GATE Application Date:28 Aug' 25 - 28 Sep' 25
GATE Data Science and AI Syllabus 2026 - IIT Guwahati has released the GATE 2026 Data Science and Artificial Intelligence syllabus pdf on the official website, gate2026.iitg.ac.in. Candidates can download the GATE Data Science and AI syllabus 2026 using the direct link given below. The Data Science and AI syllabus comprises all the topics that will be tested in the GATE exam. The syllabus comprises topics such as Probability, Statistics, Linear Algebra, Algorithms, Programming, Data Structures, Database Management Systems, Data Warehousing, Machine Learning, and Artificial Intelligence. The authority has provided the GATE 2026 exam pattern online. The authority will conduct the GATE 2026 exam on February 7, 8, 14 and 15, 2026.
Direct link to download the GATE 2026 Data Science and AI Syllabus
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The GATE 2026 question paper will be prepared based on the syllabus. Candidates must refer to the GATE syllabus to ensure that they study all the relevant topics. Understanding the syllabus of DA for GATE 2026 is the first and foremost step while preparing for the GATE exam. The previous year GATE DA syllabus is mentioned in this article. Candidates can also check the GATE Data Science and AI question paper for more understanding of the exam pattern and frequently asked topics in the exam.
IIT Guwahati has released the GATE 2026 Data Science and AI Syllabus on its official website, gate2026.iitg.ac.in. Candidates can check the updated GATE General Aptitude syllabus 2026 from the table below.
| Chapters | Topics |
|---|---|
| GATE GA syllabus for Verbal Aptitude |
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| GATE GA syllabus for Quantitative Aptitude |
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| GATE GA syllabus for Analytical Aptitude |
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| GATE GA syllabus for Spatial Aptitude |
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IIT Guwahati has uploaded the GATE Syllabus for Artificial Intelligence and Data Science online as a pdf. The syllabus topics such as Probability, Statistics, Linear Algebra, Algorithms, Programming, Data Structures, Database Management Systems, Data Warehousing, Machine Learning, and Artificial Intelligence. For detailed information, refer to the GATE syllabus for Data Science and AI below.
Subject | Topics |
|---|---|
GATE DA syllabus for Probability and Statistics | Counting (permutation and combinations), probability axioms, Sample space, Events, independent events, mutually exclusive events, marginal, conditional and joint probability, Bayes Theorem, conditional expectation and variance, mean, median, mode and standard deviation, correlation, and covariance, random variables, discrete random variables and probability mass functions, uniform, Bernoulli, binomial distribution, Continuous random variables and probability distribution function, uniform, exponential, Poisson, normal, standard normal, t-distribution, chi-squared distributions, cumulative distribution function, Conditional PDF, Central limit theorem, confidence interval, z-test, t-test, chi-squared test. |
GATE DA syllabus for Linear Algebra | Vector space, subspaces, linear dependence and independence of vectors, matrices, projection matrix, orthogonal matrix, idempotent matrix, partition matrix and their properties, quadratic forms, systems of linear equations and solutions Gaussian elimination, eigenvalues and eigenvectors, determinant, rank, nullity, projections, LU decomposition, singular value decomposition |
GATE DA syllabus for Calculus and optimization | Functions of a single variable, limit, continuity and differentiability, Taylor series, maxima and minima, optimization involving a single variable |
GATE DA syllabus for Database Management and Warehousing |
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GATE DA syllabus for Programming, Data Structures and Algorithms |
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GATE DA syllabus for Machine Learning | (i) Supervised Learning: regression and classification problems, simple linear regression, multiple linear regression, ridge regression, logistic regression, k-nearest neighbour, naive Bayes classifier, linear discriminant analysis, support vector machine, decision trees, bias-variance trade-off, cross-validation methods such as leave-one-out (LOO) cross-validation, k-folds cross-validation, mulo-layer perceptron, feed-forward neural network; (ii) Unsupervised Learning: clustering algorithms, k-means/k-medoid, hierarchical clustering, top-down, bottom-up: single-linkage, multiple linkages, dimensionality reduction, principal component analysis. |
GATE DA syllabus for AI | Search: informed, uninformed, adversarial; logic, propositional, predicate; reasoning under uncertainty topics - conditional independence representation, exact inference through variable elimination, and approximate inference through sampling. |
Related links:
| Topic Name | Number of Questions | Total Marks |
|---|---|---|
| General Aptitude | 10 | 15 |
| Probability and Statistics | 10 | 16 |
| Linear Algebra | 6 | 10 |
| Calculus and Optimization | 5 | 8 |
| Programming, Data Structures, and Algorithms | 13 | 21 |
| Database Management and Warehousing | 6 | 8 |
| Machine Learning | 8 | 11 |
| Artificial Intelligence (AI) | 7 | 11 |
| Total | 65 | 100 |
The GATE exam consists of two sections, General Aptitude and subject-oriented. Check the marking scheme of the GATE 2026 DA exam here. Candidates must note that the For a wrong answer chosen in a MCQ, there will be a negative marking. For a 1-mark question, 1/3 mark will be deducted and for the 2-mark question, 2/3 mark will be deducted.
Subject | Marks Allotted |
|---|---|
General Aptitude (GA) | 15 |
Subject marks | 85 |
Total | 100 |
Related links:
Students can refer to the following table for the list of books for GATE preparation. A useful tip to aspirants is to make GATE Data Science and AI notes in a short and precise manner for better revision. Moreover, aspirants must check their level of preparation regularly with GATE Data Science and AI sample papers and mock tests.
Book | Author |
Artificial Intelligence: A Modern Approach | Textbook by Peter Norvig and Stuart J. Russell |
‘Deep Learning’ | by Ian Goodfellow, Yoshua Benjio, Aaron Courville |
Introduction to Data Science: Practical Approach with R and Python | B. Uma Maheswari (Author), R. Sujatha (Author) |
Data Science for Dummies | Lillian Pierson (Author), Jake Porway (Foreword) |
Data Science from Scratch: First Principles with Python | Joel Grus |
Frequently Asked Questions (FAQs)
As per the exam pattern for GATE Data Science and Artificial Intelligence, the exam will have 15 marks worth GA section and the remaining 85 for the core subject. The question paper will comprise a mix of MCQs, MSQs and NATs.
A score of 90+ is considered the best for GATE 2026, since it increases the chances of admission drastically.
GATE DA 2026 will have three types of questions, multiple-choice (MCQ) type, multiple-select (MSQ) type, and numerical answer type (NAT).
Yes, there is a negative marking in the GATE Data Science and AI 2026.
It depends on the individual calibre of the aspirant. But yes, with proper planning, and good study material, 6 months is enough for GATE 2026 preparation. Provided that the students must have previous knowledge of the basics.
The GATE Data Science and AI syllabus 2026 includes such as Probability, statistics, linear algebra, algorithms, Programming, Data Structures, database management systems, warehousing, machine learning, and Artificial intelligence.
On Question asked by student community
Hello
As an EEE (Electrical and Electronics Engineering) graduate, your core GATE paper is EE (Electrical Engineering).
You can also choose papers like IN (Instrumentation) or EC (Electronics and Communication) if you're comfortable. GATE now allows two-paper combinations EE plus IN is a valid pair.
Choose based on your strengths and future goals (e.g., PSU jobs, M.Tech). Always check the latest GATE brochure for updated paper codes and combinations.
How to clear GATE Exam :
First, know the syllabus and exam pattern.
Make a small study plan and follow it every week.
Read from good books or trusted online notes.
Practice old GATE question papers.
Give mock tests to check speed and accuracy.
Revise your notes and formulas again and again.
How to get Job in PSU:
Score high in GATE, because PSUs take only top ranks.
Keep checking PSU job notices regularly.
Apply on time with your GATE score.
Be ready for interviews or group discussions.
Work on subject knowledge and also your communication skills.
Yes, it will be acceptable. In GATE registration, the name should match your valid photo ID proof in terms of spelling, not the order. Many Indian IDs have surname written first, while the portal generates it as first–middle–last. Since all three parts of your name (Vikash, Rameshbhai, Bhagel) are correct, there won’t be any issue. Just ensure you upload the correct ID proof. During verification, they check spelling, photo, and signature, not the word order.
Hello,
Yes, you can change your category from General to OBC during the GATE 2026 correction window.
GATE always allows candidates to correct details like category. You will need to pay a small correction fee for this change. Make sure you upload a valid OBC certificate as per the format and date mentioned by GATE.
So, wait for the correction window, log in to your application, and update your category to OBC.
Hope it helps !
Hello! If you are preparing for GATE, there are plenty of free resources available online that can boost your preparation. You can easily access e-books, handwritten notes, subject wise PYQs, and test series shared by toppers on different platforms. Along with that, free PDFs and study material are available through various websites and Telegram channels. To make it easier, I will be attaching the link where you can find preparation tips, a study timetable, free study materials, and previous year question papers all in one place.
https://engineering.careers360.com/articles/gate-preparation-timetable
https://engineering.careers360.com/articles/how-to-prepare-for-gate
https://engineering.careers360.com/articles/gate-preparation-material
https://engineering.careers360.com/articles/gate-mock-test
https://engineering.careers360.com/articles/gate-question-papers
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