GATE 2026 DA Syllabus: Exam Date (Feb 15), Check Pattern, Important Topics, and Books

Graduate Aptitude Test in Engineering 2026 ( GATE )

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27 Mar '26 - 31 May '26

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UPASANA PRADHAN
Assistant Manager- Editorial
Updated on Feb 2, 2026 11:45 IST
GATE Syllabus for DA - IIT Guwahati has released the GATE Data Science and Artificial Intelligence Syllabus. Candidates can download the GATE DA syllabus from the official website or this page. Check complete details about GATE 2025 DA syllabus here.

GATE DA Syllabus 2026: IIT Guwahati has released GATE DA syllabus 2026 on its official website - gate2026.iitg.ac.in. Candidates who have registered for IITG GATE 2026 DA paper can check complete syllabus, pattern, marking scheme, GATE PYQs, and important topics below.

GATE DA(Data Science and Artificial Intelligence) Syllabus

GATE Data Science and Artificial Intelligence (DA) Syllabus

What is Data Science and Artificial Intelligence (DA)?

GATE Data Science and Artificial Intelligence (DA) are fields that use data to solve problems. Data Science mainly combines statistical tools, methods, and technology to generate meaning from data. On the other hand, artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems.

The GATE 2026 Data Science and Artificial Intelligence paper contains syllabi on probability and statistics, machine learning, database management, etc. Data science and artificial intelligence graduates have many career options, such as data scientists, machine learning engineers, AI engineers, business intelligence analysts, etc. 

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GATE 2026 DA Exam Date

The GATE 2026 exam is held in two sessions on February 7, 8, 14, and 15, 2026. Registered candidates can get the detailed exam dates and instructions mentioned on the GATE admit card, which has been released. Students can download their hall ticket using their enrollment ID and password. GATE DA exam 2026 will be conducted on Feb 15 in the second shift (2:30 pm to 5:30 pm). 

 GATE 2026 DA Important Topics and Weightage

Students can check GATE DA important topics and chapter-wise weightage (as per experts)

Subjects Approximate Weightage/Marks
Probability and Statistics 16 marks
Linear Algebra 10 marks
Calculus and Optimisation 8 marks
Programming, Data Structures, and Algorithms 21 marks
Database Management and Warehousing 8 marks
Machine Learning 11 marks
Artificial Intelligence 11 marks

Read here: GATE DA (Data Science and Artificial Intelligence) important topics and most repeated questions asked

GATE DA Syllabus: Check detailed syllabus here

IIT Guwahati has released the GATE DA syllabus 2026 on the GATE’s official website. Candidates can download the GATE Data Science and Artificial Intelligence Syllabus in PDF format from the official website or check the detailed syllabus below -

Topics (Section)

Sub-Topics

Probability and Statistics

Counting (permutation and combination) | probability axioms | sample space | Bayes Theorem | Discrete Random Variables and Probability Mass Theorems | Binomial Distribution | Central Limit Theorem | Chi-Squared Test

Linear Algebra

Vector space | Subspaces | Projection Matrix | Quadratic Forms | Orthogonal Matrix | Eigen Values and Eigen Vectors | LU Decomposition | Singular Value Decomposition

Calculus and Optimization

Functions of a Single Variable, Limit, Continuity, and Differentiability | Taylor Series | Maxima and Minima | Optimization Involving a Single Variable

Programming, Data Structures, and Algorithms

Programming in Python | Search Algorithms: Linear Search and Binary Search | Basic Sorting Algorithms | Basic Data Structures: Stacks, Queues, Linked Lists, Trees, Hash Tables | Introduction to Graph Theory | Basic Graph Algorithms: Traversals and Shortest Path

Database Management and Warehousing

ER-Model | Relational Model: Relational Algebra, Tuple Calculus, SQL, Integrity Constraints, File Organization, Indexing, Data Types, and Data Transformation, such as normalisation, discretisation, sampling, compression, etc. | Data Warehouse Modelling: Schema for Multidimensional Data Models, Concept Hierarchies, Measures: Categorisation and Computations

Machine Learning

Supervised Learning: Regression and Classification Problems | Simple Linear Regression | Support Vector Machine | Multi-Layer Perception | Feed-Forward Neural Network | Unsupervised Learning

Artificial Intelligence (AI)

Search: Informed and Uniformed | Adversarial: Logic, Propositional, Predicate | Reasoning under Uncertainty Topics - Conditional Independence Representation, Exact Inference Through Variable Elimination, and Approximate Inference Through Sampling

Click here to download GATE DA syllbaus PDF: GATE DA Syllabus

GATE DA Syllabus: Check Exam Pattern and Two Paper Combination

The GATE DA 2026 exam will be conducted as a three-hour computer-based test. Three types of questions will be asked in the examination: multiple-choice questions (MCQ), multiple-select questions (MSQ), and numerical answer-type questions (NAT). 

According to the GATE exam pattern, the DA question paper will comprise 65 questions of 100 marks. It is divided into general aptitude questions of 15 marks and subject-specific questions of 85 marks. 

GATE 2026 Allowed Two-Paper Combinations

Candidates opting for data science and engineering (DA) in GATE 2026 as the primary subject can choose the following test papers as the secondary papers in the GATE two-paper combination -

  • Computer Science and Information Technology (CS)
  • Electronics and Communication Engineering (EC)
  • Electrical Engineering (EE)
  • Mathematics (MA)
  • Mechanical Engineering (ME)
  • Physics (PH)
  • Statistics (ST)
  • Engineering Sciences (XE)

Books for GATE 2026 Data Science and Artificial Intelligence Preparation

Candidates can refer to the books below for GATE preparation for Data Science

Book Name

Author

GKP GATE 2025: Data Science and Artificial Intelligence - Guide (solved papers)

GK Publications

Mathematical Statistics and Data Analysis (3rd Edition)

John A. Rice 

Introduction to Probability Models

Sheldon M.Ross

Data Structures and Algorithms in Python

Roberto Tamassia, Micheal H, Goldwasser, Michael T.Goodrich

Database Management Systems

Raghu Ramakrishnan

Data Mining and Data Warehousing

Prateek Bhatia

Artificial Intelligence by Example

Denis Rothman

Artificial Intelligence Basics

Tom Taulli

Machine Learning for Beginners

Chris Sebastian

Fundamentals of Database Systems

Navathe Shamkant

Read More: 

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About the Author
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UPASANA PRADHAN
Assistant Manager- Editorial

Upasana Pradhan is an Mtech graduate in Electronics and Communication Engineering from DTU who specialises in curating postgraduate and undergraduate engineering entrance exam content, such as GATE, TS PGECET, KCET,

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