GATE DA Previous Year Questions & Study Resources
GATE Data Science and Artificial Intelligence (DA)
195 solved GATE DA questions from 2024–2026, each with the official answer and a step-by-step solution. Solving past papers is the highest-signal preparation there is: it teaches the real difficulty level, the recurring topics, and the time pressure of the actual exam.
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GATE DA subject-wise PYQs
Choose a subject to revise one area at a time. Subject tags can overlap; these question counts are not marks weightage.
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Build on your GATE DA PYQ revision
Reading a solution is a useful start. In Success Tracker, you can attempt questions yourself, review mistakes and return to the topics that need another pass.
- PYQs with solutions
- Attempt available previous-year questions, then compare your reasoning with the worked solution. Coverage varies by stream.
- Practice that adapts
- Choose a topic, work on weaker areas and bookmark questions to revisit. Your attempts feed your progress tracking.
- AI doubt support
- Ask follow-up questions about a step or concept while practising, instead of stopping at the final answer.
Unlimited practice is available on eligible plans. Free practice and AI usage have limits; check the current plan allowances before choosing.
This page stays readable without an account. AI responses can be wrong; check them against the solution and source material.
Learn the concept, then solve the PYQs
Start with the available GATE DA revision companions: Probability & Statistics, Programming, Data Structures & Algorithms, General Aptitude, Machine Learning, Database Management & Warehousing, Linear Algebra, Artificial Intelligence, Calculus & Optimization. Each combines concept notes, mistakes to avoid, an original worked example, a self-check and free further reading with the subject’s PYQs. No account is needed to read them.
Probability & Statistics: define the experiment before calculating
Define outcomes, events, and a sampling rule before choosing a formula. Conditional probabilities depend on observations; statistical conclusions depend on data collection. These selected foundations connect counting, distributions, and inference without replacing the full syllabus.
Read notes and solve questionsProgramming & Algorithms: trace the code, then count the cost
Simulate code on small inputs before generalizing. Identify the data structure's invariant, the algorithm's loop structure, and the input size before claiming a complexity bound. These selected foundations connect Python-style pseudocode execution, fundamental data structures, sorting, searching, and asymptotic analysis. They are not a complete syllabus.
Read notes and solve questionsGeneral Aptitude: extract the relationship before computing
Translate word problems into explicit relationships before substituting numbers. Verbal questions are answered from the passage, not from outside knowledge; quantitative questions require identifying the correct base, ratio, or logical connection. These selected foundations cover reading comprehension, data interpretation, quantitative reasoning, and logical deduction. They are not a complete syllabus.
Read notes and solve questionsMachine Learning: separate fitting, prediction, and evaluation
State the model, objective, and data split before calculating an update or reporting a score. Training improvement and generalization are different claims. These selected notes connect regression, classification, validation, trees, and unsupervised learning through explicit assumptions and checkable calculations.
Read notes and solve questionsDatabase Management & Warehousing: state the schema before querying
Record the schema, functional dependencies, or ER structure before choosing a rule or writing a query. SQL semantics depend on duplicate handling, NULL behavior, and grouping rules. Data warehousing questions require distinguishing facts from dimensions. These selected foundations connect the relational model, normalization, SQL, and warehousing concepts. They are not a complete syllabus.
Read notes and solve questionsLinear Algebra: connect matrix operations to subspaces
Track dimensions and interpret calculations as statements about linear maps. Elimination describes solvability, projections describe approximation, and eigenvectors describe invariant directions. These selected revision notes emphasize checks that expose errors before they propagate into larger problems.
Read notes and solve questionsArtificial Intelligence: define the state space before searching
Specify the state representation, actions, goal test, and cost model before choosing a search strategy. Logical inference requires valid rules applied to a stated knowledge base. These selected foundations connect search algorithms, propositional and first-order logic, constraint satisfaction, and planning. They are not a complete syllabus.
Read notes and solve questionsCalculus & Optimization: verify conditions before applying a rule
State the domain, continuity, or differentiability condition a formula requires before substituting. Optimization problems need both a critical-point calculation and a classification step. These selected foundations connect single-variable calculus, multivariable derivatives, and constrained optimization as they appear in the GATE DA syllabus. They are not a complete syllabus.
Read notes and solve questionsA repeatable PYQ revision routine
- Attempt a question before reading its solution. Write down your assumptions and reasoning, not just the answer.
- Compare the reasoning. Classify a miss as a concept gap, a calculation error or a misread condition.
- Use the revision notes to repair the gap, then attempt a different question from the same subject.
- Reattempt the missed question later without the solution. Use a complete paper to check pacing after topic revision.
This is our suggested study workflow, not an official sequence or a prediction of the next paper. Read how we produce our content.