Machine learning with R in collaboration with IBM

Students can find various online courses for machine learning with R but none of them is as good as provided by DataTrained. We present to you the best online certification course for Machine Learning with R that you can find anywhere. DataTrained is India’s number one online platform for learning various courses.

In this course the student will learn to utilize R language to retrieve databases, analyse, visualize and filter data with R. In these times of covid it is difficult to enroll in or attend offline physical classes. That’s why we provide you with 100% online content. in which students are required to attend weekend classes, It has been fixed on weekends so that even working professionals can join our classes without having to leave their current jobs.

Here are the salient features of our Machine Learning with R course:-

• Certificate of completion from DataTrained and IBM
• Capstone projects and access to 15 real life projects
• 100+ hours of learning
• Learn from Industry professionals and experts
• Practice tests included
• Access to in-demand tools from IBM
• Analytics Jobs placement assistance

The demand for skilled and qualified machine learning professionals has been rising significantly for the past few years. This majorly due to the fact that machine learning technologies have been growingly adopted in every sector you can name.

Organizations have realized the positive impact that machine learning brings to the table. As you know there are hundreds of courses available in the market for machine learning but are they really worth it? Organizations only want the best skilled and a candidate who is certified from a reputed institute.

DataTrained and IBM or International Business Machines have joined forces to bring you the best online machine learning with R course available. DataTrained is India’s number 1 Ed Tech Institute providing various online courses and IBM is a world renowned organization. There is huge demand for IBM certified professionals in the market. IBM machine learning certification is totally worth it and it will skyrocket your career.

According to r-project.org R is a computer programming language and an environment for graphics and statistical computing. It is supported by R Core Team and R foundation for statistical computing. This programming language was developed by Ross Ihaka and Robert Gentleman. R is used by data miners for data analysis and statisticians for developing statistical software.

For machine learning R is mainly used for exploratory purposes and developing one off models. The R programming language has an interactive environment which is very beneficial for investigating and studying the use of packages and functions.

The best thing about using R for machine learning is that you don’t need to be a good programmer. The only knowledge you would be requiring is understanding which packages to use and how to use them. Even if you have knowledge of other programming language such as Java, C# or Python you will be able to quickly pick up syntax very quickly.

There are hundreds of machine learning packages in R. There has been a frequently asked question about, which programming language is best suited for machine learning? There are several contenders such as R, Python and MATLAB. According to a survey by Kaggle, open source R programming language is the top choice for data scientists.

Machine learning is a part of artificial intelligence which centres around developing of softwares and computer programs which access data to learn itself and make predictions. It does so without being specifically coded.

Being an open sourced programming language, packages are published on R with the help of contributions from developers throughout the globe, which makes it very user friendly. Here is a list of R packages which are widely used:-

• CARET or Classification And Regression Training
• data.table
• dplyr
• Random Forest
• ggplot2
• e1071
• xgboost
• kernLab
• rpart

According to indeed.com web portal, the average base salary of a machine learning professional is ₹ 21,611 per month in India. This is based on 154 salaries reported and updated on 8 January 2022. With top companies being:-

• PRISM : It provides a salary of ₹ 1,22,573 per month.
• 2COMS Consulting Pvt Ltd : It provides a salary of ₹ 63,702 per month.
• Ikya Human Capital Solutions Pvt Ltd : It provides ₹ 60,748 per month.

According to another web portal glassdoor, the average salary for a machine learning professional is ₹8.4 Lakhs per year based on 722 salaries listed. The salary ranges from ₹4.1 Lakhs per year to ₹19 Lakhs per year. With top companies being:-

• Quantiphi : It provides ₹8,82,602 per year.
• Tata Consultancy Services : TCS provides ₹5,39,405 per year.
• Accenture : It gives ₹8,71,959 per year.
• Amazon : It provides ₹4,56,658 per year.

On another platform payscale.com the average salary in India was found out to be ₹7,31,169 per year. With salaries ranging from ₹305k to ₹2m.

A student can find tons of courses on machine learning with R online and offline but are they really worth it? Majority of them would be of no use when it comes to finding suitable jobs. Only a certification from a world renowned institute would count.

DataTrained’s Machine Learning with R course is in collaboration with IBM. This certification carries a lot of weight in the industry. Our course is offered at an unbeatable price of ₹14999 plus taxes. It is an affordable price keeping in mind every class of society because we at DataTrained believe in providing affordable and quality education.

DataTrained Machine Learning with R course has a very beginner friendly curriculum. Our tutors teach everything from scratch keeping in mind the pace of learning of every student. Here is a detailed syllabus for our course:-

• Popular Algorithms such as dimensional, clustering, regression and classification reduction.
• Popular models such as train or test split, root mean square error and random forests.

• Decision trees
• Random Forests
• Reliability of Random Forests
• Advantages & disadvantages of decision trees

• Model Evaluation
• Overfitting underfitting
• Understanding different evaluation models

• Hierarchical clustering plus advantages and disadvantages
• Measuring distances between cluster - single linkage
• Clustering
• Measuring the distances between clusters - algorithms
• Density based Clustering

• Collaborative filtering and its challenges

Yes! You can definitely learn R programming language with no prior experience in programming. In Fact many of our students for machine learning with R course had no previous programming experience. Yet they achieved handsome packages in reputed organizations after completing our course.

In just 100+ hours you can master machine learning with R. Our tutors teach in depth concepts and give insights of various trending topics. With our Learning Management System (LMS) a student can raise any queries and get them resolved within a short period of time.

R is one of the most popular programming languages along with Python. R has been an eminent choice for data scientists and IT professionals. Let’s look at various reasons which tells us why R is worth learning in 2022:-

• R is an open source platform, which means it’s free of cost and has no licence restrictions.
• It has cross platform compatibility on various operating systems and softwares like MS Excel, MySQL.
• Extensive library with Inbuilt packages for machine learning.
• It has a vast community of developers and volunteers.
• Exceptional visualizations like ggplot2, RGL, etc.
• Interactive web apps development packages.
• Excellent for statistical analysis and probability distributions.
• Scope in various fields.

In simple terms machine learning or ML is a study of algorithms which improves automatically by experience over time and by utilization of data. It is a subset of Artificial Intelligence. Machine learning has an application in various fields like medicine, email filtering, computer vision and speech recognition. It is also used where it is unfeasible to make conventional algorithms to do required tasks.