Although choosing to learn data science is indeed the perfect decision, many people still find it difficult to understand what this course entails. Beginners have found themselves in a dilemma when trying to figure out where to start.
There are different roles that data scientists play in their line of duty so it is important that one understands the courses that fall under data science so as to successfully choose the right career path. Moreover, one should take note that data science skills are very marketable and it is almost impossible to miss out on employment after successful training.
Every data science course consists of two different paths. The first one being the Non-programming Path under which an expert is able to manage data entirely without having to use programming skills. One is able to study data and from it, predict future business trends. Most people who choose this line of data science end up becoming business analysts. On the flip side, the programming path is for those interested in using programming skills to manage data. At the end of the study, one can either be a data analyst or advance more and become a data scientist.
Below, we have compiled together a list of skills that one learns in the journey to becoming an expert in data science.
For a data science course, most people prefer the R-Programming language. Almost all problems one encounters in data science can be solved using R-programming. Though a tough skill to internalize, understanding its concept is a major achievement towards being a professional data scientist. There are many online platforms with useful insights on how to use R-programming language.
Python language has become the most popular coding technique in the field of data science. Many confess that it is easier and faster to use python coding in all the processes of data science. It allows one to make various datasets effectively. Moreover, one can also import SQL tables and use a variety of data formats when coding. It is a technical skill that is a must have to everyone who is looking forward to a career in data science.
SQL Database and coding
Structured query language is essential as it helps a programmer to perform operations such as add, delete and the extraction of information from a database. It is a coding language that is well designed to help one find, communicate and analyse data. It is also used to perform analytical functions and change database structures effectively.
Skills in machine learning are used when it comes to projects that need one to predict possible organizational outcomes. Some of the skills under machine learning include supervised machine learning, unsupervised machine learning, outlier detection, survival analysis, adversarial learning and time series. Most projects in data science involve large amounts of data and thus it is very important for one to sharpen skills in machine learning.
There are many tools a data science expert can use to transform data into a visualized format. This way, the results of very complex research can be presented in a manner many will be able to quickly understand.
Data science is a wide and complex field and one needs to do some research before deciding to venture into it. Networking with experts is also instrumental in understanding better what data science entails and how best one can learn.