6 Steps to Consider When Starting a Career in Data Science
It’s satisfying to be in the data science industry. However, this field will not be that satisfying if you don’t have an idea of what you need to do at a given time. The success in your data science startup career you don’t need experience so that you can experience the best results. This are some of the things that you have to put into consideration when you are about to start a career in data science.
The first thing is to know what you need. This is step is very important for you because that where you get the basis for your career. The main thing here is to understand where you are at the moment and what you want to achieve. To start with you have to describe what data science means. Data science deals with the asking and answering of questions in numeric data form. Nevertheless, you need to have a program to help you in solving the huge data that you will be working on. The program will be responsible for collecting data, clean and analyze it to give the answers to the questions. Some of the important things that you have to consider is a program writer and also flowing mathematics. The flowing of the coding language that you intend to use is very important.
Learn Python and R The use of R is to compute statistical data like data manipulation, storage and also graphing. On the other side python is preferred by many people because of its easy to learn the syntax and dynamic semantics. It’s a good idea to start with a single language until you are sure you are good at it. Its good if you practice semantics. structures and basic functions until they stick into your end.
You should consider perusing a degree. A degree in either information technology, computer science mathematics or statistics will be an advantage to your data science career because you will get into details of your career and you will also be close to experts in the field hence giving you a chance to ask any question that you may have.
It’s good that you learn about specialization. If you think data science is the only thing you can do when you are wrong because there are different sub-branches of data science that you consider to concentrate with.
The next step is to focus on practical applications. In your field of concentration its good you be careful with the theory part of it so that you will learn how the program works and how it behaves with certain syntax but you also need the practical part of it for you to be able to use it.
Finally, you will need to have an independent project to ensure you get the details of theory in action.