Being one of the highest-paid tech jobs ever, data science has rapidly become a popular career option for many. With the growing possibilities of emerging technologies, data science has come to be a relevant field of research and work. According to a survey, the data science and analytics ecosystem have been witnessing an overall growth in the number of jobs with India contributing to 6% of open job openings worldwide. And therefore, not surprisingly, many students and college graduates are gearing their education towards a career in data science.
Just thinking about the first step can leave any student dazed and confused, especially if you lack previous experience in the field. In this article, we will discuss ten things that a student should consider before pursuing a career in data science.
Pick A Relevant Major
Although many experts have mentioned that degrees aren’t important for a data science career, it indeed requires strong skills in statistics, maths, and programming. To have an early kickstart to your data science career, students need to focus on topics like statistics, computer science, physical sciences, linear algebra and calculus, and social sciences for their choice of major. Choosing a STEM major at an early stage of a career will let the students’ brain expose to the field early and will create a solid base in applied math and statistics, which is a key skill for analysing the large volumes of data and data trends collected by big companies.
Books Are The Best Tools
Although there are several internet resources that one can use to learn data science, books are still one of the best tools to learn from. One of the issues students of this era face when trying to get into a new field is the overload of information available, which, in turn, confuses students who are totally novice. If one has to check, there are hundreds of online courses, specialisations, videos, podcasts etc., but it is best that students, who are willing to learn about this new field, pick a book and start learning the basics concepts, and then keep filling the gaps with other resources. And thankfully, the community of data science is very open and giving, so there are a ton of books students can opt from to learn more about data science that students can enjoy without paying a considerable sum from their pocket.
Create A Personal Project
Learning shouldn’t be contained to the classroom, rather the best way to learn something new is to apply what is learnt in the classroom into something you care about, like creating a personal project. Data science is not about learning tools and techniques; in order to become a data scientist, students need to build a portfolio by working on real projects — maybe independently on platforms like Kaggle. In fact, if data science enthusiasts aren’t equipped enough to design their independent projects, they can even opt from premade projects and tutorials online that pose problems for students to solve. Such possibilities will let students get hands-on experience without investing in expensive tools or training.
Enhance Your Computing Skills
Computing skills are essential, not just for the field of data science but to survive in today’s world. Experts believe that “Computer codes attributes for more than 80% of our lives today.” And therefore, learning about programming and coding will not only help you in making software, apps or websites but will also allow the students to understand how technology impacts our lives. And, for the future, these computing skills will help you learn advanced programming skills that are extremely important for job perspective. No matter what type of role you’re interviewing for, candidates will be expected to know the statistical programming language, like R or Python, and a database querying language like SQL.
Opt For Online Courses Early
Online classes can be a great way to quickly learn about data science, from technical skills like Python or SQL to basic data analysis and machine learning. That said, you may need to invest in getting the real deal of effort to study online courses, as it not only requires a heavy sum of money but also needs immense discipline to find the right course and finish it in time to gain the returns of investment. In fact, there are several courses and tutorials available online that it is perfectly possible to gain a thorough understanding of this subject. Some of these materials are even developed and distributed by the world’s leading universities, while some are also put together by experts and experienced professionals. One can choose the right online course for themselves and begin their journey of data science.
Join A Peer Group
Although students need to read articles written by data science professionals or watch tutorials and videos on data science, it’s also important if students and data science enthusiasts can have face-to-face conversations with people and experts of the field. Joining a peer group keeps enthusiasts motivated, as learning a new field may seem a bit daunting when you do it alone. The preferable way to join a peer group is to have a group of people one can physically interact with; however, students can also find people over the internet who share similar goals and can still have a meaningful technical discussion. In fact, peer groups are the best way to keep updated with the latest news and updates on different technology related to the field. One can also go to a data science conference or attend interesting talks by experts of the field. Actually, a meetup can be very beneficial for students when it comes down to making your mark in the data science community.
Follow Right Resources
To never stop learning, students should engulf with every source of knowledge they can find. In today’s world, there isn’t any shortage of information for one to learn data science — such as podcast, webinars given by data scientists, data science articles, various online courses, and engaging with data science community — however one has to filter out the noise and should only follow the right resources to gain the maximum advantage from the heap of information available. One can even follow the blogs run by most influential data scientists, who are active in the industry and also update their followers about the recent advancement in this field. Developing relevant resources will provide students with pertinent information about the field, and in turn, the students will not be overwhelmed with the information provided.
Work On Your Communication Skills
People don’t usually associate communication skills with data science roles, and it is considered that to be a good data scientist one has to be only technically profound. In reality, this is a myth. Like any other field of the IT industry, data science also requires excellent communication skills. Communication skills are even more critical when you are working in the field of data science, as data scientists need to share their ideas to their colleagues and other teams, and having good communication skills help them to have smooth communication with the rest of the organisation. Whether it is to understand the business requirements or to communicate business insights, a data scientist needs to have good communication skills to be persuasive in front of stakeholders. Often underestimated, this is one of the most important skills for the simple reason that all statistical computation is useless if the teams can’t understand, communicate, or act upon it.
Don’t Jump Into The Deep End
Some young enthusiasts and students enter this field with a vision to build a technology of the future or to directly become the next tech genius with their self-driving cars, advanced robotics, computer vision, and so on. However, usually, people forget that it’s important to first master the fundamentals of data science. For a student who is willing to pursue a career in data science needs to be completely aware of the field, basics as well as advanced knowledge before they actually start to dream about building revolutionary technology. Some of the fundamental steps towards data science is learning the basic techniques and algorithms, which serve as building blocks for advanced topics, along with the components and the application of data science in solving business problems. Students should learn a systematic approach to structuring machine learning projects.
Peruse The Job Market
Being a student, it might seem premature to assess the job market now; however, it’s always valuable to have an idea of the companies that typically hire data scientists and the skills they are looking for in their candidates. Such a piece of knowledge will help students in shaping their choices of courses and skills for future perspective. Moreover, learning about the job market can help you find out whether certain cities or regions have higher or lower data scientist job openings. Then, as students continue to plan their careers, they can easily measure the likelihood of their placement for the future. Staying relevant and aware is crucial to the ever-evolving field of data science, and therefore students should also be mindful of their future job perspective. In this age of constant technological innovation, continuing education is a hedge against shifts in the career market. A career-oriented data scientist is always learning and evolving with the industry.