Install R studio. Explore R language fundamentals, including basic syntax, variables, and types
Learn about data structures that R can handle. Create and manipulate regular R lists, tuple etc.
Learn about control and loops statements
Learn to write user defined functions and object oriented way of writing classes and objects.
Use functions and import packages
Learn to apply data processing functions in R for describing and performing operations on data.
Learn to Summarize the data which helps you to take necessary steps for further analysis
While there are no prerequisites, participants would benefit if they have elementary programming knowledge.
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Learning Objectives:
Get an idea of what R is and why it is so popular among Data Scientists.
Topics Covered:
Hands-on: No hands-on
Learning Objectives:
In this module you will learn to install R and its components, install and load R libraries and learn about the frequently used libraries.
Topics Covered:
Hands-on:
Know how to install R, R Studio and other libraries.
Learning Objectives:
Learn about data structures in R.
Topics Covered:
Hands-on:
Write R Code to understand and implement R Data Structures.
Learning Objectives:
Learn all about loops and control statements in R.
Topics Covered:
Hands-on:
Write R Code to implement loop and control structures in R.
Learning Objectives:
Learn how to write custom functions, nested functions and functions with arguments.
Topics Covered:
Hands-on:
Write R Code to create your own custom functions without or with arguments. Know how to call them by passing arguments wherever required
Learning Objectives:
Learn all about loop functions available in R which are efficient and can be written with a single command.
Topics Covered:
Hands-on:
Write R Code to implement various types of apply functions and understand their usage.
Learning Objectives:
Learn all about string manipulations and regular expressions. The functions can be extremely useful for text or unstructured data manipulations.
Topics Covered:
Hands-on:
Write R Code for string manipulation and handle regular expression.
Learning Objectives:
Learn how to import data from various sources in R and how to write files from R. Also learn how to connect to various databases from R.
Topics Covered:
Hands-on:
Write R Code to read and write data from/to R. Read data not only from CSV files but also using direct connection to various databases.
Learning Objectives:
Learn how to apply various data processing functions in R. These operations can be useful to describe data and perform certain operations on it. This will help you to take necessary steps for further analysis.
Topics Covered:
Hands-on:
Learning Objectives:
Learn basic data visualization techniques to build charts using R.
Topics Covered:
Hands-on:
Write R code to perform basic visualization of the data
Learning Objectives:
Case Study to explore R.
Topics Covered:
Hands-on:
Case Study to explore R
Write R code to perform basic visualization of the data
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I was totally impressed by the teaching methods followed by Knowledgehut. The trainer gave us tips and tricks throughout the training session. The training session gave me the confidence to do better in my job.
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 learn the R programming language which is one of the most commonly used languages in the Data Science space.
By the end of this course, you would have gained knowledge of the use of R language to build applications on data statistics. This will help you land jobs as data analysts.
Tools and Technologies used for this course are
There are no restrictions but participants would benefit if they have elementary programming knowledge.
Yes, KnowledgeHut offers this training online
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 canceled 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 a refund. Kindly go through our Refund Policy for more details: Refund Policy.
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
