GATE DA Syllabus 2027: Topic-Wise Breakdown, Weightage & Prep Plan

Quick Summary: The GATE DA (Data Science and Artificial Intelligence) paper tests 7 core subjects worth 85 marks, plus General Aptitude worth 15 marks. GATE 2027 is conducted by IIT Madras, with exams on February 6, 7, 13, 14, 20 and 21, 2027. This guide breaks down every section of the GATE DA syllabus 2027, the weightage each subject typically carries, and the smartest order in which to study them.

If you are starting your preparation, pair this guide with our complete GATE DA course 2027, which covers every subject below with lectures, notes, PYQs and a full test series.

GATE DA 2027 at a Glance

Note: IIT Madras has revised GATE syllabi for 2027 (the first revision in five years). Always cross-check the final official syllabus PDF on the GATE 2027 website before your last phase of revision. The structure below reflects the DA paper’s core sections.

Section-Wise GATE DA Syllabus 2027

1. Probability and Statistics

Counting (permutations and combinations), probability axioms, sample space and events, independent and 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 PMFs (uniform, Bernoulli, binomial); continuous random variables and PDFs (uniform, exponential, Poisson, normal, standard normal, t-distribution, chi-squared); cumulative distribution functions; Central Limit Theorem; confidence intervals; z-test, t-test and chi-squared test.

This is consistently among the highest-weightage core subjects in the DA paper. Build it early with our dedicated Probability & Statistics for GATE DA course.

2. Linear Algebra

Vector spaces, subspaces, linear dependence and independence; matrices (projection, orthogonal, idempotent, partition); quadratic forms; systems of linear equations; Gaussian elimination; eigenvalues and eigenvectors; determinant, rank, nullity; projections; LU decomposition; singular value decomposition (SVD).

Linear algebra questions in GATE DA are concept-driven rather than lengthy — see the Linear Algebra for GATE DA course for a PYQ-first approach.

3. Calculus and Optimization

Functions of a single variable, limit, continuity and differentiability; Taylor series; maxima and minima; optimization involving a single variable.

This is the shortest section of the syllabus and one of the fastest to complete — our Calculus & Optimization for GATE DA course covers it end to end, and this GATE DA Calculus guide explains the strategy.

4. Programming, Data Structures and Algorithms

Programming in Python; basic data structures — stacks, queues, linked lists, trees, hash tables; search algorithms — linear and binary search; sorting algorithms — selection sort, bubble sort, insertion sort, divide and conquer with mergesort and quicksort; introduction to graph theory; basic graph algorithms — traversals and shortest path.

Python-based questions make this section very scoring for practice-driven students. Prepare it with the Data Structures & Algorithms for GATE DA course.

5. Database Management and Warehousing

ER-model, relational model — relational algebra and tuple calculus; SQL; integrity constraints; normal forms; file organization and indexing; data types, data transformation — normalization, discretization, sampling, compression; data warehouse modelling — schema for multidimensional data models, concept hierarchies, measures.

Read our detailed DBMS & Warehousing for GATE DA guide, and prepare with the DBMS and Data Warehousing course.

6. Machine Learning

Supervised learning: regression and classification, simple and multiple linear regression, ridge regression, logistic regression, k-nearest neighbours, naive Bayes, linear discriminant analysis, support vector machines, decision trees, bias-variance trade-off, cross-validation (leave-one-out, k-fold), multi-layer perceptrons and feed-forward neural networks. Unsupervised learning: clustering algorithms, k-means and k-medoids, hierarchical clustering (top-down and bottom-up, single-linkage and multiple-linkage), dimensionality reduction and principal component analysis (PCA).

Machine Learning is the single largest core subject by weightage in the DA paper. It deserves the most time in your plan — start with the Machine Learning for GATE DA course.

7. Artificial Intelligence

Search — informed, uninformed, adversarial; logic — propositional and predicate; reasoning under uncertainty — conditional independence representation, exact inference through variable elimination, approximate inference through sampling.

Compact but conceptual — covered fully in the Artificial Intelligence for GATE DA course.

General Aptitude (15 Marks)

Verbal aptitude (grammar, vocabulary, reading comprehension), quantitative aptitude (data interpretation, ratios, percentages, elementary statistics and probability), analytical aptitude (logic, deduction and induction, analogy) and spatial aptitude. These 15 marks are the cheapest marks in the paper — do not leave them for the last week.

Subject-Wise Weightage Trend in GATE DA

Based on the DA papers conducted so far (2024 onwards), the approximate weightage pattern looks like this:

Weightage varies year to year; treat this as a planning guide, not a guarantee.

What Order Should You Study the GATE DA Syllabus In?

1. Linear Algebra + Probability & Statistics first — they are prerequisites for Machine Learning.
2. Python, Data Structures & Algorithms in parallel — daily practice beats marathon sessions.
3. Machine Learning next — the highest-weightage subject, now that its math foundations are ready.
4. AI, DBMS & Warehousing, Calculus — compact subjects that convert quickly into marks.
5. General Aptitude + full-length mocks — throughout the final 3 months.

For a complete week-by-week plan, read our GATE DA preparation strategy for 2027, and see the best books for GATE DA for subject-wise references.

FAQs on GATE DA Syllabus 2027

Is Engineering Mathematics a separate section in GATE DA?

No. Unlike papers such as CS or EC, the DA paper has no separate Engineering Mathematics section — the math you need (probability, statistics, linear algebra, calculus) is built into the core syllabus itself.

Has the GATE DA syllabus changed for 2027?

IIT Madras announced a syllabus revision across GATE 2027 papers — the first in five years. Check the official GATE 2027 syllabus PDF for the final DA topic list, and revisit this page as we track any changes.

Which subject should I start with?

Start with Linear Algebra and Probability & Statistics. They unlock Machine Learning, which carries the most marks.

Is the GATE DA syllabus easier than GATE CS?

It is shorter, but not “easy” — DA trades breadth (CS has 10+ subjects) for depth in math and ML. Strong fundamentals in probability and ML decide ranks in DA.

Ready to start? Explore the complete GATE DA 2027 course by Piyush Wairale (IIT Madras) — structured lectures, notes, topic-wise PYQs and a full test series for every subject in this syllabus.

Free YouTube Lectures: Subject-Wise GATE DA Playlists

Want to start learning right now, for free? Piyush Wairale’s YouTube channel has subject-wise playlists mapped to this syllabus:

• Machine Learning for GATE DA — full playlist
• Artificial Intelligence for GATE DA — full playlist
• Calculus & Optimization for GATE DA — full playlist
• All subject playlists — Linear Algebra, Probability & Statistics, DBMS, Python/DSA and more

Subscribe to Piyush Wairale IITM on YouTube for new GATE DA lectures, PYQ solutions and strategy sessions.