How to Become Data Scientist After 12th
India’s data economy is projected to reach $70 billion by 2026, driven by digital payments and a rapidly expanding fintech ecosystem. This rapid expansion creates significant opportunities for aspiring data scientists after 12th grade. A data scientist analyzes complex data to inform business decisions and develop strategic insights. Data Science is an integrative field that combines statistical methods, scientific algorithms, and machine learning to extract knowledge from large datasets. A Data Scientist’s primary role revolves around data analysis to help companies make strong decisions and improve business strategy. They pull, merge, and analyze data using various tools, write and test algorithms, and present findings to clients.
| Parameter | Details |
|---|---|
| Definition of Data Science | An integrative subject using statistical methods, scientific algorithms, information science, data analysis, and machine learning concepts to extract knowledge from large groups of structured and unstructured data for business strategy. |
| Core Objective of Data Science | To help companies make strong decisions and improve business strategy based on data analysis. |
| Key Disciplines Integrated | Statistical methods, scientific algorithms, information science, data analysis, and machine learning. |
| Types of Data Handled | Large groups of structured and unstructured data. |
| Primary Role of a Data Scientist | Analyzing data, writing and testing algorithms, and conducting client meetings to provide actionable insights. |
| Daily Activities | Pulling, merging, and analyzing data; writing new algorithms based on analysis; testing algorithms in real-time. |
| Common Tools Used | Python, MATLAB, R, Tableau, Hadoop, SQL, and Excel. |
| Output of Data Scientist’s Work | Strategies for companies based on data analysis, future predictions about business. |
| Industry Relevance (2026) | An emerging career option with high demand due to the steep rise in big data. |
| Nature of the Profession | Requires extensive knowledge in Data Science, Mathematics, and Computer Science; an ever-evolving field with new technologies. |
| Common Data Science Job Titles | AI Engineer, Data Scientist, Machine Learning Engineer, Data Architect, Data Analyst, Business Analyst, Business Analytics Manager, Data Engineer, Big Data Specialist, MIS Consultant/Data Visualization Consultant. |
The field of Data Science is continuously evolving, requiring professionals to stay updated with new technologies and methodologies.
Why Pursue Data Science after 12Th in India? Job Market & Career Scope by 2026
India is projected to have over 11 lakh job openings for Data Scientists by 2026, making IT the second-highest Data Scientist recruiting country globally (Times of India). The Indian data science industry is expected to grow at a Compound Annual Growth Rate (CAGR) of 57.5% from 2023 to 2028, offering a dynamic and financially rewarding career path for students after 12th grade.
| Metric / Career Path | Description / Key Statistic | Growth Outlook & Impact (by 2026) |
|---|---|---|
| Total Data Science Jobs (India) | Approximately 1.2 lakh jobs as of 2024. | Expected to exceed 1 million by 2026, indicating massive demand (NASSCOM). |
| Data Science Industry Growth (India) | CAGR of 57.5% from 2023 to 2028. | This rapid growth creates lakhs of new job opportunities across sectors. |
| India’s Global Ranking in Data Scientist Recruiting | Second-highest country in the world. | Strong global recognition ensures sustained demand and career prospects. |
| Data Scientist | Transforms raw, unstructured data into actionable insights using statistics, programming, and business understanding. Entry-level salaries typically range from ₹4-10 LPA. | High demand across healthcare, IT, e-commerce, and finance; considered a “sexiest job of the 21st century” (Harvard Business Review). |
| Data Analyst | Focuses on reporting, interpreting data, and identifying trends to support business decisions. | Many professionals progress from Data Analyst to Senior Analyst and then to Data Scientist with additional ML skills. |
| Data Engineer | Builds and maintains the infrastructure for data collection, storage, and processing. Requires strong technical expertise and problem-solving skills. | role in the data ecosystem, with high demand for strong data pipelines. |
| Machine Learning Engineer | Designs, builds, and deploys machine learning models and algorithms. | An emerging profession with significant growth potential, especially in AI-driven applications. |
| AI Researcher | Conducts research to develop new AI algorithms, models, and applications. | An emerging and highly specialized profession at the forefront of technological innovation. |
| Business Analyst | bridge between business needs and data solutions, translating requirements into technical specifications. | for ensuring data projects align with strategic business goals. |
| Big Data Specialist | Manages and analyzes extremely large datasets that traditional tools cannot handle. | Increasingly vital as companies deal with petabytes of information. |
| MIS Consultant / Data Visualization Consultant | Helps organizations design and implement Management Information Systems (MIS) or create compelling visual representations of data. | Supports effective decision-making through clear data presentation. |
| Talent Gap for Specialized Data Roles (India) | 60-73% gap for roles like ML Engineers, Data Scientists, and Data Architects. | This wide talent gap ensures high future demand and competitive compensation for skilled professionals. |
| Career Progression for Data Professionals | Common path: Analyst → Senior Analyst → Data Scientist. Senior roles include Lead Data Scientist, ML Architect, Head of Analytics. | Offers clear growth trajectories and opportunities for leadership in top tech and product companies. |
| Industries Hiring Data Scientists | Healthcare, IT, transportation, education, retail, e-commerce, manufacturing, finance, consulting. | Data Science skills are universally applicable, opening doors across almost every sector. |
| Time to Job Ready | Typically 2–4 years with consistent learning, projects, and internships after a bachelor’s degree. | A focused approach can lead to early career entry and rapid skill development. |
The strong growth of India’s data science sector and the diverse career paths available make IT an impactful and financially rewarding choice for students completing 12th grade in 2026.
Data Scientist Salary in India 2026: Fresher to Experienced Pay & Influencing Factors
Data Scientist salaries in India for 2026 range from ₹4-10 LPA for freshers, reaching ₹25-40+ LPA for lead roles. The overall average annual salary for a Data Scientist in India is ₹13-15.5 LPA, reflecting strong demand across diverse industries.
| Experience Level | Average Salary (LPA) | Key Factors Influencing Pay | Top Recruiters |
|---|---|---|---|
| Fresher (0-1 Year Experience) | ₹4-10 LPA (2026) | Technical skills (Python, SQL, ML, Data Visualization), Project complexity, Tech stack, Hiring demand, Location, Company type | TCS, Infosys, Accenture, IBM, High-growth startups, Cognizant, E&Y |
| Early Career (1-4 Years Experience) | ₹8-10 LPA (2026) | Industry knowledge, Skill set, Location, Company and Industry, Job Role, Project exposure | Tech giants (e.g., Amazon, Google), Consulting firms, Financial institutions, E-commerce platforms, Healthcare organizations |
| Mid-Level (4-6 Years Experience) | ₹10-22 LPA (2026) | Advanced technical skills, Proven project leadership, Impactful business solutions, Mentoring junior staff, Company type | Large enterprises, Product-based companies, Fintech, Pharma, Automotive sectors |
| Senior (5-10 Years Experience) | ₹15-25 LPA (2026) | Strategic thinking, Cross-functional collaboration, Driving data initiatives, Deep domain expertise, Managing junior data scientists | Leading tech companies, Global consulting firms, Unicorn startups, Research & Development divisions |
| Lead/Principal Data Scientist (10+ Years Experience) | ₹25-40+ LPA (2026) | Visionary leadership, Architecting data solutions, Influencing business strategy, Team management, Innovation, Chief scientist roles | Fortune 500 companies, AI-first organizations, Deep tech startups, Advisory roles |
| AI Data Scientist (All Experience Levels) | ₹6-30+ LPA (2026) | Expertise in Generative AI, Large Language Models (LLMs), MLOps, Cloud platforms (AWS, GCP, Azure), Advanced algorithms | Companies working on AI projects, Automation firms, Cybersecurity companies, Cloud service providers |
| Overall Average (All Experience Levels) | ₹13-15.5 LPA (2026) | Cumulative impact of experience, skills, location, company, industry, and job role across the data science field | Tech giants, Consulting firms, Financial institutions, E-commerce platforms, Healthcare organizations |
| General Influencing Factors | Varies significantly by factor | Location (major cities vs. Others), Company and Industry type, Job Role, Specific Skill Set, Data Science certifications, Postgraduate programs, Project portfolio | Across all industries and company types |
The Data Science field offers a financially rewarding career path, with salaries significantly increasing with experience and specialized skills in areas like AI and machine learning.
Step-by-Step Roadmap to Become a Data Scientist after 12Th in India (2026)
Becoming a Data Scientist in India after 12th involves a structured educational and skill development path, typically spanning 3-5 years. The demand for Data Scientists is projected to create approximately 11 lakh job openings by 2026, with a strong growth outlook across various industries.
- Understand the Data Scientist Role (2026 Outlook): A Data Scientist transforms raw, unstructured data into actionable insights for business decisions. This role blends statistics, programming, and business understanding, often going deeper into prediction and modeling. The profession is projected to grow at a CAGR of 57.5% from 2023 to 2028 in India, offering financially rewarding opportunities in IT, healthcare, and e-commerce sectors.
- Choose the Right 12th Stream & Foundational Subjects: Students should clear Class 12th with Physics, Chemistry, and Mathematics for B.Tech Data Science programs. A Computer Science background is highly beneficial for aspiring data scientists. For those without 12th-grade Mathematics, some universities may require a foundation or bridge course before enrollment in B.SC. Data Science or BCA Analytics programs.
- Pursue a Relevant Undergraduate Degree: Options include a 4-year B.Tech in Data Science or Computer Science with Data Science specialization, or a 3-year B.SC. Data Science, B.SC. Statistics, or BCA Analytics. Admission typically involves national-level entrance exams like JEE Main/Advanced for B.Tech, or university-specific tests and merit-based selection for B.SC/BCA programs.
- Develop Technical and Soft Skills: Key technical skills include Python, R, SQL, Machine Learning, Deep Learning, and Data Visualization, which are learned during UG courses and through dedicated certifications. Problem-solving, analytical thinking, and business understanding are soft skills for a Data Scientist, enabling them to translate complex findings into actionable outcomes.
- Gain Practical Experience Through Projects and Internships: Building a strong portfolio with hands-on projects is vital; students can undertake Data Science Internships lasting 1 to 6 months during their degree. Institutes like Indira University offer multiple certifications and strong recruiter networks, significantly boosting internship and placement opportunities for graduates.
- Consider Advanced Degrees and Professional Certifications: After a bachelor’s, an M.SC. Or M.Tech in Data Science/AI/Analytics (2 years) or a PG Diploma from IITs, IIITs, or ISB can career prospects. Professional certifications, such as the Microsoft Azure Data Scientist Associate, further validate specialized skills and can be completed in a few weeks to months.
- the Job Market and Plan Career Progression: Freshers can target roles like Data Analyst or Junior Data Scientist, with average starting salaries ranging from ₹4-10 LPA in 2026. Career progression often moves from Analyst to Senior Analyst to Data Scientist, with senior roles like Lead Data Scientist earning ₹25-50+ LPA in top tech companies.
Following this structured roadmap helps students effectively prepare for a dynamic and impactful career as a Data Scientist in India.
Eligibility Criteria for Data Science Courses after 12Th: Science & Commerce Streams
Most Data Science undergraduate programs in India (2026) require students to have passed Class 12th with a minimum of 50% marks. While a Science stream with Mathematics is preferred, students from Commerce backgrounds can also pursue data science with foundational math or bridge courses.
- Science Stream (PCM/PCMB): Students aiming for B.Tech Data Science or B.SC. Data Science typically need Class 12th with Physics, Chemistry, and Mathematics. Top engineering colleges like IITs and NITs often require 60-65% aggregate marks in 10+2 for admission to B.Tech programs.
- Computer Science Background: Having Computer Science as a subject in Class 12th is beneficial for aspiring data scientists. This background provides a head start in programming and computational thinking, which are core to data science.
- Mathematics Requirement: Mathematics is a subject for data science, even if not strictly compulsory for all courses. Students without 12th-grade Mathematics may need to complete a foundational or bridge course offered by some universities.
- Commerce Stream with Mathematics: Commerce students who have studied Mathematics in Class 12th are eligible for various data science pathways. They can pursue degrees like BCA (Analytics) or B.SC. Data Science, often requiring basic entrance exams.
- Commerce Stream without Mathematics: IT is possible to pursue data science without 12th-grade Mathematics, but a strong understanding of basic statistics is . Some universities may mandate a bridge course to cover necessary mathematical foundations.
- Minimum Aggregate Marks: General eligibility for B.SC. Level data science courses is typically 45% aggregate in 10+2 from a recognized board. For B.Tech and other professional courses, a minimum of 50% aggregate is usually required.
- No Prior Coding Skills: Most undergraduate data science programs do not require prior coding knowledge in Python, SQL, or Machine Learning. These skills are taught progressively throughout the degree curriculum.
Understanding these specific academic prerequisites helps students choose the most suitable undergraduate path for a data science career after Class 12th.
Top Data Science Courses after 12Th: UG Degrees, Diplomas & Online Certifications
Students after 12th grade have diverse academic options to pursue a career in data science, ranging from 3-year undergraduate degrees to specialized 4-year B.Tech programs. , short-term diplomas and online certifications offer focused skill development for aspiring data scientists in 2026. These programs cater to various academic backgrounds, including Science, Commerce, and Arts streams, with a strong emphasis on mathematics and statistics.
| Course Type | Examples | Duration | Eligibility | Career Benefit |
|---|---|---|---|---|
| Undergraduate Degree (Science) | B.SC Data Science, B.SC in Programming and Data Science (IIT Madras) | 3 Years | 12th pass; Mathematics background beneficial; basic statistics knowledge helps | Builds foundational skills for entry-level Data Analyst roles; strong base for further studies. |
| Undergraduate Degree (Computer Applications) | BCA, BCA Analytics | 3 Years | 12th pass (Science, Commerce, or Arts stream); Mathematics background beneficial | Develops programming and analytical skills; pathway to MCA or Data Science roles. |
| Undergraduate Degree (Engineering) | B.Tech Data Science, B.Tech Computer Science, B.Tech CSE in AI & Data Science (ITM, Rungta) | 4 Years | 12th pass (Science stream with Physics, Chemistry, Mathematics); Computer Science background beneficial | Provides in-depth technical expertise for direct entry into specialized Data Scientist/ML Engineer roles. |
| Undergraduate Degree (Foundation) | B.SC Statistics, B.SC Maths | 3 Years | 12th with Mathematics | Develops strong analytical and quantitative base for advanced Data Science careers. |
| Diploma Program | Diploma in Data Science programs | 1 Year (typically) | 12th standard | Offers practical, job-oriented skills for quicker entry into junior data roles. |
| Online Certification | Certifications in Data Science, Microsoft Data Science Certification Azure Data Scientist Associate | A few weeks to months | No specific 12th stream requirement (often open to all) | specific skills, builds portfolio, and complements formal education for career advancement. |
Choosing the right course depends on academic background, career aspirations, and desired depth of study. Each path offers unique advantages for building a successful career in data science.
Admission Process & Entrance Exams for Data Science Programs in India 2026
Most Data Science programs after 12th require a strong academic background in Science or Mathematics. Admission to these undergraduate programs in 2026 often involves national-level entrance exams like JEE Main or CUET UG. Eligibility criteria vary by course type and institution, with top colleges often having higher percentage requirements.
| Course Type | Minimum 12th Marks | Mandatory Subjects | Notes |
|---|---|---|---|
| B.Tech Data Science / CSE (AI & DS) | 50-65% (Top IITs/NITs require 60-65%) | Physics, Chemistry, Mathematics (PCM) / Computer Science | Science stream is compulsory. Computer Science background is beneficial. |
| B.SC Data Science | 45-50% | Mathematics (or Statistics) | Science stream preferred; Commerce/Arts students may need foundational math. |
| BCA (Data Science/Analytics) | 12th pass | Mathematics (recommended) | Open to Science, Commerce, or Arts streams. Basic statistics knowledge is helpful. |
Several entrance exams are for securing admission to Data Science programs after 12th in India for the 2026 academic session. These tests assess aptitude and subject knowledge, determining eligibility for various undergraduate degrees.
- JEE Main 2026: The National Testing Agency (NTA) conducts JEE Main for admission to B.Tech programs, including Data Science specializations, across NITs, IIITs, and other government-funded technical institutes. Results for Session 1 are declared by NTA, with specific application and exam dates for 2026 to be announced on the official website.
- JEE Advanced 2026: This exam is the gateway to undergraduate engineering programs at the prestigious Indian Institutes of Technology (IITs), including their Data Science offerings. Only candidates who qualify JEE Main are eligible to appear for JEE Advanced.
- BITSAT 2026: BITSAT is the entrance examination for admission to integrated first-degree programs at the Birla Institute of Technology and Science (BITS) campuses in Pilani, Goa, and Hyderabad. This exam is a key route for B.Tech Data Science aspirants.
- CUET UG 2026: The Common University Entrance Test (CUET UG) is administered by NTA, providing a single, standardized platform for admission to undergraduate programs in central, state, deemed, and private universities nationwide. Registration for CUET UG 2026 begins around January 3, 2026, with a fee payment deadline of January 31, 2026, and tentative exam dates from May 11-31, 2026 (Source: CUET.NTA.nic.in).
- OJEE 2026: The Odisha Joint Entrance Examination (OJEE) is conducted by OJEEB for admission to various undergraduate and postgraduate professional courses in Odisha, including B.Tech (Lateral) and MCA. Registration for OJEE 2026 starts on January 30, 2026, with an application deadline of March 20, 2026, and exam dates from May 2-6 and May 10-11, 2026 (Source: OJEE.nic.in).
Understanding these admission processes and preparing for the relevant entrance exams is for students aspiring to pursue Data Science after 12th grade.
Skills for Aspiring Data Scientists: Technical, Soft & Tools for 2026
Aspiring data scientists in 2026 need a blend of technical expertise, analytical thinking, and strong communication skills. These competencies are for transforming raw data into actionable business insights. Many undergraduate programs and certifications integrate these skills into their curriculum, preparing students for the evolving data .
- Programming Languages: Proficiency in Python and R is fundamental for data manipulation, statistical analysis, and machine learning model development. Libraries like Pandas, NumPy, and Scikit-learn are tools for daily tasks.
- Database Management (SQL/NoSQL): Strong SQL skills are required to extract, manage, and query data from relational databases. Knowledge of NoSQL databases is also beneficial for handling unstructured data.
- Statistics & Mathematics: A solid understanding of basic statistics, probability, linear algebra, and calculus forms the analytical backbone of data science. This knowledge helps in model interpretation and hypothesis testing.
- Machine Learning & Deep Learning: The ability to build, train, and evaluate machine learning models (e.g., regression, classification, clustering) is a core technical skill. Familiarity with deep learning frameworks like TensorFlow or PyTorch is also highly valued.
- Data Visualization: Tools such as Tableau, Power BI, Matplotlib, and Seaborn are used to create compelling visual representations of data. Effective visualization helps communicate complex findings to non-technical stakeholders.
- Data Cleaning & Preprocessing: Data scientists spend a significant portion of their time cleaning and preparing raw, unstructured data for analysis. This involves handling missing values, outliers, and inconsistencies.
- Business Acumen & Domain Knowledge: Understanding the specific industry or business context is vital to ask the right questions and interpret data in a meaningful way. This helps in translating data insights into strategic decisions.
- Problem-Solving & Analytical Thinking: Data scientists must possess strong problem-solving abilities to identify patterns, explore anomalies, and develop innovative solutions. Critical thinking is key to navigating complex datasets.
- Communication Skills: The ability to translate complex technical findings into clear, concise, and actionable insights for diverse audiences is important. This includes presenting results and collaborating with teams effectively.
- Big Data Tools: Familiarity with big data technologies like Hadoop and Spark can be advantageous for handling large volumes of data. Excel and MATLAB are also used for specific analytical tasks.
Developing these skills through dedicated coursework, projects, and certifications is key for students aiming to become data scientists after 12th grade.
Top Data Science Colleges in India 2026: Fees, Admission & Placement
India offers 200+ colleges for data science courses after 12th, including 167 private and 34 government institutions . These programs, primarily B.Tech, B.SC, and BCA degrees, prepare students for the rapidly growing data science job market by 2026.
| College Name | Location | Type | Approx Fees (LPA) | Avg Placement (LPA) | Admission Mode |
|---|---|---|---|---|---|
| IIT Madras (Online) | Chennai | Government | ₹0.5-0.8 lakh | ₹6-10 LPA | Online Entrance Exam |
| ITM (Navi Mumbai) | Navi Mumbai | Private | ₹1.8-3.0 lakh | ₹4-8 LPA | Entrance Exam / Merit |
| VIT Vellore | Vellore | Private | ₹1.9-3.0 lakh | ₹7-9 LPA | VITEEE |
| Rungta University | Central India | Private | ₹1.0-2.5 lakh | ₹3-6 LPA | Entrance Exam / Merit |
| Regional College of Management (RCM) | Bhubaneswar | Private | ₹0.6-1.2 lakh | ₹3-5 LPA | 10+2 Merit + PI |
| Online SRM | Online (Chennai HQ) | Private | ₹0.5-1.0 lakh | ₹3-6 LPA | Direct Online Admission |
| IIITs (Various) | Across India | Government | ₹1.5-2.5 lakh | ₹10-20 LPA | JEE Main |
| Central Universities (e.g., DU, BHU) | Across India | Government | ₹0.05-0.5 lakh | ₹3-6 LPA | CUET UG |
Students can choose from various undergraduate degrees like B.Tech Data Science or B.SC Data Science, with eligibility typically requiring a Class 12th science stream with Mathematics.
Building a Strong Data Science Portfolio: Projects, Internships & Certifications
A strong data science portfolio is for securing entry-level roles, demonstrating practical skills beyond academic scores. Consistent learning, projects, and internships can lead to job readiness within 2-4 years after graduation.
- Real-World Projects: Start building projects early, focusing on diverse datasets from platforms like Kaggle or government data portals. Inspiria Knowledge Campus emphasizes hands-on experience with real-world projects to employability.
- Your Work: Create a GitHub repository to host your project code, analyses, and visualizations. A personal website or blog can further your portfolio, making IT easily accessible to potential employers.
- Data Science Internships: Pursue internships during your undergraduate studies, typically lasting 1 to 6 months (summer or winter). These provide practical industry exposure and are for understanding real-world data challenges.
- Industry Certifications: Obtain certifications to validate specialized skills in areas like machine learning, cloud platforms, or specific tools. Indira University offers multiple certifications aligned with data science and analytics pathways.
- Microsoft Azure Data Scientist Associate: Consider specific industry-recognized certifications such as the Microsoft Azure Data Scientist Associate. These demonstrate proficiency in cloud-based data science tools and methodologies.
- Online Data Science Courses: Supplement your degree with online data science courses from platforms like IIT Madras, which offers various online programs. These courses often include practical assignments and project work.
- Hands-on Diploma Programs: Explore Diploma programs in Data Science that emphasize hands-on learning and often include a placement cell. Cyber Success in Pune is known for job-oriented learning and placement success.
Key Takeaways
- Consistent project work and internships are vital for data science job readiness, typically taking 2-4 years post-graduation.
- Industry certifications, such as Microsoft Azure Data Scientist Associate, validate specialized skills and employability.
- Online courses and Diploma programs provide practical, hands-on experience and contribute significantly to a strong portfolio.
Begin building your data science portfolio by exploring online courses and identifying relevant internship opportunities for the 2026-2027 academic year.
Frequently Asked Questions (FAQs)
Can I join data science after 12th?
Yes, you can pursue BTech/BE in Data Science, Computer Science, or related fields after 12th with PCM/PCB. IIT Madras offers BTech Data Science with ₹2.5 lakh annual fees (2026), requiring 60% in 12th and JEE Main rank.
How to become a data scientist in India after 12th?
Complete 12th with PCM/PCB, enroll in BTech/BE (₹4-15 lakh total fees), then pursue MSc or PG Diploma. Top recruiters like TCS, Amazon, and Flipkart offer ₹6-12 LPA to freshers (as per 2025 data).
Which subjects are required in 12th for data science?
Physics, Chemistry, and Mathematics (PCM) are mandatory for most engineering data science programs. Commerce students must take additional math/stats courses to qualify for BSc Data Science programs.
Are there entrance exams for data science courses after 12th?
Yes, JEE Main (for IITs/NITs), SRMJEEE, and VITEEE are required for BTech Data Science. Christ University Bangalore conducts its own entrance test for BSc Data Science (₹1.2 lakh annual fees).
Can commerce students become data scientists?
Yes, commerce students can pursue BSc Data Science by clearing additional math/statistics papers. Online platforms like Coursera offer foundational courses (₹10,000-25,000) to bridge gaps in quantitative skills.
What are the job opportunities after data science courses?
Roles include Data Analyst, Machine Learning Engineer, and Business Intelligence Developer. Top recruiters in 2026: TCS, Amazon, Accenture, with entry-level salaries ranging ₹4.5-9 LPA (NIRF 2025 report).
Which are the top colleges for data science in India?
IIT Madras (BTech Data Science, ₹2.5 lakh/year, NIRF 2025 Rank #1), IIIT Hyderabad (BSc Data Science, ₹3.2 lakh/year), and Christ University Bangalore (₹1.2 lakh/year with 85% placement rate).
Disclaimer: The information provided in this article is sourced from official websites, NIRF rankings, and publicly available data. Fees, placement figures, and other details may vary. Please verify with the official institution website for the most current information.
