GATE DA syllabus 2027
Data Science & Artificial Intelligence
GATE's newest and fastest-growing paper, blending statistics, core CS and machine learning.
Syllabus sections
- Probability & Statistics
- Linear Algebra
- Calculus & Optimization
- Programming, Data Structures & Algorithms
- Database Management & Warehousing
- Machine Learning
- Artificial Intelligence
Subject-wise weightage (indicative)
| Topic | Typical marks |
|---|---|
| General Aptitude | 15 |
| Probability & Statistics | 15+ |
| Machine Learning | 12–15 |
| Linear Algebra | 7–9 |
| Programming, DS & Algorithms | 7–9 |
| Artificial Intelligence | 6–8 |
| Database Management & Warehousing | 5–7 |
| Calculus & Optimization | 5–7 |
Weightage is indicative, based on recent papers. It varies year to year.
About the GATE DA paper
Data Science & Artificial Intelligence (DA) is the newest GATE paper, introduced in 2024 in response to demand for AI and ML talent. It is unusual among GATE papers because it has no separate Engineering Mathematics section: instead, mathematics is built directly into the syllabus as Probability & Statistics, Linear Algebra, and Calculus & Optimization.
Probability and Statistics is the single heaviest area in this paper, followed by Machine Learning. Candidates from a CS background often underestimate the statistics load and over-prepare the programming portion.
Why DA is different to prepare for
Because DA launched only in 2024, the pool of previous year papers is small. That changes the strategy:
- PYQs alone are not enough, since there simply aren’t enough of them yet.
- Mock tests carry more weight than in older papers, for exposure to question variety.
- Concept clarity in probability and ML matters more than pattern recognition.
Pairing DA with CS
DA and CS share programming, data structures, algorithms and databases. Many candidates prepare one shared core and sit both papers, which doubles their admission and recruitment options for a modest amount of extra preparation.
Recommended books for GATE DA
- Pattern Recognition and Machine Learning by Christopher Bishop
- An Introduction to Statistical Learning by James, Witten, Hastie, Tibshirani
- Artificial Intelligence: A Modern Approach by Russell & Norvig
Frequently asked questions
When was the GATE DA paper introduced?
Data Science & Artificial Intelligence (DA) was introduced in 2024, so only a few previous year papers exist. Mock tests and topic-wise practice matter more in DA than in older papers.
Can I appear for both GATE DA and GATE CS?
Yes. GATE allows up to two papers from an approved combination list, and DA with CS is the most popular pairing because of heavy syllabus overlap in programming, data structures, algorithms and databases.
Does GATE DA have a separate Engineering Mathematics section?
No. DA does not have the standard Engineering Mathematics section. Instead it has its own Probability & Statistics, Linear Algebra, and Calculus & Optimization units, which together carry very high weightage.
Is GATE DA easier than GATE CS?
Neither is reliably easier. DA leans heavily on probability, statistics and machine learning intuition, while CS is broader across systems subjects. Choose based on your background rather than perceived difficulty.