November 01, 2019
Amani Hassan
VP of Marketing and Communications

Have you wondered about what skills you need to be successful in data science and analytics careers.
Although there are boundless possibilities that could positively affect your request for landing a data science and analytics job it helps to start with some obvious ones such as data mining, machine learning, natural language processing, statistics, and visualization.
Data mining is a broad term referring to the practice of examining a large amount of data for the purpose of finding meaningful patterns and establishing significant relationships to help solve a problem.
Machine learning is a subfield of artificial intelligence. It focuses on optimizing ways to use algorithms to conduct data analysis and analytics tasks with as little human supervision as possible.
Natural language processing allows a computer to make sense of its interactions with human beings through linguistic means, such as spoken and written languages.
Statistics is a foundation for data analysis and analytics in general, without statistics, it is impossible to do any sophisticated data processing like data mining or machine learning.
Visualization is usually the last step of data science and analytics projects. The goal here is to communicate the results of analysis or analytics in the most intuitive way so that our stakeholders can quickly get the gist of the meaning and significance of the report.
All these skills are essential in becoming a well-rounded data scientist and a typical data science and analytics education program touches upon all of these areas.
These skills are pillars of data science and analytics and they are foundational skills embedded into many of the courses required to be taken in data science and analytics education programs. As you can see becoming, a data scientist demands many of your efforts that is why the job is so valued and sought out.