How can a fresher start a career in Data Science?

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from noisy, structured, and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains. As for 21 st century with growing development in technology Data is often quoted as new Gold. A career in Data Science is going to be one of the most exciting and rewarding career options in the coming days. In this space, we have covered Detailed information regarding Careers in Data Science for Freshers.

Starting and navigating through the data science career can become a daunting challenge for beginners due to the abundance of resources. It is not rocket science, it is Data Science. What you need is proper guidance and a roadmap to become a successful data scientist.

Choose the right role

There are a lot of varied roles in the data science industry. A data visualization expert, a machine learning expert, a data scientist, data engineer, etc are a few of the many roles that you could go into. Depending on your background and your work experience, getting into one role would be easier than another role. For example, if you a software developer, it would not be difficult for you to shift into data engineering. So, until and unless you are clear about what you want to become, you will stay confused about the path to take and skills to hone.

Take up a Course and Complete it

The demand for data scientists is big so thousands of courses and studies are out there to hold your hand, you can learn whatever you want to. Finding material to learn from isn’t a hard call but learning it may become if you don’t put effort.

What you can do is take up a MOOC which is freely available, or join an accreditation program which should take you through all the twists and turns the role entails. The choice of free vs paid is not the issue, the main objective should be whether the course clears your basics and brings you to a suitable level, from which you can push on further.

 Choose a Tool / Language and stick to it

It is important for you to get an end-to-end experience of whichever topic you pursue.After all, tools are just a means for implementation; but understanding the concept is more important.There are various guides/discussions on the internet which address this particular query. The gist is that start with the simplest of language or the one with which you are most familiar. if you are not as well versed with coding, you should prefer GUI based tools for now. Then as you get a grasp on the concepts, you can get your hands-on with the coding part.

Focus on practical applications and not just theory

While undergoing courses and training, you should focus on the practical applications of things you are learning. This would help you not only understand the concept but also give you a deeper sense of how it would be applied in reality.The best way to build your machine learning profile is to participate in data science competitions and get a feel for data science projects.

Work on your Communication skills

People don’t usually associate communication skills with rejection in data science roles. They expect that if they are technically profound, they will ace the interview. This is actually a myth. Ever been rejected within an interview, where the interviewer said thank you after listening to your introduction?

Try this activity once; make your friend with good communication skills hear your intro and ask for honest feedback. He will definitely show you the mirror!

Communication skills are even more important when you are working in the field. To share your ideas with a colleague or to prove your point in a meeting, you should know how to communicate efficiently.

Basic Database knowledge and SQL is a must

Data doesn’t magically appear in the form of tables. Usually, beginners start their machine learning journey by using data in the form of CSV or an excel file. But something is definitely missing! It’s SQL. It is the most fundamental skill for a data science professional.

Knowledge of data storage techniques along with the basics of big data will make you much more favorable than a person which hi-fi words on the resume, it’s because organizations are still figuring their data science requirements.

These organizations want SQL professionals that can help them with their day-to-day tasks.

 Guidance is essential

Coming to the final point which is perhaps the most crucial one – finding the right guidance. Data Science and machine learning, data engineering, and relatively a very new field and so are its alumni. There are only a few people who have decrypted their path in this field. To master Data Science Skills visit Job Oriented Courses

There are many ways to become a data scientist, the simplest one is to cough up lakhs of rupees for a recognized certification only to later get frustrated with the recorded videos or even follow along with a youtube playlist but you are still not an industry-ready professional.

Find a mentor who has navigated his career in the field of data science and ask them how they did it, what’s the best way for you to become a data scientist?

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