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Last Updated: Mar 27, 2024
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Tips to Become a Data Scientist

Leveraging ChatGPT - GenAI as a Microsoft Data Expert
Prerita Agarwal
Data Specialist @
23 Jul, 2024 @ 01:30 PM


Technology now is emerging at a pace which we have never seen before. So is the need to interpret data flowing from the technology. This indicates that the candidates who are working with analytics and data science have to continuously keep themselves up to date with the current events in the industry after getting a professional qualification. Learning data science can be challenging, but it is rewarding, too. After all, a data scientist is ranked as one of the best job roles by Glassdoor since the past three years in a row.

The need for highly skilled and smart people is going to rise with the rise of big data. Pursuing your career in data science without any guidance can be a bit confusing. Which tool to use? Which technique to use? The questions are endless.

Here are some data science tips that will help you if you’re about to start learning data science:

Choose the right role: 

Rather than recklessly jumping into a decision of which role to choose, take your time to understand the requirements of the role. From a data visualization expert to a machine learning expert or a data engineer, the role of Data Scientist entails a varied amount of tasks. We would like to suggest a few things you can do beforehand:

• Find out the field that you’re close to from your past experiences or the most relevant role which you can excel.

• Talk to a professional who has been in this field for a long time.

• Make someone your mentor from the industry to guide you and help you choose the right role for you.

Take courses: 

Now that you are all done with choosing the role, the next thing you do is to understand the role entirely. Since the demand for data scientists is highly increasing, there are a lot of courses out there to look forward. You have both, paid and free classes. Now, remember, while taking online courses to be sure if it has good reviews. You can also get help from your seniors to know which direction can be beneficial. Even when you take up the course, go through it actively. Engage in every coursework, assignment and all the discussions happening around the course.

Choose a language/tool: 

This might be the most commonly asked questions from a beginner that which language to choose and with which tool to stick. The answer is simple, go with the one that you are familiar with or if you don’t have had any experience with coding yet then go with the simple one. After all, tools are just a means for implementation; the primary thing is to understand the concept.

Join a peer group: 

After choosing a language to continue with the next thing you should do is join a peer group. Not only the group members help you study but also keep you motivated throughout. Starting your career in  Data science can be intimidating but having a bunch of people doing the same thing besides you can make it much easier.

Even if you don’t have such people around, you can always join a massive online course and talk to people online. Trust me; there are a lot of people in it.

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Focus on practice and building applications: 

During the course try and have a practical approach towards the projects assigned rather than theoretical. To stay on the top of the skills, you have to keep yourself updated with all the new tools that are continually coming out. Start with easy projects first.

• You can start with the projects assigned to you in the course.

• Explore the projects which are already solved by the experts.

• Instead of following a theoretical approach, look for online tools that help you code as you learn.

Follow the right resources: 

It is essential for a data scientist to know that the skills sets that are applied to be a data scientist are constantly shifting. So to keep a pace with that, follow the most influential professionals of this field. Read their blogs, attend seminars and meetups arranged by data scientists. As it is one of the most searched topics nowadays, scientists are actively participating in updating their blogs and updating us with the recent happenings. Make sure you don’t follow the wrong resource as it harms your career.

Work on your communication skills: 

Working hard on your communication skills might not associate with the fact of being a data scientist. But actually, it is one of the most important aspects as you have to communicate with a lot of people from the industry and within the organization, as you are the one who will keep them in the loop of the growth of your company. And to do that you have to communicate effectively.

Like we said earlier, the demand for upskilled data scientists is only going to increase with time. So, if you are planning to explore the career, there couldn’t be a better time than now. You can also consider our online coding courses such as the Data Science Course to give your career an edge over others.

Topics covered
Choose the right role: 
Take courses: 
Choose a language/tool: 
Join a peer group: 
Focus on practice and building applications: 
Follow the right resources: 
Work on your communication skills: