Geoffrey Moore once said, “Without big data analytics companies are blind and deaf wondering on the web like a deer on a freeway” and we could never agree more.
What does it take to become a data scientist in the era of digitization? If you want to know the answer to this question in short then you would hear “a lot”. There are several factors that contribute to the journey of becoming a data scientist and if you are searching for more information on these factors, then below blog is what you need. Through this blog, you will comprehend what it takes to become a data scientist? How online training and certification can help you become a data scientist? What data scientist do?
The data science has extended to a level that a recent job survey highlighted that there are currently more than 97,000 jobs available for the data scientist. This growing demand for the data scientist has made the job title falls into the category of the “hottest job list” that pays a good salary. Although, data scientist jobs has become a buzz word in the industry only a few understand what it takes to become a data scientist. Here you will teach the step-by-step guide to become the data scientist. However, it is a challenging journey but in the end, it worth it!
Step-by-step guidance to become a data scientist
- Begin with the mathematics and statistics
If you are willing to become a successful data scientist, then you must have a strong background in mathematics and statistics. In the middle of the data-driven world, the basics are somehow getting neglected by all. The boom in the data world needs executives to have mathematic and statistics skills. Some of the most basic concepts that data scientist aspirants must know are causation, correlation, and how to test the hypothesis.
Students who are at the beginning stage must cover the basic understanding of linear algebra, and calculus as working on these subjects will make your foundation strong.
- Practice programming on a regular basis
As per the fundamental studies, data researchers have found that Python is one of the highly recommended programming languages for the data scientist. Therefore, beginners who are still developing their knowledge and skills in data science should start focusing on Python programming. Once, you have a good understanding of the Python programming, you can start learning other programming languages as well like R and Java.
- Test the waters for machine learning
The most common mistake people make when it comes to Machine Learning is they learn every algorithm without knowing where they will use them. As for beginners, it is highly suggested to learn popular and standard algorithm because not every single time a complex algorithm is not a solution to the problem.
- Work on machine learning projects
The learning is just the beginning phase. An aspirant should know how to implement the knowledge and skills you have obtained to real-life projects. Always remember, the skills you have obtained will only be recognized or appreciated when it is represented in front of everyone. Take up the live projects to understand what it is like to work within the strict architecture.
- Create a strong portfolio
A resume is an important component to showcase your skills in front of employers. Moreover, the data scientist should be able to showcase his or her ability in the form of coding and other software abilities.
In the end, if the above information is not enough, then you can consult with the experts at the ProICT Training.