Big Data Analysis with R Programming
ABOUT R Programming
R is an open source programming dialect and programming condition for measurable registering and design that is bolstered by the R Foundation for Statistical Computing. The R dialect is generally utilized among analysts and information mineworkers for creating factual programming and information examination. Surveys, overviews of information excavators, and investigations of insightful writing databases demonstrate that R’s prevalence has expanded considerably as of late.
R is a GNU package. The source code for the R programming condition is composed basically in C, FORTRAN, and R.R is openly accessible under the GNU General Public License, and pre-accumulated twofold forms are accommodated different working frameworks. While R has a summon line interface, there are a few graphical front-closes accessible.
WHY LEARN Big Data Analysis with R Programming?
R is considered as most widely used language of Data Science. Competitors with aptitude in R programming dialect are in exceedingly popularity and paid lucratively in Data Science. IEEE has over and over positioned R as one of the top and most prominent Programming Languages. Practically every Data Science and Machine Learning work posted all around notices the necessity for R dialect capability. All the top positioned colleges like MIT have included R in their separate Data Science courses educational programs. With its developing group of clients in Open Source space, R enables you to beneficially chip away at complex Data Analysis and Data Science ventures to get, change/purify, examinations, show and imagine information to bolster educated basic leadership. Yet, there’s one catch: R has a significant soak expectation to learn and adapt!
ABOUT THIS COURSE
The course will begin from the very fundamentals of presenting Data Science, significance of R and afterward will steadily manufacture your ideas. In the principal section, we’ll begin from setting up R improvement condition, R Data sorts, Data Structures (the building squares of R scripts), Control Structures and Functions.
The second portion contains applying your educated aptitudes on creating industry-review Data Science Application. You will be acquainted with the attitude and manner of thinking of taking a shot at Data Science Projects and Application improvement. The venture will then concentrate on creating robotized and powerful Web Scraping bot in R. You will get the astonishing chances to find what numerous methodologies are accessible and how to survey options while settling on plan choices (something that Data Scientists do each day). You will likewise be presented to web advances like HTML, Document Object Model, XPath, RSelenium with regards to web scratching, that will take your information examination aptitudes to the following level. The course will walk you through the well-ordered procedure of scratching genuine and live information from a classifieds site to examinations land slants in Australia. This will include getting, purifying, munging and examining information utilizing R measurable and representation abilities. Every single theme will be altogether clarified with genuine hands-on illustrations, practices alongside dispersing suggestions, subtleties, difficulties and best-hones in light of my times of understanding. What you will pick up from this course will be unique to what’s presently accessible out there as you will use my developing background and introduction in Data Science. This course will position you to apply for Data Science occupations as well as empower you to utilize R for all the more difficult industry-review ventures/issues and eventually it will super-charge your profession. So take the choice and enlist in this course and lets cooperate to make you spend significant time in R Programming more than ever!
This course will cover the installation, configuration, development and deployment of Python Programming Language and build Web Sites using the Django framework and Basic Open ERP. About 50% of the time will be instructor presentation and about 50% will be hands on labs.
- Setup and Use Development Environment for R
- Install and Use Packages in R
- Learn and use Atomic Data Types in R
- Learn and apply advanced explicit/Implicit Coercioning in R
- Learn multiple approaches to create vectors in R
- Understand nuances and implications in Vector Coercions
- Understand Vector indexing principles in R
- Understand and leverage Vectors’ flatness property
- Understand Vector Labels and Attributes and their practical use-cases
- Learn Matrices and multiple approaches for creation
- Learn how Matrices Dimension Property works
- Learn advanced techniques for Matrices Indexing
- Learn Matrices Operations and Important Functions
- Learn the amazing use-cases of Lists
- Learn to leverage Lists’ Recursive Nature
- Learn multiple ways to create Lists (including from other data structures)
- Learn critical nuances in Lists Indexing, Labels and Lists Properties
- Learn multiple approaches to create Data Frames (including from other data structures)
- Learn Data Frames sub-setting (beginner to advanced)
- Learn how to impute missing values in Data Frames for efficient Data Analysis
- Learn R Control Structures (Conditional statements and loops)
- Learn to create and use R Functions
- Understand Web Scraping Process
- Learn R’s Apply family of functions for advanced data manipulation
- Learn Multiple ways to perform Web Scraping in R
- Learn how to perform Data Munging, Cleansing and Transformation in R
- Learn HTML and Document Object Model in the context of Web Scraping
- Learn XPath Query Language for Web Scraping
- Learn RSelenium setup and usage for advanced Web Scraping
- Learn Regular Expression Functions in R for advanced analysis
- Learn advanced Data Frames techniques for efficient data analysis
- Learn how to perform statistical analysis and visualisation to derive insights in R
WHO IS THE TARGET AUDIENCE?
- Anyone who wants to get started or advance further in Data Science
- Anyone who wants to develop expertise in R programming based on best-practices
- Anyone who wants to learn how to use R for real-life challenging Data Science projects and applications
- No Programming Experience is Required
- No Programming Knowledge Required
- Lectures 0
- Quizzes 0
- Duration 3 hours
- Skill level Advanced
- Language Bengali & English
- Students 12
- Assessments Self