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How to Become a Data Scientist in 2019: A Beginner’s Guide

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Reema Paul
How to Become a Data Scientist in 2019: A Beginner’s Guide

How can I become a data scientist? What are the most important skills to learn for a data scientist?  What does a data scientist do? These are few questions that are being discussed online, on forums, on blogs, and on knowledge-sharing platforms like Quora.

It is true that the “hottest job of the 21st century” has all the buzz, glam and traffic, but many enthusiasts are still confused as to what this job entitles. Let’s discuss how you can become a Data Scientist.

Learn Mathematics and Statistics

If you are a data science aspirant, you need a strong background in mathematics and basic knowledge of statistics. In the midst of the hype around data-driven decision making, the basics are somehow getting sidelined. The boom in data science requires an increase in comprehensive statistics and maths skills. Some of the fundamental concepts expected from a business analyst are correlation, causation and how to statistically test hypothesis. You can learn these skills by joining data science training course.

Practice Programming

Numerous studies have come to the conclusion that Python is the most important language to be learnt by a data scientist. In fact, in 2019, this sentiment is being clamored, as almost 75% of the industry, as well as the professionals, are saying that.

So beginners should focus on learning Python programming by joining data science training in Noida for at least their first next six months and interacting with databases. Then once you have a good understanding of Python and programming in general, you can then start learning other languages like R and Java, then move to machine learning packages like sci-kit-learn.

 Create a Portfolio

While a resume is an important component to showcase your abilities to the potential employers, a data scientist should also be able to showcase his/her abilities in coding and other software capabilities. A crucial part of data science jobs is to be able to code, and GitHub serves as a perfect platform to access the coding skills and display hands-on ability to solve problems.

Focus On Soft Skills Too

Industry experts say that simply hiring a data scientist is not enough. Managers need to take special care to align business and data teams thus enabling data scientists to be self-sufficient. Here are the skills a good data scientist should focus on:

  1. Communication
  2. Problem-solving
  3. Ability To Draw Parallels To Real-world Problems
  4. Prioritization
  5. Business acumen

 Apply For Jobs Wisely

As tools are evolving, data science job roles are maturing and becoming more mainstream in companies. The number of openings that companies have for data science roles is also on an all-time high. Given the number of opportunities available, these are being expanded to professionals with a non-technical background as well. While there are many positions with a shortage of ideal candidates, it has made it quite possible for one candidate landing up with more than one job offer in hand for similar roles.

That’s why it is necessary to ask questions about:

  1. Responsibilities
  2. Tools used
  3. Methodologies used
  4. Type of data used in the organization
  5. Time spent on aspects of the role like analysis, data management

 Keep Upskilling

To keep up with the changing times, most organizations try to hire candidates who have a definite willingness to learn and up skill. Companies in 2019 are focusing on not just training a single skill but a cluster of skills which will be relevant for more number of years. Some of the skills that are currently picking up are:

  • Automation
  • RPA
  • Robotics
  • Cybersecurity
  • Artificial intelligence
  • IoT
  • Connected devices
  • FinTech
  • Data analytics
  • Blockchain

 

All the above given points will help you in becoming a data science professional.

                                               

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