The field of data science has started booming in the last few decades and there are a lot of job opportunities present in the field because of the rising demand for data scientists in the corporate world. So a lot of individuals are becoming interested in the field and are asking the question – Which is the best way to study Data Science?

Things you will need to learn for data science –

1. Education –

An aspiring data scientist first requires a very good educational background. They should have a high-school degree from a very high-quality, prestigious, and reputed high school. They should have scored very high marks in all of their high-school exams and should have completed all of their high-school projects successfully and before the deadlines.

The data science certification course can not help the learners with this aspect of data science.

2. R Programming –

An aspiring data scientist should also learn the R programming language. They must know how to program in the R programming language because the R programming language is a very important tool in the field of data science and is used by almost every data scientist to carry out analysis and data modeling work related to statistics.

In fact, the R programming language was designed especially for data modeling work and to organize, tabulate, and visualize statistical data and statistical models like charts, graphs, histograms, etc.

The R programming language is taught in the third module of the data science certification course.

3. Python Coding –

Python is another very important and essential language that any aspiring data scientist should learn and study thoroughly. Python is used by every data scientist in practically every data science project or task. Python is by far the most popular programming language used by data science and has a large number of libraries for all kinds of common data science tasks and problems.

If you will work in any business or organization which works on data science projects you will have to collaborate with other data science professionals and it is absolutely certain that they will use the Python programming language to work on the project.

4. Hadoop Platform –

The Hadoop platform is used very widely by data science professionals of every kind to host data science projects and to develop them from the beginning stage to the end implementation and execution stage because the Hadoop platform offers several features which make the development of data science projects very easy and very simple.

The Hadoop platform is taught very early on in the data science certification course. The learners will learn how to use the Hadoop platform when they study the Data Science courses.

Resources –

Advanced Degree –

It is very helpful for an aspiring data scientist to have an advanced degree such as a Masters’s degree or a Ph.D. degree from a college or a university. This degree will help them by equipping them with all the information and knowledge they will need to work on data science projects in the real world in big businesses and organizations in the corporate world.

MOOCs –

Another option for an aspiring data scientist who wants to learn more about the field is to take a massive open online course. The MOOCs from these providers tend to be very high quality but the learners will not be able to get any individual time or attention from the instructors and they will not be able to learn data science at their own pace.

Data science certification course –

The best way to study and learn data science is by taking a data science certification course. When you will learn data science course you will find that it will be very beneficial for you.

The data science certification course will help you to learn data science in a systematic and organized manner under the guidance of seasoned and experienced instructors who will be able to give you all the help, direction, and feedback that you will need to become an advanced user of the tools and techniques of data science.

Bootcamps –

The aspiring data scientists also have the option of registering for and attending boot camps. These boot camps are usually a few weeks long or at most a couple of months long. We don’t recommend this option because we don’t think that boot camps are very effective at teaching the learners the core concepts and topics of data science.

The basics and fundamentals of data science themselves are very complex and sophisticated, what to speak of the advanced topics? So we don’t think that the short time for which the boot camps last will be enough for the learners to grasp and imbibe all of these core concepts and topics to a sufficient degree.

LinkedIn Groups –

The learners can also join a LinkedIn group because these usually contain very seasoned and experienced data science professionals