Developing your skill and building it as a career is a difficult thing that takes a lot of time, I have seen a lot of developers that find it very difficult to lay their hands on one programming language? while some want to upgrade by knowing more in the tech ecosystem today, I will be talking about "Career in Data Science"
First, what is Data Science? about 75% of the world population of programmers in the tech ecosystem are data scientists. today I will break it down and talk about their career. Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, deep learning, and big data. Data Science is the secret sauce here. All the ideas which you see in Hollywood movies can actually turn into reality by Data Science. Data Science is the future of Artificial Intelligence. Therefore, it is very important to understand what is Data Science and how can it add value to your business.
let’s dig deeper and see how Data Science is being used in various Career
The Career in Data Science
Data Science can be used in predictive analytics.
Let’s take weather forecasting as an example. Data from ships, aircraft, radars, satellites can be collected and analyzed to build models. These models will not only forecast the weather but also help in predicting the occurrence of any natural calamities. It will help you to take appropriate measures beforehand and save many precious lives.
Machine learning for making predictions:
if you have transactional data of a finance company and need to build a model to determine the future trend, then machine learning algorithms are the best bet. This falls under the paradigm of supervised learning. It is called supervised because you already have the data based on which you can train your machines. For example, a fraud detection model can be trained using a historical record of fraudulent purchases.
Machine learning for pattern discovery:
If you don’t have the parameters based on which you can make predictions, then you need to find out the hidden patterns within the dataset to be able to make meaningful predictions. This is nothing but the unsupervised model as you don’t have any predefined labels for grouping. The most common algorithm used for pattern discovery is Clustering.