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GATE DA Syllabus 2027 PDF Out - Check Data Science and AI Important Topics
GATE 2027 Data Science and AI Syllabus: IIT Madras has uploaded the GATE Data Science and AI Syllabus 2027 PDF. The GATE 2027 syllabus for Data Science and Artificial Intelligence PDF is available on the official website, gate2027.iitm.ac.in. The GATE 2027 DS and AI syllabus comprises all seven major topics that will be tested in the GATE exam. The topics are Probability, Statistics, Linear Algebra, Calculus and Optimisation, Programming, Data Structures, ETC. The authority has released the GATE 2027 exam pattern online along with the syllabus. The authority will conduct the GATE 2027 exam on February 6, 7, 13, 14, 20 & 21, 2027.
Direct link to download the GATE 2027 Data Science and AI Syllabus
This Story also Contains
- GATE DA Syllabus 2027 for General Aptitude
- GATE DS and AI Syllabus 2027
- GATE Data Science and AI Marking Scheme 2027
- GATE 2027 Data Science and AI Books
The GATE 2027 question paper will be prepared based on the syllabus. Candidates must refer to the GATE 2027 syllabus to ensure that they study all the relevant topics. Understanding the syllabus of DA for GATE 2027 is the first and foremost step while preparing for the GATE exam. Candidates can also check the GATE Data Science and AI question paper for a better understanding of the exam pattern and frequently asked topics in the exam.
GATE DA Syllabus 2027 for General Aptitude
IIT Madras has released the GATE 2027 Data Science and AI Syllabus on its official website. Candidates can check the updated GATE General Aptitude syllabus 2027 from the table below.
GATE 2027 syllabus for General Aptitude
| Chapters | Topics |
|---|---|
Verbal Aptitude |
|
Quantitative Aptitude |
|
Analytical Aptitude |
|
Spatial Aptitude |
|
GATE DS and AI Syllabus 2027
IIT Madras has uploaded GATE Syllabus for Artificial Intelligence and Data Science online as a pdf. The syllabus topics include 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.
GATE 2027 DA Syllabus
| 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, tdistribution, 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 Optimisation | 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 |
|
| Programming, Data Structures and Algorithms | Programming in Python, basic data structures: stacks, queues, linked lists, trees, hash tables; Search algorithms:
linear search and binary search, basic sorting algorithms: selection sort, bubble sort and insertion sort; divide and
conquer: mergesort, quicksort; introduction to graph theory; basic graph algorithms: traversals and shortest path. |
| Machine Learning | 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, multi-layer perceptron, feed-forward neural network;
Unsupervised Learning: clustering algorithms, k-means/k-medoid, hierarchical clustering, top-down, bottom-up:
single-linkage, multiple-linkage, 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:
GATE DA and AI Topic-Wise Weightage
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 |
GATE Data Science and AI Marking Scheme 2027
The GATE exam consists of two sections, General Aptitude and subject-oriented. Check the marking scheme of the GATE 2027 DA exam here. Candidates must note that for an incorrect answer in an MCQ, there will be negative marking. For a 1-mark question, 1/3 mark will be deducted and for a 2-mark question, 2/3 mark will be deducted.
GATE 2027 Data Science and AI Marking Scheme
Subject | Marks Allotted |
General Aptitude (GA) | 15 |
Subject marks | 85 |
Total | 100 |
Related links:
GATE 2027 Data Science and AI Books
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.
GATE 2027 Data Science and Artificial Intelligence Books
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)
Q: What is the exam pattern for GATE Data Science and Artificial Intelligence 2027?
A:
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.
Q: What is a good score in GATE 2027?
A:
A score of 90+ is considered the best for GATE 2027, since it increases the chances of admission drastically.
Q: What type of questions are asked in GATE 2027 DA?
A:
GATE DA 2027 will have three types of questions, multiple-choice (MCQ) type, multiple-select (MSQ) type, and numerical answer type (NAT).
Q: Is there negative marking in GATE 2027 Data Science and AI paper?
A:
Yes, there is a negative marking in the GATE Data Science and AI 2027.
Q: Is 6 months enough for GATE 2027 preparation?
A:
It depends on the individual calibre of the aspirant. But yes, with proper planning, and good study material, 6 months is enough for GATE 2027 preparation. Provided that the students must have previous knowledge of the basics.
Q: What is the syllabus for GATE data science 2027?
A:
The GATE Data Science and AI syllabus 2027 includes such as Probability, statistics, linear algebra, algorithms, Programming, Data Structures, database management systems, warehousing, machine learning, and Artificial intelligence.
Q: What is the weightage of subjects in GATE data science and AI?
A:
The weightage of the two sections in the exam is 15% and 85%,
Q: Who is eligible for GATE data science and AI?
A:
Candidates must possess a degree in computer science, electronics and communication, electrical engineering, mathematics, statistics, and physics.
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Hello Student,
A two year gap after b tech is not automatically affect your career negatively, especially if you have used this time productively to prepare for GATE. Many students take one or two years to prepare for competition examinations, and employers or University generally understand this provided you can
Yes, you can apply for GATE if you satisfy the eligibility criteria prescribed for the examination. GATE is open to eligible Indian and foreign nationals from approved countries. Since you are currently studying in India, your nationality alone does not automatically make you ineligible. It is advisable to check the
Hello Dear Student,
The GATE cutoff varies widely by subject paper and candidate category (General, OBC, SC/ST). For instance, the general category qualifying mark for Computer Science (CSE) was 27.6 in 2025 and 25.0 in 2024, while Mechanical Engineering (ME) was 35.8 in 2025.
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Hello Student,
The topic wise mark distribution for GATE 2027 has not been officially released. GATE does not prescript fixed marks for each topic. The weightage varies every year independence on the question paper.
Please mention your GATE paper/branch (such as CSE, ECE, EE, ME, CE, DA, etc.), and we
Hello Dear Student,
Yes, you can appear for the GATE Mechanical Engineering (ME) paper even if you have a B.E./B.Tech in Aeronautical Engineering , provided you meet the GATE eligibility criteria.
However, qualifying GATE ME does not automatically make you eligible for PSU jobs .
- GATE ME: You are eligible
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