Overview & Career Prerequisites of Data Science

Posted by Kapil Devang on March 20th, 2020

Data science has taken over the business world at a rapid rate. Everything that’s in today’s cloud-based business world is moving much faster that is resulting in production and compilation of data at an increased rate. The opportunities of managing and utilizing the data operations are now endless as new applications of Data Science are being discovered every now and then. Thus, it’s creating jobs across the wide range of industries and also it’s giving rise to new career paths. Therefore, data science course can act as a huge platform for fulfilling the career objective of individuals.

Why Data Science?

This is the question that arises in the mind of readers. So, the answer to this query is that it enables you to make better decisions, better predictive analysis and pattern discovery. It also lets you to:

  •          Finding the lead cause of the issue by asking right set of queries
  •          Performing the exploratory study of the data
  •          Making the model of the data using various algorithms
  •          Communicate and visualize the results via graphs, dashboards, more.

What are the prerequisites for Data Science?

The prerequisites for Data Science are being described below:

  • Machine Learning: This is the backbone of data science. It is vital that the aspirants of data science must be well aware of ML in addition to basic knowledge of statistics.
  • Modeling: With the help of mathematical models, you can easily make quick calculations and predictions on the basis of what you already know about the data. Modeling is also one of the main parts of ML that involves identifying the algorithms. This consists of identifying the algorithms which would be considered as more suitable for solving an issue.
  • Statistics: Statistics are considered as the core of data science. By having a depth study on the statistics would help you in extracting more intelligence and obtaining more meaningful results.
  • Programming: Certain level of programming is required for execution of the successful data science project. Some of the common and easy to learn programming languages are Python, and R. Python. While beginning the data science course, keep in mind that you learn the basics of programming languages too as it would help you in supporting it.
  • Databases: For becoming a successful data scientist in the future, it is vital that you have good understanding of how the databases work, how they are managed and how data is extracted from them.
Kapil Devang

About the Author

Kapil Devang
Joined: September 5th, 2019
Articles Posted: 13

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