Simply put, data science and applied AI have a far deeper impact on modern day Information Technology (IT) than what you can gauge. From collecting data to putting it to use for understanding the impact on business-centric decision making, data analytics can benefit the whole value chain of data science programming. In this value chain, R Programming plays a very critical role.
In this article, we discuss what R Training course could do your data science career.
Refresher in the Basic Computing Knowledge
R training course could be considered a refresher module in your data science knowledge basket. This is attributed to the essentials of R programming being vested in the logic-based building blocks of each practice and theory session. The basics of R training program include understanding of Objects, Arrays, Vectors, Data Frame and Logical Reasoning.
In brief, R training would involve involvement of these five basic Object class –
- Real Numbers
- Whole Numbers and Integers
- Complex Numbers/ Imaginary Entities
- If Else/ True False Logic
Stuff You Can Learn in R Training Makes You Invincible
Yes, that’s right, and data scientists with R Training certification boast of their invincibility at length. For example, all major banking and financial statistics are derived from algorithms running on R Programming. Rmetrics, a core components taught in R Training course is based entirely on the stastical part of R Programming. Together with other R Packaged software models, Rmetrics Project addresses the multiplicity and involvedness of computational finance and financial engineering within a simple, comprehensible programming framework that are already known to most Java and C++ professionals.
It’s FREE but Applications Need Industry Evaluation
Though R programming language is an open-sourced software, ongoing research is must to deal with the principle component analysis and plotting of statistical results. There are more Applied AI-relevant implications in R programming than in any other computing course currently available online or in classrooms.
R training can do wonders to your data science career by provides the guaranteed possibility to continue research within IT-centric embedding script among the vast community of academia and business, both.
Overall, your learning in the R Training course would validate your data science skills for industry-relevant projects that mostly revolve around AI, machine learning and IoT applications.
Lucrative Job Opportunities with Multi National Data Science Companies
Since R is an open source programming language a free software module, global companies are heavily invested in improving their infrastructure around the data science models. In 2011, R training courses received a major impetus after Oracle announced the ambitious Big Data Appliance where it brought together the systematic integration of other generic programming languages, including Apache, Hadoop, Oracle Linux, and NoSQL with R programming. Since then, other mega cloud companies have increasingly relied on professionals with certified R Training degrees to further their data science and Big Data projects.
Today, a data scientist with R training certification could take a pay out of anywhere between $300,000 and $450,000 per year as a salary! In fact, Glassdoor and LinkedIn ranks data scientists with R training certification favorably for crowd sourced salary data sources.
Diversity of R Training Makes It Popular
Apart from Python and regular Java courses, R Training is popular choice for data analysts and data science. In fact, most professionals realize the true differences between being an analyst and a scientist at R training certification courses. Since R offers a range of packages, ranging from importing available data to installing algorithms for data frameworks, there is a very clear demarcation in activities for analysts and scientists.
Once completed, R training courses help professionals deal with these activities in a better, simplified manner –
- Data Visualization and Graphical Reporting
- Advanced Data Plotting and Manipulation for advanced computational frameworks
- Modeling and Machine Learning for randomForest, rpart, etc
- Stepping stone to Predictive modeling and Descriptive Intelligence
As we sink deeper into the Fourth industrial revolution, professionals would be required to learn and develop their own algorithmic techniques, mostly AI techniques such as Deep Learning and Reinforcement Learning, to drive applied data science projects for military, healthcare, industrial automation, education and marine ops. The scope of learning and applying R training basics are endless in 2019.