Step-by-Step Process to Become a Data Scientist After 12th?

Learning Saint
2 days ago
7 min read

Introduction: Why Choose Data Science After 12th?

In today’s data-driven world, organizations across industries rely heavily on data for decision-making. This has skyrocketed the demand for data scientists globally. If you’ve just completed your 12th grade and are fascinated by technology, numbers, and problem-solving, then learning how to become a data scientist after 12th could set you on a highly rewarding career path.

Whether you're from a science, commerce, or arts background, it's now more accessible than ever to begin your journey early. This blog will walk you through every step on how to start a career in data science and establish yourself in this fast-growing field.

Who is a Data Scientist? Key Roles and Responsibilities

Before diving into the steps, it’s important to understand what a data scientist does. A data scientist is a professional who analyzes large sets of data to find meaningful insights. These insights help companies improve performance, understand customer behavior, and predict future trends.

Roles and Responsibilities:

Data collection and preprocessing
Statistical analysis and modeling
Programming using tools like Python or R
Visualizing data for business decisions
Building machine learning models

If you’re wondering how to become a data scientist, these are the core areas you’ll need to master over time.

Eligibility to Start a Career in Data Science After 12th

A common question is: Can I become a data scientist after the 12th? Yes, you absolutely can—but with the right educational and skill-building approach. Here are some basic eligibility criteria:

Completion of 12th grade from a recognized board
Strong foundation in mathematics and logical reasoning
Passion for technology, analytics, and data
Willingness to learn programming and statistics

Remember, your 12th board subjects may influence your entry route into data science, but they don’t limit your options completely.

Step 1: Choose the Right Stream in 12th Grade

While it is possible to switch tracks later, choosing the right stream in your 12th grade can help ease your journey. Here's what’s ideal:

Science (PCM/PCMB): Best suited as it includes mathematics and computer science
Commerce with Mathematics: Also viable for data-centric domains
Arts with Statistics/Economics: Less traditional but still possible with upskilling

Having mathematics in your curriculum makes it easier to grasp data science concepts later. If you're clear on how to become a data scientist after 12th, make sure you begin aligning your subjects accordingly.

Step 2: Pursue a Bachelor’s Degree (B.Sc, BCA, B.Tech, etc.)

After the 12th, your next step is enrolling in a relevant undergraduate program. While it’s not mandatory to take a computer science degree, it helps to choose a field that builds your analytical and technical skills.

Top recommended degrees:

B.Tech in Computer Science/Data Science
B.Sc in Statistics, Mathematics, or Computer Science
BCA (Bachelor in Computer Applications)
BA/B.Com with Data Analytics electives

These degrees lay the academic foundation for anyone serious about how to become a data scientist in the long term.

Step 3: Learn Programming Languages (Python, R, SQL)

No matter your degree, one of the most critical skills you’ll need is programming. Data scientists work with programming languages daily to analyze and manipulate data.

Must-learn languages:

Python – Widely used and beginner-friendly
R – Great for statistical computing
SQL – Essential for database querying

Online platforms, coding bootcamps, and YouTube tutorials are great places to start. This step is essential for those wondering how to start a career in data science without a computer science background.

Step 4: Master Mathematics and Statistics for Data Science

Understanding math and statistics is the backbone of data science. If you skipped these in school, now is the time to go back and master the basics.

Focus areas include:

Linear algebra
Probability and statistics
Calculus
Descriptive and inferential statistics

Knowing how to interpret data and apply statistical tests is vital for model building and analysis. It’s a non-negotiable skill on your journey toward how to become a data scientist after 12th.

Step 5: Enroll in Data Science Certification or Diploma Courses

A college degree is important, but real-world skills are built through additional learning. There are numerous online and offline data science certification courses that you can pursue even during your graduation.

Look for certifications in:

Data Science Fundamentals
Machine Learning
Data Analytics
Business Intelligence Tools

These certifications offer hands-on training and can dramatically boost your resume. They also provide exposure to practical tools and datasets—giving you a real feel of the industry.

Step 6: Build Hands-On Skills with Projects and Internships

The best way to stand out in the data science field is by building a portfolio. Theory is important, but hiring managers look for practical problem-solving ability.

How to start:

Take part in Kaggle competitions
Complete mini-projects using public datasets (e.g., Titanic Survival Prediction, Movie Recommendation Systems)
Do internships during or after college
Contribute to open-source data science repositories

Hands-on work demonstrates your ability to apply what you’ve learned. If you're wondering how to become a data scientist, this step is where your skills start becoming job-ready.

Step 7: Learn Data Visualization and BI Tools (Tableau, Power BI)

Being able to interpret complex data is one thing—but visualizing it for others to understand is an essential skill for data scientists. This is where data visualization tools come into play.

Popular tools to learn:

Tableau – For drag-and-drop dashboards and charts
Power BI – Microsoft’s analytics and visualization platform
Matplotlib / Seaborn – Python-based visualization libraries

Visual representation helps communicate your insights effectively to business teams. As you plan how to become a data scientist after 12th, make sure to include data visualization tools in your learning roadmap.

Step 8: Create a Strong Data Science Portfolio

A strong portfolio is your golden ticket to job interviews and internships. It reflects your practical knowledge and thought process. Employers want to see more than just certificates—they want real proof of your abilities.

How to build a great portfolio:

Host your projects on GitHub
Write blogs on platforms like Medium explaining your projects
Include Jupyter Notebooks with well-documented code
Add visual dashboards (Tableau Public, Power BI dashboards)

Your portfolio is the best way to showcase how you started your career in data science and how your skills evolved from beginner to job-ready.

Step 9: Apply for Entry-Level Data Science Jobs

Once you’ve gained the necessary skills and built your portfolio, it’s time to take the leap and start applying for entry-level data science roles. Some titles you can apply for include:

Junior Data Analyst
Data Science Intern
Machine Learning Associate
Business Intelligence Analyst

Tips for applying:

Tailor your resume to highlight data science certifications, projects, and skills
Use platforms like LinkedIn, Internshala, AngelList, and Indeed
Prepare for interviews by practicing data structure, SQL queries, statistical questions, and case studies

You don’t need to wait until your post graduation—many successful data scientists have started their careers right after graduation by taking the right steps. If you're committed to how to become a data scientist after 12th, real job exposure will accelerate your learning.

Step 10: Consider Higher Education (Master’s, PGP, or Specialization)

Although you can enter the field with a bachelor’s degree and strong practical skills, many professionals go for higher education to advance their careers.

Advanced options:

M.Sc. or M.Tech in Data Science / AI / Big Data
PGP (Post Graduate Program) in Data Science
MBA in Business Analytics (for leadership/managerial roles)

These programs deepen your domain knowledge and increase your chances of entering high-paying roles. If you're planning long-term, this step is vital for career growth beyond entry-level.

Top Skills Needed to Succeed as a Data Scientist

If you’re serious about how to start a career in data science, it's important to consistently work on the following skill sets:

Technical Skills:

Programming (Python, R, SQL)
Machine Learning Algorithms
Data Visualization Tools
Big Data Technologies (Spark, Hadoop)
Cloud Platforms (AWS, GCP)

Soft Skills:

Communication
Problem-solving
Critical thinking
Collaboration and teamwork

A balance of both technical and soft skills will make you a well-rounded data professional. These are non-negotiable for anyone pursuing the path of how to become a data scientist from scratch.

Online Platforms and Courses for Data Science Learning

Today, you don’t need to attend a top-tier university to learn data science. Numerous online platforms offer high-quality courses, certifications, and even mentorship.

Recommended learning platforms:

Coursera
edX
Udemy
DataCamp
Kaggle Learn

Many of these platforms offer free modules, hands-on labs, and career guidance. If you're asking yourself how to start a career in data science with limited resources, these are excellent places to begin.

Career Opportunities and Salary Scope in Data Science

Data Science is one of the most lucrative and in-demand careers of the 21st century. Starting from entry-level to senior roles, the earning potential increases significantly with skills and experience.

Popular career paths:

Data Analyst
Data Scientist
Machine Learning Engineer
Data Engineer
AI Researcher
Business Intelligence Developer

Average salaries in India (as of 2025):

Entry-level Data Scientist: ₹6 – ₹10 LPA
Mid-level (3–5 years): ₹12 – ₹18 LPA
Senior-level (5+ years): ₹20 LPA and above

If you’re strategic about how to become a data scientist after 12th, you can achieve impressive growth in a short span of time.

Conclusion: Your Roadmap to Becoming a Data Scientist After 12th

Becoming a data scientist is not an overnight journey—but starting after the 12th gives you a significant head start. The steps are clear: choose the right educational path, upskill consistently, gain hands-on experience, and build a strong portfolio.

The earlier you start, the stronger your foundation will be. With the right attitude, tools, and guidance, you can successfully transition from a student to a data science professional within a few years.

If you're still wondering how to become a data scientist after 12th, remember: it’s all about persistence, practice, and passion.

18. Frequently Asked Questions (FAQs)

Q1: Can I become a data scientist without coding?

While it’s possible to enter data-related roles like analytics or BI without heavy coding, data science usually requires knowledge of Python, R, or SQL.

Q2: Which stream should I take after 10th to become a data scientist?

Science with Mathematics or Commerce with Mathematics are ideal for laying the foundation in statistics and logic.

Q3: How long does it take to become a data scientist after 12th?

It can take 3–5 years depending on your learning pace, degree path, and hands-on experience.

Q4: Is data science a good career in India?

Yes, it’s one of the most in-demand careers with strong salary potential and global opportunities.

Q5: What if I am from a non-technical background?

With the right certification courses and dedication, even non-tech students can become data scientists.

Ready to begin your journey? 👉 Start learning Data Science today with industry-recognized training programs at Learning Saint!