Who are non-technical people? Those without an engineering degree? The journey for these people to become a data scientist is not very different from the technical ones. To be in the Data Science Industry, one needs not to be a top-notch engineer with in-depth knowledge of complex topics but should have an eye for data, enthusiasm for learning new things and telling stories with numbers. We are living in data generation- a world full of data. Currently, 2.5 quintillion bytes of data are being created every day, and it is expected to grow more. The industry has witnessed continuous growth in the last few years and is expected to reach $77.6 with a 30% CAGR by 2023. Not only technical organizations, but every industry is moving to data-driven decision making. Therefore, the demand for data scientists will keep growing shortly.
Table of Contents
- About Data Science
- Learning the skill
- Practice
- Conclusion
Everyone is enchanted by the innovation and problem-solving talents of the data scientists. This article looks at how non-technical people can become a data scientist with the best data science certification.
About Data Science
The current Chief Data Scientist of the United States and former Head of Data Products at LinkedIn coined the term ‘data science.’ According to him, the dominant trait among data scientists is the desire to go beneath the surface of a problem, find solutions, and form a clear set of the hypothesis due to intense curiosity. There is no strict profile definition for a data scientist. One of the most famous data engineers and the creator of the Hadoop framework is a Linguistics graduate. Tim O’Reilly- founder of O’Reilly Media and the curator of thousands of programming and data resources- graduated in Classics. This testifies the fact that data science is not only for people with technical degrees. The curiosity drives them to take up challenging problems and pull out new insights from old datasets.
The global revenues for business analytics and big data are set to reach $210 billion this year. Due to an increase in demand, there will be a shortage of data science professionals. Thus, firms are reaching out with open arms to those wishing to embrace the industry and join the workforce. However, the gap between the required skill and existing skills is enormous, which has fueled the gap between supply and demand. No doubt, it is a lucrative job opportunity and is set to grow and permeate into other fields regardless of the gap. If you are looking to close the gap and jump from a non-technical background to data science, these tips will guide you to get into the industry and ace the competitive job interviews.
Learning the skill
Data science is a complex field that can be applied across various industries. To get a jumpstart in the field as a beginner with no background knowledge, candidates must upskill by enrolling in the best data science programs online, which is well-outlined. A data science course curriculum includes basics of programming in R, Python or Java, Deep Learning, Data Visualisation, Big Data handling, Statistics, and probability. This is the easiest and the most organized way to approach learning about the field because otherwise, it would be time-consuming to gather relevant sources and find a starting point. It is nearly impossible to learn all skill sets within data science. Some skills are based on people-handling and experience, so the best place to start is taking up the best online data science courses. These courses are usually created by experts in the field and come with the added benefits of mentorship programs and career counseling.
Practice
Once you achieve the best data science certification and learn different tools and skills, the next step should be practicing in real-life situations. The best way to substitute for the degree and lack of demonstrated technical knowledge is by creating real-time projects that impact. As an aspiring data scientist, a portfolio of projects can help you get notices and build credentials. This is the way to apply your skills and improve at an accelerated pace. Take a substantive problem and see if you can come to a solution based on hidden insights of data such as predicting electoral results, tracing a sportsman’s performance to tweet sentiment analysis. One can take any dataset and lend a fresh perspective to it with the new skills. An online degree in data science can give you a structured curriculum with plenty of practice and feedback in the form of assignments and exams. The structure is essential because of the broad nature of data science. Global Tech Council offers the best online certificate programs that can serve as your curriculum.
Conclusion
Data Science is a fast-paced field, and the trends are changing every day. It is imperative to continually self-educate and understand new learning trends. As a non-technical person, it is essential to keep reading articles, blogs, books, and research papers to learn new tools. This is imperative to stay relevant in the competitive market. Recruiters are looking for self-learners that can contribute to the field. It is not difficult for non-technical people to be a part of the data science industry. The domain knowledge of the current area of work of non-tech people serves as an added advantage, like one working in Finance can become an Expert Financial Analyst by learning analytical skills. The industry is vast, and there is an innumerable number of opportunities for all data enthusiasts. Start learning today with the best data science programs online.
