Shift Your Career To Data Science
Are you thinking of making a transition to data science from your existing career? If yes, then you may have a lot of unanswered questions about the skills needed, the language or tools to learn, and basically where to start. This guide will help you through this career transition:
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Tips to Shift to Data Science Career
At the outset, it is important to understand that you don’t need to have a technical background to have a data science career. All that is needed is to be curious and dedicated to learning and hunting for information.
This itself should act as a motivation especially to those from a non-technical background to make the move to data science. Listed below are some effective tips that you can incorporate:
Enroll for a Course
Learning data science can be a huge challenge given that there are numerous aspects to cover. There are many tools, languages, techniques, data structures, etc to learn and understand. If you are doing all the learning by yourself it may become complicated as there are lots of materials available online.
Choosing the one that is relevant becomes difficult from this sea of information. Hence it is recommended that you opt for a well-designed course that covers the basic concepts. An ideal course will include programming language basics of Python/R, data structure concepts, visualization, statistics, handling Big Data, and deep learning.
Apart from theory, focus on completing assignments and worksheets for practical learning. After attending the course you can go csm training which will add more value to your CV and boosts the chance of getting a job.
Take Kaggle Challenges
One of the best ways to learn is to look at the Kaggle competition kernels. It is a place where Kaggler’s upload solutions to problems posed in its competitions. Understand the code and run it to see what the code does.
It may seem frustrating in the beginning as it is not easy to understand the code, but with time and patience, you can crack the code. Set specific and realistic goals and make it time-bound as you cannot finish taking these challenges in a week.
Find a Project to Work on
There is nothing better than getting some practical experience after learning the theory part. If you are unable to find projects online, find one for yourself. The best way to look for projects is through community discussions.
Get ideas from their problems or issues and work on them. It can also be a problem that you want to solve or a concept that you are passionate about. Convert it into a project so that you can showcase it on your portfolio.
Learn to Talk and Think like a Data Scientist
Learn how the data scientists speak and what jargon they use as that will help in communicating with peers in the future. If you are not aware of some terms, make a note of it and search or ask around. Thinking and speaking like one is also a step towards learning.
Transitions are never easy, be it in your life or career. But with strong basics, methodical approach, curiosity, and constant reading making this career switch can become easy. The move will definitely be worth it as it helps in your career growth greatly, even if you are from a non-technical background.
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