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Successful Data Scientist Without A Tech Degree! Yes, It Is Possible

By Milan Published in Data Science 9-10 mins
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An image portrays a recruiter conducting an interview with two data science aspirants after completing a data science course.

You Can Still Become A Data Scientist Without Any Tech Degree

Technology keeps evolving with discoveries every day. In recent years many interesting jobs have been created with high-paying salaries, and a data science job is one of them. But being a non-stem degree holder, you might lose hope of a successful data science career. The first question that comes to mind is can I become a data scientist without a degree? Well, there is good news for you. It's nothing but a myth. No degree is irrelevant to becoming a demanding data science pro. You can surely become a successful data scientist without a tech degree or you can become a data scientist without a stem degree.

Aspirants without a tech/ stem degree can enroll in the and AI course and land a promising data science career. A course report has found that when it is about the ROI, the coding, and data science boot camps or certifications, they need less time and money and offer equal to better earnings like a professional holding a "CS degree."

To break through in data science as a professional should consist of technical skills, problem-solving talent, and the courage to work with enormous data. Any data science enthusiast with a STEM degree can become a data scientist. All this is just to inform you that whether you are new to data science or you are taking a mid-career leap, there are many roads empty for you to become a data scientist without a tech degree.

DJ Patil was the United States' first Chief in data science. He tweeted, "In Data science it does not matter whether you have majored in or if you even hold a degree. It is what with data that you do is all that what really matters."

Even if a college degree can help you, in reality, many organizations recruit data scientists who do not even have a degree. What matters is that, as Patil stated, candidates should be able to do a job of a data scientist, wrangling big data, understanding multiple programming languages, and performing data analysis. Everything can be learned through a data science course.

How Can One Become A Successful Data Scientist Without A Degree?

An image of a person sitting in front of a laptop, searching for ways to boost their profile as a data scientist without a degree.

To become a data scientist, you need to dedicate ample time and gain a massive edge through portfolio projects and certifications. But if you are enthusiastic and put in your best efforts, you can reward yourself with a great career. You can pursue a job-ready course in Advance Data science and AI.

If you want to become a successful data scientist without a degree, then do the following:

Learn all the basic skills

Statistics and Mathematics are the core foundation of data science. It will enable you to gain usage trends, get meaningful insights from scattered data, and create forecasts. You need to apply mathematics and statistical concepts like variance, standard deviation, probability, calculus, and linear algebra to do all this. So when you start to work on complex problems, you will have to work with logistic regression, linear regression, and decision trees. If you perfect yourself with these skills, you are on the right track to becoming a data scientist, even without a degree.

Get better at data handling skills

A major part of a data scientist's job involves accessing, cleaning, wrangling, collecting, and storing structured and unstructured data. It is even crucial that you know the uses of relational databases like MongoDB and MySQL. Enhance yourself by working with tools like Hadoop or Spark, so you can learn how to process and store big data, and these are very useful for a data scientist in his career. In addition, you even have to learn multiple languages like SQL and Python specifically. The other various languages a data scientist without a degree should know are:

  • Perl for text manipulation and structuring

  • R is for analysis and statistical inference

  • Ingesting, storing, and processing big data by Scala.

Work hard with Data Science projects

When you are comfortable working with key skills and tools, you have to work a little deeper. Test yourself with Kaggle and TopCoder competitions, a data science hackathon. Apply skills when and where you do all of these.

Hands-on projects and capstone projects are the keys to your resume and career. Data science and AI certificates are good, but these projects will make you stand out from the crowd. And this is also where the recruiters are more curious to know about than the certificates or whether you have a degree or not. A data science course must include real-time projects and fresh capstone projects. Learnbay data science course offers a project completion certificate by IBM on the successful completion of capstone projects.

Create A Portfolio

A resume displays what you are capable of, but a portfolio is mostly necessary. If you are starting a career as a data scientist working on real-world projects, it becomes the most important measure. It's your project portfolio that decides your data science career transition's fate.

  1. Work on personal projects Take publicly available but authenticated data sets and develop your dashboard. Identify opportunities and create your case studies.
  2. Look for internships and start-ups , as they are always actively hiring and would be happy to have you on short-term projects. Such training is more valuable than the degree, as it is a real-world experience.
  3. Many government departments, small businesses, and NGOs need data scientists' help. Keep an eye on such opportunities.

An image portrays a recruiter interviewing two data science aspirants who had completed their data science course.

Hone Your Interview Cracking Skills

Data science interviews are one of the toughest ones to crack. The data scientist application process usually involves a portfolio, references, and cover letters. Then candidates undergo interview loops to check applicants' talent and skills for the role. This can involve technical interviews, writing algorithms, SQL coding interviews, and a list of questions that would reveal a candidate's true value.

Work Towards Your Dream of Becoming a Data Scientist

Your first job in data science may not be the one you wish to work for. Getting a foot in the door is more valuable rather than completely moving towards your dream job late. You can improve your data analysis skills, so if you work in data warehousing or management, you can develop your expertise in data structures and databases.It is important to set the right goals that you learn from each role in data science. Everything that you learn technically with soft skills will bring you closer to becoming a data scientist, your dream job role.

Yes, you can learn data science without a degree. It won't take you years to know so. If you feel that you are working too much on math, you can give programming ample time. It will hardly take months to become a data scientist if you choose the right guidance. You can join Learnbay data science and AI training with an interview guarantee, where you get live classes from MAANG experts. This course includes real-world capstone projects and even helps you build your resume and portfolio.

So why wait? Jump into the world of possibilities. Best of luck.


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