Data Science, Deep Learning and Machine Learning with Python

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Data science continues to evolve as one of the most promising and in–demand career paths for skilled professionals. Today, successful data professionals understand that they must advance past the traditional skills of analyzing large amounts of data, data mining, and programming skills.

What Does a Data Scientist Do?

In the past decade, data scientists have become necessary assets and are present in almost all organizations. These professionals are well–rounded, data–driven individuals with high–level technical skills who are capable of building complex quantitative algorithms to organize and synthesize large amounts of information used to answer questions and drive strategy in their organization. This is coupled with the experience in communication and leadership needed to deliver tangible results to various stakeholders across an organization or business.

Data scientists need to be curious and result–oriented, with exceptional industry–specific knowledge and communication skills that allow them to explain highly technical results to their non–technical counterparts. They possess a strong quantitative background in statistics and linear algebra as well as programming knowledge with focuses in data warehousing, mining, and modeling to build and analyze algorithms.

Glassdoor ranked data scientist as the #1 Best Job in America in 2018 for the third year in a row. 4 As increasing amounts of data become more accessible, large tech companies are no longer the only ones in need of data scientists. The growing demand for data science professionals across industries, big and small, is being challenged by a shortage of qualified candidates available to fill the open positions.