Machine learning is a form of artificial intelligence where the focus is to develop computer programs that automate data analysis by learning and adapting through the experience without the need for precise programming. R is one of the major languages for data science. It provides excellent visualization features, which is essential to explore the data. ACTE has been designed to help you master machine learning concepts and techniques working with actual data, developing algorithms, performing classification and operations. This course explores in depth the libraries and functionalities the R programming language offers for machine learning techniques in order to draw conclusions from data. Start Learning with us ACTE Machine Learning Classroom and Online Training Course.
Machine Learning Using R is very useful for career. Machine Learning can be a rewarding career for students who are good in mathematics and statistics and have sharp programming skills. ... Machine Learning is evolving quite rapidly and a lot of technology professionals are required in the coming years in the area of Machine Learning.
Machine Learning Using R, have great scope, Scope is high Basically, it's an application of artificial intelligence. Also, it allows software applications to become accurate in predicting outcomes. Moreover, machine learning focuses on the development of computer programs. The primary aim is to allow the computers learn automatically without human intervention.
Moreover, research from MarketsandMarkets depicts, by 2022, the growth in machine learning market size will be USD 8.81 Billion. So, as you can see there are lots of opportunities lies in this field, this is the right time to upskill in Machine Learning.
Even as a fresher, you can get a job in Machine Learning Using R domain. Broadly speaking, if you want to develop your career in artificial intelligence, you can get started with a software development background and pick up the machine learning theory, or you can start off with the machine learning theory and communication skills and gradually pick up the programming chops to work in ...
If you are going for 6 months of self-study for Python, R and SQL, you can certainly get a job as a data scientist but it is not that easy. You will have to possess an extensive grasp of machine learning, statistics, mathematics, programming languages and so on.
We are happy and proud to say that we have strong relationship with over 700+ small, mid-sized and MNCs. Many of these companies have openings for Machine Learning Using R. Moreover, we have a very active placement cell that provides 100% placement assistance to our students. The cell also contributes by training students in mock interviews and discussions even after the course completion.
There are plenty of machine learning algorithms. The choice of the algorithm is based on the objective.
In the example below, the task is to predict the type of flower among the three varieties. The predictions are based on the length and the width of the petal. The picture depicts the results of ten different algorithms. The picture on the top left is the dataset. The data is classified into three categories: red, light blue and dark blue. There are some groupings. For instance, from the second image, everything in the upper left belongs to the red category, in the middle part, there is a mixture of uncertainty and light blue while the bottom corresponds to the dark category. The other images show different algorithms and how they try to classified the data.
- Statistics.
- Linear Algebra.
- Calculus.
- Probability.
- Programming Languages.
Learn R. Can someone with no programming knowledge learn “R”? The answer is yes! ... Despite not having any previous programming experience , I analyzed my first data set of more than 20,000 data points in only a couple of months.
Our course ware is designed to give a hands-on approach to the students in Machine Learning Using R. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.
Yes It is worth , Yes!! Learning R is worth any time in the near future. ... So, I will suggest take some time and start with Python if you have some Engineering background (I think engineers are more comfortable with python). If you are a master in Statistics/Economics etc then start with R and after some time use python for complex tasks.
Yes Definitely! From my point of view learning, R language has a worth to learn. R is the best programming language to perform analytical operation. The number of applications such as healthcare, finance, media use R programming to analyze their data.
10 days may not seem like a lot of time, but with proper self-discipline and time-management, 10 days can provide enough time to gain a survey of the basic of machine learning, and even allow a new practitioner to apply some of these skills to their own project.
For more detailed examples, coding in R /python, using libraries yourself or products like weka 2-3 months easily, depending on the depth to which you need to immerse yourself. Another 2-3 months to learn and practice using machine learning libraries with varying types, size of data.
- R is Open-source and Freely Available
- R is Cross-platform Compatible
- R is a Powerful, Scripting Language.
- R Has Widespread Acclaim
- R is Highly Flexible and Evolving.
- Publishers Love R.
Future Scope of Machine Learning
The scope of Machine Learning is not limited to the investment sector. Rather, it is expanding across all fields such as banking and finance, information technology, media & entertainment, gaming, and the automotive industry.
Machine Learning Job Profiles
Machine Learning Engineer
One of the most sought job profiles in the field of machine learning is a machine learning engineer. Machine learning engineer is responsible for designing and implementing machine learning algorithms to help decipher meaningful patterns from humongous amounts of data.
Data Scientist
The main role of a Data Scientist is to collect, analyze, and interpret large amounts of unstructured data by using machine learning and predictive analysis, to derive insight and help design future strategies. Chances of getting hired as data scientist increases if someone have a good hands-on-experience working with machine learning, Big Data technology, and analytical tools.
Data Analyst
A Data analyst delivers value to their organization by first acquiring information about a specific topic, and then interpreting as well as analyzing it, and at last present their findings in comprehensive reports. They use their skills and tools to provide competitive analysis and identify trends. Data analysts have a strong background in calculus, economics, statistics, machine learning, and programming.
Data Architect
One of the most in-demand Machine Learning professionals today, data architects takes care of organizations big data ecosystem. They develop, construct, test, and maintain highly scalable data management systems by using Machine Learning algorithms. After collecting data and doing batch processing, they send it for analysis to data scientist via an API.
Careers in R
Being an R programmer does not only guarantee jobs in the IT industry but also there are several industries that are making use of data to transform problems into solutions. Some of the areas where R applicants are most in-demand are as follows:
- Financial Sectors
- Banks
- Health Organizations
- Manufacturing Companies
- Academia
- Governmental departments
R programmers are most in-demand, especially in emerging startups. Some of the positions that are available for the R programmers are as follows:
- Data Scientist
- Business Analyst
- Data Analyst
- Data Visualization Expert
- Quantitative Analyst