Learn from Home Offer
R Programming Training (12 Courses, 20+ Projects)
This R Programming Course includes 12 courses, 20 Projects with 116+ hours of video tutorials and Lifetime access.
You will also get verifiable certificates (unique certification number and your unique URL) when you complete each of them. It will explain you R Programming, Machine learning using R, Business Analytics using R, Data Visualization using R, Customer Analytics using R, Marketing Analytics using R among others.
MOST POPULAR
1
R Studio UI and R Script Basics
2
R Programming for Data Science
3
Project - Logistic Regression with R
4
Project - Decision Tree Modeling using R
5
Project on ML - Churn Prediction Model using R Studio
Offer ends in:
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* One Time Payment & Get Lifetime Access
* One Time Payment & Get Lifetime Access
What you get in this R Programming Training?
Online Classes
Technical Support
Mobile App Access
Case Studies
About R Programming Course
| Course | No. of Hours | |
|---|---|---|
| R Studio UI and R Script Basics | 3h 7m | |
| R Programming for Data Science | A Complete Courses to Learn | 6h 22m | |
| Project - Logistic Regression with R | 4h 25m | |
| Project - Decision Tree Modeling using R | 1h 45m | |
| Project on ML - Churn Prediction Model using R Studio | 1h 25m | |
| Decision Tree Case Study Using R- Bank Loan Default Prediction | 1h 51m | |
| Financial Analytics in R - Beginners | 3h 53m | |
| Financial Analytics in R - Intermediate | 1h 32m | |
| Financial Analytics in R - Advanced | 1h 4m | |
| R for Finance - Beginners to Beyond | 2h 18m | |
| Comprehensive Course on R | 4h 1m | |
| Project on R - Forecasting using R | 4h 28m | |
| Project - Fraud Analytics using R & Microsoft Excel | 2h 37m | |
| Project - Marketing Analytics using R and Microsoft Excel | 3h 32m | |
| Machine Learning with R | 20h 2m | |
| Projects on R and Tableau - Customer Analytics | 2h 12m | |
| Projects on R and Tableau - Pricing Analytics | 2h 06m | |
| Business Analytics using R - Hands-on! | 16h 11m | |
| Project - Market Basket Analysis in R | 39m | |
| Project - Hypothesis Testing using R | 3h 13m | |
| Data Visualization with R Shiny - The Fundamentals | 44m | |
| Data Science with R | 5h 8m | |
| R Studio Anova Techniques Course | 2h 18m | |
| Project - Exploratory Data Analysis EDA using ggplot2, R and Linear Regression | 2h 08m | |
| Project on R - HR Attrition and Analytics | 2h 52m | |
| Project on R - Predictive Model for Term Deposit Investment | 3h 12m | |
| Project on R - Card Purchase Prediction | 2h 31m | |
| Employee Attrition Prediction using Random Forest Technique and R | 2h 2m | |
| Project on Term Deposit Prediction using Logistic Regression CART Algorithm | 1h 43m | |
| Machine Learning Project using Caret in R | 1h 6m | |
| Machine Learning Project - K-Means Clustering using R | 44m | |
| Project on R - Telecom Customer Churn Prediction | 1h 32m |
| Course Name | Online R Programming Course Bundle |
| Deal | You get access to all 12 courses, 20 Projects bundle. You do not need to purchase each course separately. |
| Hours | 116+ Video Hours |
| Core Coverage | R Programming, Machine learning using R, Business Analytics using R, Data Visualizing using R, Customer Analytics using R, Marketing Analytics using R |
| Course Validity | Lifetime Access |
| Eligibility | Anyone serious about learning R Programming and wants to make a career in this Field |
| Pre-Requisites | Familiarity with R programming language is recommended |
| What do you get? | Certificate of Completion for each of the 12 courses, 20 Projects |
| Certification Type | Course Completion Certificates |
| Verifiable Certificates? | Yes, you get verifiable certificates for each course with a unique link. These link can be included in your resume/Linkedin profile to showcase your enhanced R Programming skills |
| Type of Training | Video Course – Self Paced Learning |
| Software Required | Free Download of R Software |
| System Requirement | 1 GB RAM or higher |
| Other Requirement | Speaker / Headphone |
Online R Programming Training Curriculum
Let’s now briefly understand the R Programming courses we are offering in this Bundle.
Goals
This course aims at providing end to end technical expertise required for accomplishing challenging tasks in day to day activity of being an R programmer. This course also has elements of machine learning technologies to provide expertise in that field specifically in R.
Objectives
In the current scenario where we produce 2.5 quintillion bytes (1 quintillion bytes = 1018 bytes!) of data every day, it becomes imperative for an organization to look for someone who is a master in understanding the data and derive meaningful insights from there. Post completion of the course it will be a cakewalk for learners to look at the data perform some exploratory data analysis on that and provide meaningful insights for the data. R is a statistically powerful tool that aims at providing powerful statistics of the data fed into that. This course will also enable you to use libraries in R specifically designed to get the output of insights either graphically or matrix formation.
Course Highlights
Our course acts in the same way as a beginner or an advanced learner. During the course itself one would gain enough confidence to take up challenging data science project in R in real-life and to make this happen here are some key highlights of what you as a learner would sign up for:
- This course will eventually start with the UI of R studio to make the learner get a hang of what is in store of being an R programmer. Post that one would learn and get a hang of how we do programming in R. This portion is critically helpful for beginners who have no idea on how it looks like.
- Then we dive into a particular domain of financial analytics and provide deep insights in terms of a beginner, an intermediate and even for an advanced learner.
- Once a person is well versed with the individual aspects of financial analytics we move our focus to Business analytics in R. In this portion, one would get to know about a well-knit community using CRAN packages and many more such libraries and build a culture within the learner to be a part of the community as well.
- This course also brings you the advantage to learn Anova, which deals with the analysis of variance. This portion is also critically helpful for the learner to know about the data statistically. One common technique one would get acquainted with is to analyze differences among group mean.
- Last but not least, a well-known library Caret is not a topic we can miss on in this course.
Project Highlights
This course will not only strengthen your grasp in this technology by teaching technical terms but with this course, one would gain immense exposure to hands-on experience in completing real-time projects. Learning through practicing will enable better grasping of technical details. Some of the highlights of projects from this training are:
- In the starting itself once a learner gets used to the RStudio and R scripting basics we have a project on Logistic regression and decision trees to take care of putting into work the technical details of machine learning learned along with getting more used to the RStudio.
- Once we have a better understanding of what R programming is we would be going through domain-specific projects like Forecasting in R, Fraud analytics and marketing analytics. These projects will prepare you better for the upcoming challenges in everyday work.
- Not only R, but we would also combine the advantages of Tableau along with R to provide wide experience on different projects like Customer Analytics, Pricing Analytics.
- In some of the retail analytics, we come across Market basket analysis a lot and a project on this in our training is like an icing on the cake. This project will prepare you more in getting ready for the role in the retail domain if any.
- In a different domain, we have analytics on HR attrition and term deposit prediction as well.
- Last but not the least a training without a project on exploratory data analysis is like forgetting to put a key to start a 4-wheeler.
R Programming Course – Certificate of Completion
What is R Programming?
- R is a programming language that is used for statistical programming mainly. It is one of the most popular languages for data science and machine learning problems. People around the world use R for the same.
- R is a functional programming language that is considered to be very easy to learn. Even those people who never had any programming background find it easier to learn and code R.
- There are many benefits of learning R. Almost all data science job requires the candidate to know R. because of its simple function-based approach, most of the activities in R can be completed in a couple of lines of code which in another language such as C or Java would need dozens of lines.
- R comes with several inbuilt libraries that can be used by anyone to develop their codes and solutions. Apart from that, it has thousands of additional libraries that can be installed by simple one-line command and thus a huge set of functionalities is available to be used by the user with a single click of a button.
- R can be connected to databases, it can be used to build front-end dashboards and can talk to the third-party application as well as using REST API and microservices.
- R is available on the Server as well as on Cloud as well.
- R is open-source and free to use.
- R has an IDE as well which is called RStudio which is fun to use.
- R is the preferred language in both industry and academia. New additions to it keep on happening and to support code for version issues, it also provides version control.
- Among many outstanding features, R can also be used to connect to GIT for project management and code repository.
Industry Growth Trend
The global MOOC market size is expected to grow from USD 3.9 billion in 2018 to USD 20.8 billion by 2023, at a Compound Annual Growth Rate (CAGR) of 40.1% during the forecast period.[Source - MarketsandMarkets]
Average Salary
Average Salary$73,990 per year
The average salary for a Programmer is $73,990 per year in the United States.
[Source - Indeed]
[Source - Indeed]
Which Skills will you learn in this Training?
- One can become an expert in R programming via this course. It has more than 70 hours of material which talks about nothing but R language. It covers all the topics and focus on examples and use cases. There are plenty of self-exercises which makes the learner confident about his/her skillset.
- This opens up a new career avenue for many learners. R skill is highly in demand these days and the demand is only going to rise in the coming years. Independent studies from top surveyors across the world predict that there is a huge shortage of qualified data scientists and r programmers everywhere and thus it is a great time to upskill and join the workforce.
- Data visualization, machine learning and statistical concepts are also covered in this R programming course which makes it a complete package. Learners get to learn a lot of good stuff which will make them industry ready in no time.
Pre-requisites
- Some understanding of mathematics and statistics is recommended so that it becomes easy to understand the concepts discussed in the class.
- If there is any familiarity with one programming language, then it becomes very easy for leaner. However, the course does not expect that and hence teaches the programming skill from the beginning.
- It requires that one has a technical background such as a degree in mathematics, statistics, basic science or engineering. Otherwise, the course may become quite challenging at times.
Target Audience
- Prospective data scientists: – those who want to become a data scientist can join this R Programming course and learn about the essentials of r programming. Such candidates could be both freshers as well as working professionals. This course is suitable for both. It has been designed considering no experience what so ever in programming or data science.
- Managers and leaders:- Those candidates who want to set-up a data science team, or wants to guide and lead an existing data science team can also benefit from this R Programming course. They may probably not be interested in coding and hands-on exercises which is fine. They can grab the concepts at a high level and then while working get the things done by the team.
- It is expected that the candidates have a technical background such as a degree in mathematics, statistics, basic science or engineering to make the most out of this course. Technical people are more likely to understand the lectures then the non-technical people.
FAQ’s- General Questions
How difficult is this R programming course to follow?
This R Programming course is not very difficult, but it is not too easy too. If one spends some 30-4 hours per week and do all assignments on time, they will understand everything. Most students find it difficult because they do not adhere to the timelines.
Will I be able to finish this R programming course while working?
Yes, with some motivation and determination you shall be able to pass the course.
All that you need to do it to study regularly and complete exercises on time. You only need to spend 3-4 hours per week and hence we believe it should not be challenging for working people.
Will this R programming course help me in changing my job?
Many of our students changed their job and got a hike post this R Programming course and thus we believe you could also be able to do so. Don’t bother about hike and job change, first learn the course well, if you could do so, you will be able to crack interviews.
Does this R programming course connect with industry requirements?
Our course is regularly updated and relevant use-cases and examples are added from time to time to make sure it stays focused on current demand and thus teaches the skills that the student needs to learn.
Career Benefits of this Training on R Programming
- Career benefits come in many forms for our students. Many of our students switched to better jobs after going through this course. Many others started their start-ups and consulting businesses as well. One of our students became so attached to statistics and machine learning that he is now doing a Ph.D. into machine learning full time.
- Thus, career benefit depends upon individual candidates’ aspirations. If you are looking for a job change or even wants to move internally within your organization for a data-science based role, you could do so after this course as many of our students did. If you are a fresher who is looking for a job of the future and is not just willing to do usual software engineering jobs such as web development or testing, this course could bring the real difference in your career and life goal.
- Thus, what we suggest to our students is not to worry too much about benefits, first learn the concepts, learn the skill, get fully confident with coding and solving problems and then you shall surely be able to get your reward because if you do so much hard-work then you only will get the benefit, not the third person. R programming course is more relevant today than ever before and this more than 70 hours, of course, covers everything that a student needs with practice and use cases too.
R Programming Course Testimonials
A nice introduction in R for beginners
The R Programming Training provides a nice overview of the R programming language and I believe that it is a nice introduction for beginners that want to get involved with statistics and mathematics. The instructor can present the theory and the code behind each lecture, using a clear, concise and complete example. Recommended for beginners and nice job from the instructor.
Linked
Dimitris Moustakas
R Programming Training
A deep-dive worth taking, this R Programming course about R fundamentals highlights the use, benefits, features and much much more about the language – quite in-depth. I lacked only the exercises to practice all this theory and although at times the lessons were slightly repetitive, overall it is worth it!
Linked
Miguel Gomes Monteiro
Marketing Analytics using R and Excel
R Programming Training Course is quite informative with exposure to commonly used techniques in marketing. It covers topics like conjoint analysis, market basket analysis, logistic regression to leverage the customer data to support the marketing strategies to improve retention, acquisition and overall experience of the customers.
Linked
Ankit Tyagi
Pricing Analytics
It was a very comprehensive course with nice examples. It helped me in all aspects of pricing analytics like -descriptive, predictive and prescriptive. The explanation is supplemented with small exercises that help in gaining hands-on experience of a business problem. The case studies are carefully picked to explain the concepts. It helped me gain a better understanding of the market. Very helpful.
Linked
Abbas Singapurwala
