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How to land a job in data science as a beginner?

by Jakaria
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How to land a job in data science as a beginner?
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Data science is an in-demand career field with strong job prospects, and believe me, now is the best time to step into this field. And the best part if you don’t even need prior experience to become a data scientist.

There are plenty of ways to acquire the skills needed to become a data science on your own. But again, getting skills and then a decent job is a different thing. It’s not that easy to get a decent job be it in any field. Below you’ll find steps that will help you to break into data science without previous experience.

Also Read: 7 Best WordPress Plugins To Use For Better Ranking In SERP

Step 1: Polish your math skills
For individuals coming from a quantitative background, data science should be an easy shift. But for individuals who don’t have a mathematical background should focus on improving their mathematical skills because mathematics plays a vital role in data science.

In the data science process, before analyzing data with high-tech tools, data scientists are required to get to the foundation of data analysis, which begins with plotting data points on graphs along the X and Y axes and finding trends and correlations between different variables.

To make sure you can draw accurate conclusions and write efficient codes, here are some suggested mathematics concepts you should master:

Statistical modeling and fitting
Data summaries and descriptive statistics
Regression analysis
Bayesian thinking and modeling
Markov chains
Statistical methods and probability theory
Probability distributions
Multivariable calculus
Linear algebra
Hypothesis testing
Step 2: Learn one or two programming languagesCode, Programming, Python, Programming Code, Coding
Once you have a solid foundation in mathematics, you can start to pick up a few of the must-know programming languages for data science i.e, Python, SQL, R, and SAS.

Python is used for software development, web development, deep learning, and machine learning. Python is the most generally used language in the field of data science.
R is useful for complicated statistical and mathematical calculations. It is also useful in data visualizations and has a great support community to help you get started.
Step 3: Take on side projects or internships
Companies will ask to see your professional practical experience. So, as you start building your skill base, make sure you are applying your skill set in real-world settings. For that, you can join internships. Internships are a great way to implement skills in the real world as well as a great way to learn new things right from the experts. It will also build your resume.

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