CBSE Class 11 Data Science Syllabus 2025–26 | NCERT
CBSE Class 11 – Data Science
(Based on NCERT | Latest CBSE Curriculum 2025–26)
📊 CLASS 11 – DATA SCIENCE
Board: CBSE
Subject: Data Science
Academic Year: 2025–26
📝 QUESTION PATTERN & MARKING SCHEME (CBSE)
Theory Examination: 30 Marks
Time: 1½ Hours
Practical / Internal Assessment: 70 Marks
Assessment Structure
- Theory (30 marks)
- Section A: MCQs / Very Short Answer (1 mark each)
- Section B: Short Answer Questions (2–3 marks)
- Section C: Case-based / Application-based Questions (4–5 marks)
- Practical / Internal (70 marks)
- Hands-on practicals using tools/programming
- Project / Portfolio
- Viva Voce
Total Marks: 100 (30 Theory + 70 Practical)
Map-based questions: Not applicable
📚 SYLLABUS – UNIT-WISE (AS PER NCERT & CBSE 2025–26)
NCERT / CBSE Curriculum: Data Science – Class XI
| Unit | Chapter / Theme | Learning Outcomes / Chapter Summary |
|---|---|---|
| Unit I | Introduction to Data Science | Understand what data science is, its scope, applications and career pathways in modern industries. |
| Unit II | Data and Its Types | Learn types of data (qualitative, quantitative), data sources, data collection methods and data quality. |
| Unit III | Data Handling and Preparation | Understand data cleaning, preprocessing, handling missing values and basic data organisation. |
| Unit IV | Data Visualisation | Learn to represent data using tables, charts and graphs; interpret visual data effectively. |
| Unit V | Basics of Statistics | Understand mean, median, mode, range, measures of dispersion and basic probability concepts. |
| Unit VI | Introduction to Programming (Python) | Learn basics of Python, variables, data types, operators, conditional statements and loops for data tasks. |
| Unit VII | Data Analysis Using Python | Apply Python libraries to analyse datasets and derive simple insights. |
| Unit VIII | Introduction to Machine Learning Concepts | Understand basic ideas of machine learning, supervised and unsupervised learning (conceptual level). |
| Unit IX | Data Science Project Cycle | Learn problem definition, data collection, analysis, interpretation and presentation of results. |
| Unit X | Applications of Data Science | Study real-life applications of data science in healthcare, business, education and governance. |
🧪 PRACTICAL WORK / PROJECT (CLASS XI)
| Area | Activities | Skills Developed |
|---|---|---|
| Data Collection | Simple datasets & surveys | Data literacy and organisation |
| Programming | Python coding exercises | Logical thinking and coding skills |
| Visualisation | Charts and graphs | Interpretation and presentation skills |
| Mini Project | Data-based project using project cycle | Problem-solving, teamwork and analysis |
| Portfolio | Record of work and reflections | Documentation and communication |
📌 PEDAGOGY & ASSESSMENT NOTES
- Emphasis on hands-on learning and real-world data problems
- Strong focus on analytical thinking and interpretation of data
- Project-based learning enhances practical understanding and confidence
- Portfolio maintenance is mandatory
🔍 RELATED KEYPHRASES
- CBSE Class 11 Data Science Syllabus 2025-26
- NCERT Data Science Class 11 Curriculum
- Class 11 Data Science Exam Pattern CBSE
- CBSE Data Science Practical Syllabus
- Data Science Project Work Class 11
❓ FREQUENTLY ASKED QUESTIONS (FAQs)
Q1. Is Data Science a practical subject in CBSE Class 11?
Yes, Data Science is mainly practical, with 70 marks allotted to practical work and projects.
Q2. How many marks are allotted for theory in Data Science?
The theory examination carries 30 marks.
Q3. Is programming compulsory in Class 11 Data Science?
Yes, basic Python programming is an essential part of the syllabus.
Q4. What type of projects are included in Data Science?
Students work on simple data-based projects involving collection, analysis and presentation of data.
Q5. Is Data Science a scoring subject in Class 11?
Yes, with regular practice and project work, Data Science is considered a highly scoring and skill-oriented subject.
