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Data science and its applications are growing at a very fast pace. Demand for data scientists is increasing as the applications of data science are overwhelming. Its applications are not limited to a certain industry or business. Data science involves many technical and non-technical skills, and practicing these skills will help you compete with other data scientists. Earning a data science certification is the best way to develop such skills.

Skills required in data science are divided into the following two categories:

  • Non-Technical Skills : These skills do not require much technical knowledge or any certification. However, even the most technically sound data scientists should have such skills to retain in the market
  • Technical Skills : When you closely observe the job description list for a data scientist, you will find out that these skills are mentioned on the top. Various organizations lay stress on such skills to improve their analytics

Now, as we have understood the two categories, let’s take a glance at some of the required skills:

  • Critical Thinking

It is a skill that is required in almost every profession, be it data science or any other. A data scientist must possess such skills, as it helps them to understand and analyze the extracted information. Moreover, it helps them frame questions that will help the business grow and excel in their career.

This skill helps a lot in identifying and solving problems when dealing with loads of data. By learning this skill, you will be able to:

  • Analyze questions and give results
  • Identify which resources can solve a critical problem
  • Look at problems from  different angles and views
  • Communication

Effective communication is another important skill that is required everywhere. It does not matter what your designation is. It is an important trait that will help you out in every aspect.

In data science, effective communication helps you to fluently explain and deliver the findings to all types of audiences. It should be delivered in such a way that even a non-technical person can catch up with you. When there is a solution to a problem, the whole organization relies on the data scientist to be the problem solver. Hence it is necessary to convey the information effectively.

  • Preparing data for analysis

It is the process of preparing and getting the data ready for further analysis and operations. It is pivotal as it involves tasks cleaning and data discovery which plays a major role in improving the workflow for the scientists. There are some user-friendly data preparation tools available like Tableau, Prep Builder, etc., that can make your task easier.


Mentioning some of your data science skills in your resume will surely help you find jobs in a reputable organization. Having a data science certification can give you an extra point while applying for jobs.


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