How to Become a Data Scientist After 12th: Degree, Skills & Roadmap

Introduction

A decade ago, “data scientist” sounded like a role reserved for PhD scholars crunching numbers for their research projects. But today, it’s one of the most in-demand careers across tech, finance, healthcare, e-commerce, and even entertainment.

And here’s the surprising part: you don’t need to wait until your master’s degree to begin this journey. You can start right after the 12th, making this the ideal moment to understand how to become a data scientist after 12th.

From predicting market trends and detecting fraud to recommending what you should watch next on Netflix, data science has become the language behind every smart decision. Thus, companies want people who can make sense of clustered data and build intelligent models to drive decisions.

This blog lays out a clear, realistic, 2026-ready roadmap for students who want to step into this field early. You’ll learn what a data scientist actually does, the eligibility after 12th, the best degree and certification paths, and how to start building skills long before graduation.

What does a Data Scientist do?

A data scientist is part analyst and part problem-solver. Their job is to take massive piles of raw, unstructured data and turn it into insights that help companies make smarter decisions.

At its core, the role blends statistics, programming, business understanding, and creativity. A data scientist asks the right questions, explores patterns, builds models, and translates complex findings into simple, actionable outcomes.

Job Roles and Responsibilities

Here’s what data scientists typically do in a day:

• Collect & clean data so it’s usable for analysis
• Explore datasets to spot trends, anomalies, and hidden patterns
• Build machine learning models that predict outcomes
• Evaluate model performance and improve accuracy
• Create dashboards & visualisations to communicate insights
• Collaborate with teams in engineering, product, marketing, or finance
• Solve business problems using data-driven reasoning
• Present insights in a way that decision-makers can act on

Career Opportunities After Data Science Course

Here are some of the top job roles learners can grow into:

• Data Analyst
• Junior Data Scientist
• Business Analyst
• Machine Learning Engineer
• AI Engineer
• Data Engineer
• BI Developer / Power BI Analyst
• Research Analyst

Data Scientist Eligibility After 12th

There’s no formal “data science eligibility” at the 12th level, but colleges and employers generally look for the following:

• 12th Pass from Any Recognised Board: You can start your data science journey right after Class 12, no matter which stream you studied, i.e. Science, Commerce, or Arts.
• Comfort with Math & Logical Thinking: You don’t need to be a math genius, but a basic understanding of numbers and logical reasoning makes learning easier.
• Problem-Solving Aptitude: If you enjoy puzzles, patterns, or figuring out the optimal solution, you’re already aligned with the core of data science.
• No Prior Coding Required: You don’t need to know Python, SQL, or ML before joining a degree program. These skills are learned gradually during your UG course and through certifications.
• Optional Entrance Exams (University-Specific): Some institutions conduct entrance tests or interviews to understand your aptitude, while others admit based on merit.

2026 Roadmap: Pathway to Become a Data Scientist After 12th

How to become a Data Scientist after 12th, this question has no sure-shot one answer. It isn’t about choosing one definite pathway or one perfect degree.

It’s about building the right combination of skills, projects, and industry exposure over time.

Steps to Become a Data Scientist After 12th

Here’s a quick step-by-step guide for how to become a data scientist after 12:

1. Choose a Degree Path: Begin with a UG program like B.Sc. in AI & Data Science
2. Learn Core Skills Early: Python and SQL, the two essentials for all data roles.
3. Build Beginner Projects: Analyse simple datasets and publish your work on GitHub.
4. Take Relevant Certifications: Add ML, data analytics, or visualisation courses alongside your degree.
5. Apply for Internships: Gain real-world exposure through analyst or data trainee roles.

This roadmap gives students a clear sense of direction from Day 1 after Class 12.

Undergraduate Courses

Your undergraduate degree forms the base of your learning. Here are the strongest pathways, depending on your goals:

1. B.Sc. in Data Science: The most direct path. You learn statistics, machine learning, data analytics, programming, and visualisation from the fundamentals. Indira University’s SOIT integrates Artificial Intelligence, which amplifies the course prospects, i.e., B.Sc. in AI and DS.
2. B.Tech in CSE/AI/Data Science: Ideal for students who want both coding + engineering depth. Opens doors to roles like Machine Learning Engineer, Data Engineer, and AI Engineer.
3. BCA or BCA (Data Science Specialization): A great option for students who love coding and want a mix of software development + analytics. Often leads to data analyst, BI analyst, and ML associate roles.
4. B.Sc. in Computer Science/Mathematics/Statistics: Strong foundation paths. CS helps with coding, Math/Stats help with modelling, both crucial for data science.

Duration: 3–4 years

Fees: ₹1.5–₹3 lakhs per year

Diploma Courses

A diploma doesn’t level a proper degree, but it helps you build early skills and become job-ready faster for roles like Junior Data Analyst, Reporting Analyst, or Python Developer while you’re still pursuing your degree.

• Diploma in Data Science
• Diploma in Artificial Intelligence & Machine Learning
• Diploma in Computer Applications
• Polytechnic in Computer Science

Duration: 6 months to 1 year

Fees: ₹30,000–₹1,00,000

Certifications

Phase	Core Skills covered in Certifications	Outcome / Job-Readiness
Foundations (Months 0-3)	Python basics, SQL, SQL Bootcamp, Excel & Power BI fundamentals	Able to clean data, run queries, and create basic dashboards, ready for small data tasks and projects.
Core Data Science (Months 3-9)	EDA, Pandas/Numpy, ML fundamentals (regression, classification), model evaluation	Can build and evaluate simple ML models; suitable for Data Analyst/junior ML roles.
Applied Tools & Visualization (Months 6-12)	Advanced visualisation, reporting, Tableau/Power BI advanced, Streamlit/Flask	Able to present insights professionally and deploy simple models for demos/internships.
Specialisation (Months 9-18)	NLP Specialization, Big Data, and Cloud ML	Domain expertise that differentiates you in interviews, targets niche roles, such as NLP Jr, CV Jr, Big Data analyst.
Capstone & Industry Experience (Months 12-24)	End-to-end projects, MLOps basics, GitHub portfolio projects, and Internship certificates	Portfolio of 3–5 end-to-end projects + internships directly increases chances for paid internships/entry roles.

Why choose Indira University’s SOIT to become a Data Scientist after 12th?

Becoming a data scientist requires far more than learning Python or running a few ML models. It demands clarity in fundamentals, exposure to real datasets, hands-on problem-solving, and an environment that mirrors the pace of the tech industry.

That’s exactly where Indira University’s School of Information Technology (SOIT) stands out. Here’s how SOIT gives students a strong head start after Class 12:

1. 31+ Years of Academic Legacy in Technology Education: With over three decades of academic excellence, Indira University has built a reputation for producing industry-ready tech professionals. This legacy ensures structured learning, strong academic culture, and a proven ecosystem for growth.
2. Future-Focused, Industry-Aligned Curriculum: SOIT programs integrate programming, AI, data analytics, cybersecurity, information systems, and applied computing, helping students build the core skills underpinning data science careers.
3. Practical, Lab-Based Data & Coding Experience: Students work in advanced computing labs, coding simulations, problem-solving labs, and data-driven environments, gaining confidence through hands-on experimentation. Whether analysing datasets or training models, the learning approach is fully experiential.
4. Interdisciplinary Learning Essential for Data Science: Data science blends math, analytics, algorithms, and intelligent systems. SOIT’s programs seamlessly integrate these domains, ensuring students understand how algorithms, data structures, security layers, and intelligence models work together.
5. Strong Industry Connect & Exposure to Real Tech Environments: Students gain real-world exposure through:

1. 1. Industry visits
   2. Live projects
   3. MoUs with tech organisations
   4. Cyber Cell collaborations
   5. Workshops & expert-led sessions

These experiences give them a front-row seat to real IT operations, digital systems, analytics workflows, and problem-solving environments.

6. Strong Recruiter Network Across IT, Analytics & Cybersecurity: Top recruiters such as Infosys, KPIT, Deloitte, Wipro, TCS, Cognizant, LTI Mindtree, Accenture, and more hire Indira graduates across tech, analytics, AI, and cybersecurity roles. This network significantly boosts internship and placement opportunities after graduation.
7. Certifications That Strengthen Data Careers: Students get access to multiple certifications that align closely with data science and analytics pathways, including:
   1. Applied Machine Learning
   2. Data Analytics
   3. AWS & Cloud Computing
   4. Artificial Intelligence
   5. Microsoft Office with AI Tools

Conclusion

The answer to “How to become a data scientist after 12th” has a practical, achievable journey when you start with the right foundation, roadmap, and learning environment. With the right degree, structured skill-building, certifications, and hands-on projects, students can step confidently into one of the world’s fastest-growing careers.

For learners who want industry-aligned training, real-world exposure, and a curriculum shaped by 31+ years of academic legacy, Indira University’s School of Information Technology is the perfect choice to step into data science and analytics roles of the future.

FAQs

1. Can I become a data scientist after 12th?

Yes. With the right degree, foundational skills, certifications, and project experience, students can begin their data science journey immediately after Class 12.

2. Which degree is best after 12th to become a data scientist?

B.Sc Data Science, B.Tech CSE/AI/DS, and BCA (Data Science specialization) are strong pathways, giving students coding, analytics, and machine-learning foundations.

3. How long does it take to become a data scientist after 12th?

With consistent learning, projects, and internships, students typically become job-ready within 2–4 years, depending on their specialization and certifications.

4. Do I need coding knowledge after 12th to start data science?

No. You can begin without coding experience. Python, SQL, and ML concepts are learned gradually during your degree and through beginner-friendly certifications.

5. How does Indira University’s SOIT offer the best data science course?

Indira University’s SOIT provides industry-aligned curriculum, advanced labs, global exposure, hands-on projects, certifications, and strong recruiter connections, creating an ideal environment for students to build real data science and analytics careers.