How to become a Data Scientist after 10th?

What is Data Science?

Data Science is the field of extracting data from large volumes of datasets and transforming them into meaningful insights so that effective decision-making takes place. The field is exponentially growing in the market with millions of job opportunities in different job roles. Based on the lucrative opportunities, many of you are aspiring to become Data Science experts and want to learn Data Science.  With the demand for Data Science rising, students are willing to pursue Data Science, immediately after their 10th. There are various online Data Science courses that you can consider in Data Science after 10th that includes Data Science Course for Teenagers. So, how to become a Data Scientist after 10th? Let’s find out from the blog!

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Steps to Become a Data Scientist

If you want to pursue a Data Science course after 10th, you need to ensure that you are aware of the steps that can help you become a Data Scientist. Following is the Data Science Roadmap that you need to know:

Learn Data Wrangling, Data Visualisation and Reporting:

For dealing with complex datasets you need to learn the skill of Data Wrangling which will help you clean, organize and transform data into an understandable format. Using Python libraries like pandas can help you better in the process. Additionally, presenting the data in a meaningful form and reporting it to the executives requires data visualization and reporting skills.

Improve skills in Statistics, Math, and Machine Learning:

You do not need to have a degree in statistics or mathematics but having fundamental knowledge on the topics of linear algebra and probability is important. For instance, calculus can help with optimizing ML algorithms. Hence, developing your skills in these areas is essential.

Learn Coding:

Programming language is one of the most crucial skills you need to learn Data Science after 10th. Accordingly, make sure that you have Python and R as part of your high-school course or online course in Data Science. It will help you work with large datasets better and more efficiently.

Understand Databases:

SQL is useful in handling structured data, query databases, and preparing and experimenting with data. Accordingly, SQL is deployed alongside Python and its libraries thus, requiring you to develop your skills in using SQL.

Learn working with Big Data:

In order to become Data Scientist, working with large datasets is a given. From large datasets, experts can extract meaningful insights. Learning the use of cloud platforms like AWS, Microsoft Azure and Google Cloud can benefit your career as a Data Scientist.

Get Experience, Practice and Meet Fellow Data Scientists

With hands-on experience in using different tools of Data Science and applying your skills requires immense practice through projects and assignments. By participating in Data Science workshops it is possible for you to develop your skills effectively and meet fellow aspirants.

Take an Internship:

The best way to enhance your skills and learn about the market in Data Science is when you develop your skills by practicing in the real world and learning from senior and experienced professionals.

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Engage with the Community:

You need to engage with the various online Data Science community who provide their insights and share their experiences in Data Science. Engaging with the community will allow you to expand your knowledge and interaction with fellow Data Scientists in the market.

Data Science Courses by Pickl.AI

One of the leading platforms for Data Science courses online is Pickl.AI. the online education platform allows you to become an industry expert through its myriad of courses that help you learn from fundamental skills to advanced knowledge. Pickl.AI offers Data Science courses including Data Analytics, Machine Learning, and programming languages like Python, and help you become a professional in Data Science. Pickl.AI believes in practical and hands-on experience being the core principle for becoming an efficient Data Scientist.

Accordingly, you will have exposure to assessments where you deal with real-life case studies through Capstone Projects and the Data Science Job Guarantee Program also offering you with one-month internship which will help you gain real-world experience. Additionally, Data Science course for Teenagers offered by Pickl.AI is especially targeted for those aspirants who want to pursue Data Science after 10th. Significantly, the Data Science course duration is of 2 months which has a comprehensive curriculum from Data Mindset to Machine Learning and Python. Moreover, you need to know that this Data science course after the 10th is mainly for ensuring that students have foundational concepts developed from a young age.

data science course for high school kids

Why Should Kids Learn Data Science?

There are various advantages of the Data Science course which you need to be aware of, allowing your kids to enroll in the Data Science course after the 10th. Accordingly, the following are the advantages of becoming a Data Scientist:

  • Career Growth: Data science courses can help kids start a career from the time they are just teenagers. Consequently, they will be able to learn the basics of Data Science. effectively. It will help their potential to grow and stand against the competition.
  • Flexibility and Options: there are many options to get certified in the field of Data Science.  You will always find work in this field. Consequently, the flexibility in the field enables you to opt for a career in different fields. These fields may vary from healthcare to marketing. Data Science course for teenagers will help in choosing their interests in the field and opting for a suitable career.
  • Structured Program: Data Science Course for high school students is a course that includes a structured program. It allows kids to learn by watching videos and lectures. With practical demonstration through videos, kids are better able to understand their lessons and will be able to succeed through their course.
  • Applying theory to Business problems: as kids opt for Data Science course after 10th they have the ability to learn various theoretical concepts. These will further help them to apply their concepts to practical and real-life business problems thus, being able to demonstrate their skills better.

Conclusion

Thus, a Data Science course for teenagers can be highly beneficial in the career growth of kids where they learn from high school-level, concepts of Data Science. The blog was able to provide you with an understanding on why should you prepare for Data Science in high school. It will help you in embarking on a Data Science journey, expanding your skills and capabilities from a young age, hence, shaping your career.  

Frequently Asked Questions

You do not need to possess a degree in order to become a Data Scientist. However, you definitely need to complete your 10+2 level of education with a specialization in different technical subjects. Furthermore, pursuing a Data Science course for teenagers might additionally help you with the same.

The minimum age to become a Data Scientist is 18 which means that you need to have completed your high school for getting a job in the field.

Yes, an Arts student can become a Data Scientist given the fact that you pursue a certification course in Data Science. The course does not require you to have a technical background. However, pursuing a Data Science course online will only help you develop your skills.

Students pursuing Data Science can benefit in terms of career growth, flexibility, and options for job roles. Additionally, you can also learn Data Science tools, apply theory to business problems and remain updated with the latest industry trends.

Data Scientists typically have a strong background education in Mathematics, statistics, and computer science. Effectively, your background should consist of science, technology, engineering, and mathematics (STEM) which is the ideal background.

Aishwarya Kurre

I work as a Data Science Ops at Pickl.ai and am an avid learner. Having experience in the field of data science, I believe that I have enough knowledge of data science. I also wrote a research paper and took a great interest in writing blogs, which improved my skills in data science. My research in data science pushes me to write unique content in this field. I enjoy reading books related to data science.