018

Great course. An interesting and interactive session to better understand how to succeed in formulating a business case and how to present it effectively.

Attended workshop in May 2018

The training was very interactive and engaging with the attendees.

Attended workshop in June 2018
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Jin Shi

Director at Timber creek Asset Management from Toronto, Canada
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Richard Dsouza

Business Analyst at Valtech from Bangalore, India
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Wily Salim

Services Project Engineer at Lendlease from Sydney, Australia
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Anish Maidh

Senior Project Manager at Telstra from Melbourne, Australia

Frequently Asked Questions

Glassdoor has ranked Data Science as the best job in America 3 years in a row, with a median base salary of $110000 and 4,524 job openings. This demand is only increasing year on year, making it the fastest growing tech employment area today. Jobs that require knowledge of data science include Data scientist, Analytics Manager, Database Administrator, Data Engineer, Business Intelligence Developer etc. This course will help you master R programming language and use it to create applications for business solutions.

On completing this course, you will be able to:

  • Use R studio
  • Create user defined functions
  • Manipulate & analyze data
  • Visualize data using R libraries like Ggplot, Plotly and Ggvis

By the end of this course, you would have gained knowledge on the use of data science techniques and the R language to build applications on data statistics. This will help you land jobs as data scientists

There are no restrictions but participants would benefit if they have elementary programming knowledge

On successful completion of the course you will receive a course completion certificate issued by KnowledgeHut.

Your instructors are R experts who have years of industry experience.

Any registration cancelled within 48 hours of the initial registration will be refunded in FULL (please note that all cancellations will incur a 5% deduction in the refunded amount due to transactional costs applicable while refunding) Refunds will be processed within 30 days of receipt of written request for refund. Kindly go through our Refund Policy for more details: http://www.knowledgehut.com/refund

KnowledgeHut offers a 100% money back guarantee if the candidate withdraws from the course right after the first session. To learn more about the 100% refund policy, visit our Refund Policy.

In an online classroom, students can log in at the scheduled time to a live learning environment which is led by an instructor. You can interact, communicate, view and discuss presentations, and engage with learning resources while working in groups, all in an online setting. Our instructors use an extensive set of collaboration tools and techniques which improves your online training experience.

Minimum Requirements: MAC OS or Windows with 8 GB RAM and i3 processor

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