How to Become A Data Scientist With No Experience

Data scientists come from various backgrounds and is one of the fastest advancing careers in today’s world. Basically what a data scientist does is that they gather and analyze the data in order to reach a conclusion. This may seem simple but there is more that we will find out in this article. A data scientist collects data using different techniques. Breaking down to very simple words a data scientist looks for meaningful content from a huge mass of data. This is done by creating complex algorithms for determining patterns, obtain meaningful data from a jumble of numbers, and deriving a meaningful conclusion for an organization, business, or other purposes. Via this article let us try to find out How to become a data scientist with no experience.

Duties of a data scientist include collection and cleaning of huge amounts of data, interpreting data to solve problems, maintaining dashboards, run experiments, building algorithms, and presentation of visual data to the collaborator/stakeholder. If this information excites you we would also like to let you know it is possible to become a data scientist with no experience also. 

Check the complete article to find out more on how to become a data scientist with no experience, data scientist job profile, data scientist career, career growth etc.

How to Become a Data Scientist with no Experience – In a nutshell

Yes, you just heard it right! It is completely possible to become a data scientist with no prior experience too. There are high chances that you will come across various jobs that can be only got by possessing a master’s degree or a PhD in engineering, computer science, mathematics, etc. However, it is possible to secure a job as a data scientist even without those. Let us try to see how. Candidates can opt for plenty of online certification courses to upskill themselves. 

Now let us jump on to our main topic, how to become a data scientist with no prior experience.

Upgrading your math skills

Candidates having a decent background can easily build their careers as data scientists. But in order to make it possible it is highly important to get your basics right. Before you switch your career directly from the maths field to being a data scientist you should acquire maximum skills in the following basic fields. They include plotting data points on graphs and finding correlations. There are also certain other areas where you would want to make your basics really strong, they include

• Linear algebra
• Multivariable calculus
• Statistics
• Hypothesis testing
• Probability
• Regression analysis
• Markov chains
• Descriptive statistics

Take a free trial on an online data science course!

Strong knowledge and application of important programming languages

Having just a degree in engineering or other majors will not help you get a job as a data scientist. However, there are certain skills that you need to master in order to get into this field. Your interview for the post will be mostly to test your skill sets and your mastery of the following programming languages. 

• R – This programming language is used for statistical computing and graphics. This is also an open-source programing language. The language also helps in data visualization and calculation of complex statistical and mathematical problems.
• Python – Python is the commonly used programming language for website and software development. It helps in data analysis, visualization of data, automation of tasks, etc. Knowing python will also help you in filtering and transfer of unstructured and big data. 
• SAS – This is the common software mainly used for statistical and data visualization. However, the software is available only for the windows operating system. Large corporations use SAS for statistical analysis, predictive analysis, and business intelligence. 
• SQL – Structured query language is the most commonly used programing language to manage databases and performing various operations on the data. SQL is also a relationship management tool. You can use SQL to join data across various databases.

Upgrade your resume including various internships

One sure short strategy that can help candidates secure a job in this field is showcasing practical knowledge. Candidate can high time impress their recruiters with real-time skills. Companies hire candidates and prefer those having practical experience. Candidates can also upgrade themselves by attending certified programs from various websites. You can make your resume stronger by having real-time knowledge and working with problems in the field. 

elevate your career with data science online course ! join now !

Launch yourself being a data analyst

Confused between data analyst and a data scientist? Indeed they are both different. Responsibilities of data analysts include managing data collection and identifying data trends. However, data scientists also decipher the data. Hence in order to get your hands on this field, you can always start off as a data analyst

Candidates can also try establishing a strong network with people working in a similar field. This will be a great boon while trying to launch your career as a data scientist.  Also check out salary of a data scientist in India.

Strongly explain your career switch reason

It is indeed understood that you want to try your hands on this role because of the constant hype and booming opportunities. However, this is not a solid reason for recruiters to hire you. You will have to clearly explain the reason for your job transition. While explaining your past role try correlating it with your current job interest. Mention the skills you have that can help you flourish for the current role. Perfectly showcase your skills for the job. 

Click here to access the latest data science course!

We hope all these details will help you become a data scientist with no experience. Finally, just keep in mind to be a part of a similar community and have a very strong network. Entri also helps you upskill yourself and secure a job. Subscribe to entri for more articles related to data science and machine learning.

Related Articles