Advice To Aspiring Data Scientists
Learning data science can be daunting, especially, when you are a beginner. Which tool to learn –Python or R? What techniques to master on? How much statistics should I know? Do I require learning coding? These are some of the questions you need to answer as part of your journey.
In the following paragraphs, we are going to discuss how you can kick start your career as a beginner in the field of data science.
1. Choose the right role
There are a lot of different roles in data science industry. A machine learning expert, a data scientist, a data visualization expert, data engineer etc. are some of the professions you can choose. Based on your educational background and professional experience, getting into each role will normally have a different level of difficulty. For instance, if you are a software developer, it would not be challenging for you to shift into data engineering. Therefore, until and unless you are sure about which role you want to choose, you will be confused about the path to take and skills to master.
2. Take up a course and complete it
Now that you have chosen a role, the next logical step for you is to devote your efforts to understanding the role, which means going beyond simply the bare necessities. The requirement for data scientists is big and hence several courses and studies like Data Scientist Bootcamp, etc. are out there to hold your hand. Finding the right material to learn from isn’t a difficult task but learning it may become so if you don’t put enough efforts. Therefore, when you take up a program, go through it keenly. Follow the study materials, assignments and all the discussions tasking place around the program.
3. Choose a Tool / Language and stick to it
As discussed above, it is essential for you to acquire an end-to-end experience of whatever topic you pursue. A difficult question which the beginners face in getting hands-on is what language/tool should they choose? The most appropriate answer would be to pick any of the mainstream languages/tools there is and begin your journey into the world of data science. After all, tools are just means for application; but understanding the idea is more important.
4. Focus on practical applications and not just theory
While undergoing programs and training, you should concentrate on the practical implementations of things you are learning. This would assist you not only understand the idea but also give you a deeper knowledge on how it would be practical in reality.
The demand of data scientists is vast and employers are investing substantial time and money in Data Scientists. Therefore, taking the right steps will lead to a stellar career growth.