With a hot job market, lucrative salaries, and promising career openings, it’s a great time to become a data scientist. But what if you’re starting from scratch? Luckily, there is a myriad of different learning paths. You can learn skills in the field in numerous different ways — from getting a college degree to attending boot camps to learning yourself. Not sure where to start? In this article, we’ll show you how to go from being a novice to being job-ready in the field of data science.

Why Data Science?

.Data science has risen to the forefront of the software industry because companies have begun to understand the importance of data. Sourcing and processing data effectively is a must-have for growing organizations moment. Companies leverage data scientists to generate insights that can help them outmaneuver the competition and multiply profits.


Because of this, the field of data science is seeing an abundance of opportunities. The American Bureau of Labor Statistics has projected that the field will grow by almost 30 through 2026. That’s partially why US News has listed “ Data Scientist ” as one of the top three technology jobs.


With companies competing for the best gift, salaries are rising. The University of San Francisco reports that the graduates of its MS in Data Science program earn a median salary of$. More than 90 graduates have landed a full-time role within three months of completing the program.


Before you dive headfirst into the world of data science, you may be wondering what does a data scientist do? Let’s find out.


A data scientist turns data into meaningful insights. These insights guide upper management when making business decisions.


Data science starts with the collecting and cleaning of data. The latter is necessary because data when it’s first sourced doesn't come in a form that’s easy to analyze. There are generally missing entries, corrupted volumes, etc. So data scientists use statistical styles and engineering skills to clean that data.


Also, they conduct an exploratory data analysis, in which they look for patterns in the data. Data scientists do this by writing algorithms and creating models which can be used to run experiments on datasets and uncover useful insights.


Data scientists also communicate their insights to other teams and management. This frequently requires data visualization and donation skills.


To summarize, here are some of the tasks assigned to data scientists


Identify opportunities where data can be used to solve problems.

Source data that can be precious in working on the problem.

Clean the data and ensure that it meets the organization’s norms for data accuracy.


Employ algorithmic approaches and make models to induce perceptivity.

Use data visualization and storytelling to convey findings to colorful stakeholders.

Now that we know what a data scientist does, let’s look at how to learn data science if you’re just starting in the field.


Build a Strong Foundation in Statistics and Math

Like numerous other technology disciplines, the calculation is foundational to working in data science and will give you a strong theoretical foundation in the field.


When working in data science, statistics and probability are the most important areas to grasp. Most of the algorithms and models that data scientists make are just programmatic performances of the statistical problem-working approaches.Still, you can start with a 101 course, If you’re a beginner with statistics and probability. Use this as an opportunity to learn basic concepts like friction, correlations, conditional chances, and Bayes’theorem. Doing this will put you in a good position to understand how those concepts translate to the work that you'll do as a data scientist.



Author's Bio: 

I am a content writer from 4 years. I love to share my knowledge through writing. I work for fashion, travel, education, food and etc.