Data Science happens to be one of the highly sought after skills in today’s job market. This is reinforced by the seemingly unstoppable demand for these professionals. However, prior to you taking the plunge in getting the certification, it is imperative to know all the aspects of the landscape around it.
What are the Data Science Components?
Let us now spend some quality time in trying to uncover the intricacies of a sampling of the terms you usually hear related to Data Science. Some of the general terms you may have come around are Visualization, Statistics, Deep Learning and, Machine Learning. These terms happen to form the pillars of its components. These are also the major areas when we consider the various parts of Data Science. The individuals who form part of teams of Data Science are really expected to be experts in Statistics. Statistics forms one of the chief skill sets. Visualization also forms a big part of the required skill set. Machine Learning is not where everyone works on a Data Science team. This area is specially occupied by individuals who have a background in computer science and to top it off, they have the ability to break problems down into crisper forms.
Machine learning as it relates to Data Science
As far as Machine Learning goes, the crucial part of reaching a final solution is to ensure that the problem is made as precise as feasible. Once you can achieve that, the final solution to the given problem is very much doable or can be achieved using various methodologies. Given that there are a lot of tools centered approaches available nowadays, programming languages of the nature of R/Python along with many other exclusive tools like SAAS, Data Scientists are able to shape models of Machine Learning models very rapidly. In most of the cases, individuals typically lack the understanding of the methodologies. What these people lack is an understanding of the algorithms before using the tool. That is also an important factor in coming out with a solution successfully.
Another burning thing that is being spoken about for quite a while now in the industry is the topic of Deep Learning. Deep learning in effect is a part of Machine Learning. The really powerful thing that Deep Learning gives us is due to its very highly accurate models that it can build and that combined with its capability to work with data of higher dimensions that was not feasible with the earlier models of machine learning. Even though you are enabled to solve a problem in data science with high dimensions using machine learning, the very accuracy was really not at acceptable levels. Deep learning has been changing this very problem for us.
What are the Components of Data Science?
- Statistics is the about presentation of numbers
- Visualization is about visuals that help in communication.
- Machine learning is about to study, exploration and construction of algorithms.
- Deep Learning is an upcoming area.