Hi this Sanjiv. My experience with GangBoard is really amazing. The courses have great depth and they allow you do work on them at your own pace. I would highly recommend anyone to try GangBoard you definitely won’t regret it.
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Data Science with R Training
With online data science training with R, you will be able to offer a significantly broad and flexible approach to data science. R helps users to develop computational statistics and algorithms for data analysis. R can also integrate with languages such as C, Java and C ++ and tools like Stata and Matlab.View More165 Ratings145 Learners30 Hours20 HoursBig Data365 Days24 / 7 SupportIntermediate
Online ClassroomAttend our Instructor Led Online Virtual ClassroomOne to One TrainingGet 1-to-1 Live Instructor Led Online Training in flexible timingsAbout Course
This course focuses on R, the open-source programming language that combines statistical modeling, big data analysis, simulation, and graphics. It is widely considered one of the most flexible—and therefore powerful—tools for data science. Experts agree that R will retain its relevance for a long time to come with public documentation for the myriad of applications that it has made possible. This data science with R online training program will cover all of the main topics that are necessary for becoming fluent in the language of R and carrying out the variety of tasks that it is used for in data science applications.
The course will begin with an introduction to analytics and data science; conduct an overview of key algorithms and models; and cover the important role that statistics and probability play in the field. It will then turn to the topic of R. It will explain the syntax and variables of the language and how to proficiently use it for data structures, manipulation, and visualization. The data science with R online training program will carry out an overview of the different kinds of regression models that are used. And, R Analytics online training will also include creating and graphing data sets, plotting data, and using data frames.
R Analytics online training is intended for data scientists and those with some background in statistics, programming languages, or software engineering. R combines the fields of computer programming with statistics and graphics, and familiarity with any of these fields is an advantage. However, there are no formal requirements, and anyone can register for the data science with R online training program.
A data scientist with certification in R and real world experience in carrying out data analysis has a world of opportunities before him. It suffices to say that Google is known to use R for everything it can, and smaller companies tend to follow what Google does. Surveys have shown that R is gaining on big-data analysis packages due to its flexibility, documentation, and open-source code. This suggests that the demand for R programmers is robust and will remain so, and those new to the field have a good chance of getting hired.
R is becoming the most common language of major corporations, and a sign of its extensive flexibility is the widely different kinds of companies that use R, such as Pfizer, Bank of America, and Shell, among many others. This is further proof that R is likely to continue to be adopted by smaller companies into the future.
Data Science with R Syllabus
Introduction to R
- What is R?
- Why R?
- Installing R
- R environment
- How to get help in R
- R Studio Overview
Understanding R data structure
- Variables in R
- Scalars
- Vectors
- Matrices
- List
- Data frames
- Cbind,Rbind, attach and detach functions in R
- Factors
- Getting a subset of Data
- Missing values
- Converting between vector types
Importing data
- Reading Tabular Data files
- Reading CSV files
- Importing data from excel
- Loading and storing data with clipboard
- Accessing database
- Saving in R data
- Loading R data objects
- Writing data to file
- Writing text and output from analyses to file
Manipulating Data
- Selecting rows/observations
- Rounding Number
- Creating string from variable
- Search and Replace a string or Number
- Selecting columns/fields
- Merging data
- Relabeling the column names
- Data sorting
- Data aggregation
- Finding and removing duplicate records
Using functions in R
- Apply Function Family
- Commonly used Mathematical Functions
- Commonly used Summary Functions
- Commonly used String Functions
- User defined functions
- local and global variable
- Working with dates
R Programming
- While loop
- If loop
- For loop
- Arithmetic operations
Charts and Plots
- Box plot
- Histogram
- Pie graph
- Line chart
- Scatterplot
- Developing graphs
- Cover all the current trending packages for Graphs
Machine Learning Algorithm:
- Sentiment analysis with Machine learning
- C 5.0
- Support vector Machines
- K Means
- Random Forest
- Naïve Bayes algorithm
Statistics:
- Correlation
- Linear Regression
- Non Linear Regression
- Predictive time series forecasting
- K means clustering
- P value
- Find outlier
- Neural Network
- Error Measure
Leading Topics:
- Overture of R Shiny
- What is Hadoop
- Integration of Hadoop in R
- Data Mining using R
- Clinical research preface in R
- API in R (Twitter and Facebook)
- Word Cloud in R
Upcoming Batches
Start Date End Date Time (EST) ( UTC -5) Day 21 Sep 2018 20 Oct 2018 (09:30 PM - 12:30 AM) Fri,Sat 22 Sep 2018 20 Oct 2018 (09:30 AM - 12:30 PM) Sat,Sun 24 Sep 2018 22 Oct 2018 (09:30 PM - 11:00 PM) Mon-Fri 25 Sep 2018 23 Oct 2018 (11:00 AM - 12:30 PM) Tue-Sat 25 Sep 2018 23 Oct 2018 (09:30 AM - 11:00 AM) Tue-Sat Data Science with R Programming Certification
At end of our course, you will be assigned to work a real-time project. Once you completed assigned project with expected results we (Experts Team from GangBoard) will verify and issue Data Science Training Using R Certificate. If you are not able to deliver expected results in project we will support you by clarifying doubts and help you to re-attempt the project.Data Science with R Training Reviews
FAQ
Comprehensive of required software will be publish in your LMS for installation. Our support team will help you to setup software if you need assistance. Hardware requirements need to be fulfilled by participants.Perhaps it may happen . We will assist you by providing recorded session of what you missed in your LMS. If you deficit you can appear in live batches for that topics those you missed
Stupendous expert in analytics field who understands the learner constraints and bring out in technical as well as subject matter experts.
We offer this course in “Live Instructor-Led Online Training” mode. Through this way you won’t mess anything in your real-life schedule. You will be shared with live meeting access while your session starts.
Don’t need any predecessor knowledge to get into R but aware of basic statistics is an added advantage.
Basically >2GB RAM will be fine for installing either LAMP stack or WAMP stack. Even if you have MAC there is MAMP stack available for free.
You can get a sample class recording to ensure you are in right place. We ensure you will be getting complete worth of your money by assigning a best instructor in that technology.
We are absolutely loved to talk in-person about group training (or) corporate training. So, please get in touch with our team through “Quick Enquiry”, “Live Chat” or “Request Call-back” channels.
Payments can be made using any of the following options and a receipt of the same will be issued to you automatically via email.
- Visa Debit Card / Credit Card
- American Express
- Master Card, Or
- PayPal
We are providing Data Science online training, One-to-One training with the help of experts. Our learners and trainers are frequently coming from different countries like USA, India, UK, Australia, New Zealand, Canada and UAE. To specify in cities London, Bangalore, California, New York, Pune, Mumbai, Chennai, New Delhi, San Francisco, New Jersey, Texas, Florida, Kolkata, Gurgaon, Berlin and Hyderabad among many.
You can reach us through +91-9791273737 / +91-9791237373. Or you can share your quires through enq@gangboard.com. Estimated turnaround time will be 24 hours for emails.
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