How to Become a Data Scientist While Staying in School
Are you a 12th-grade PCM student who is interested in becoming a data scientist? While you still have time to complete your Bachelor's degree, the path to becoming a data scientist is both exciting and attainable. In this article, we'll explore the best courses, necessary prerequisites, and a detailed roadmap to help you get started on your journey.
Best Data Science Courses for Beginners
One of the best online courses you can take is the 'BSc in Programming and Data Science' offered by IIT Madras. This course is highly cost-effective and provides valuable content that can set you on the right path. If you are looking for an affordable and quality-focused program, this BSc is a great choice for you.
Essential Education Background for Data Science
To become a data scientist, you should ideally pursue a Bachelor's degree in a tech field, such as Computer Science. However, it's important to note that a Bachelor's degree is not the only requirement. A Master's degree can significantly enhance your career prospects, providing you with advanced knowledge and skills. Additionally, enrolling in data science courses online will help you develop and refine your skills in this field.
Data Science Roadmap
Step 1: Basic Mathematics and Statistics
Building a strong foundation in mathematics and statistics is crucial. Start with basic mathematics and gradually move towards more advanced topics in statistics. Statistics goes beyond just mean, median, and mode; it includes a wide range of concepts such as z-tests, t-tests, chi-square tests, hypothesis testing, ANOVA, and various types of distributions. Most importantly, you need to apply these concepts on large datasets to truly master the subject.
Step 2: Learning a Programming Language
The next step is to learn a programming language, preferably Python or R. Python is highly recommended due to its user-friendly interface and vast library support. You can use tools like Jupyter Notebook or Google Colab for a seamless experience. Start with the basics of Python and gradually explore its libraries such as NumPy, pandas, Matplotlib, Seaborn, and scikit-learn. While all these libraries are important, focus on NumPy, pandas, and Matplotlib, and apply them to large datasets.
Step 3: Machine Learning and Deep Learning
Once you are comfortable with the basics, it's time to move on to machine learning. There are countless algorithms, so don't get overwhelmed. Dedicate a minimum of 15 minutes daily to writing code and practice. Consistency is key in the world of data science. After gaining a solid foundation in machine learning, you can start exploring deep learning. Give yourself ample time to understand and implement these concepts.
Step 4: Database Management
Now that you are ready to work with large datasets, you need to learn about database management systems (DBMS). Start learning the basics of SQL, which is crucial for querying and manipulating data. Understanding and working with databases will greatly enhance your capabilities as a data scientist.
Step 5: Practical Experience and Projects
To strengthen your resume, it's important to gain practical experience. Look for opportunities to work with startups, apply for internships, or even do freelance projects. Platforms like Internshala and LinkedIn can be a great resource for finding such opportunities. Additionally, building projects is crucial for demonstrating your skills and knowledge. Experiment with libraries like OpenCV and frameworks like PyTorch, and continue to explore new tools and techniques in Python.
In conclusion, becoming a data scientist while in 12th grade PCM is both feasible and exciting. By following the steps outlined in this roadmap, you can build a strong foundation, gain practical experience, and eventually make a successful transition into a data science career.