GATE DA Test Series 2027 — Mock Tests, Topic Tests & Performance Analysis
61 tests, 1,685 problems — built specifically for the GATE Data Science & AI exam pattern.
Designed by Jay Bansal (AIR 9 GATE DA 26) and Sriniwas Paliwal (AIR 90 GATE CS 19).
What You Get: 61 Tests, 1,685 Problems & Full GATE DA Coverage
A progressive test plan designed from scratch for the GATE Data Science & AI syllabus — not repurposed from GATE CS. Every problem includes detailed solutions.
36 Topic-Wise Tests
15 problems each — test specific sub-topics within each subject to catch weak areas early.
8 Subject-Level Tests
33 problems each — covering the full scope of a subject (probability, ML, Python, etc.).
7 Multi-Subject Tests
33 problems combining 2–3 related subjects to build concept-switching agility.
10 Full-Length Grand Mocks
65 questions, 3 hours, negative marking — simulating real GATE DA conditions.
Performance Analysis & Ranking
Instant scoring, subject-wise breakdown, and All India ranking after every test.
Detailed Solutions
Step-by-step explanations for every question — concept, approach, and common mistakes.
Topic-Wise Tests3615540
Topic-Wise Tests — Detailed Topic Coverage
Probability & Statistics — Test #1
Counting: Factorials, Permutations, Combinations, Binomial & Multinomial Theorem, PIE, Seating, Circular Arrangements, Derangement | Probability: Sample Space & Events, Conditional Probability, Multiplication Theorem, Independent Events
Probability & Statistics — Test #2
Probability: Marginal & Joint Probability, Total Probability, Bayes' Theorem | Statistics: Mean, Mode, Median, Skewness, Kurtosis, Range, Interquartile Range, Variance, Standard Deviation, Covariance, Correlation
Probability & Statistics — Test #3
Discrete Random Variables: PMF, CDF, Expectation, Variance, SD, Conditional Distributions, Conditional Expectation, Conditional Variance, Covariance, Joint PMF, Joint CDF, Independent Variables, Discrete Uniform, Bernoulli, Binomial, Poisson Random Variables
Probability & Statistics — Test #4
Continuous Random Variables: Basics of Integration, PDF, CDF, Expectation, Variance, SD, Conditional Distributions, Conditional Expectation, Conditional Variance, Covariance, Joint PDF, Joint CDF, Independent Variables, Uniform, Exponential, Normal, Standard Normal Random Variables
Probability & Statistics — Test #5
Statistical Inference: Markov's and Chebyshev's Inequality, Central Limit Theorem, Sample Mean, Sample Variance, Point Estimation, Confidence Intervals, Hypothesis Testing (z-test, t-test, chi-square test)
Calculus — Test #6
Functions: Standard Functions, Odd/Even Functions, Types of functions, Inverse functions | Limits: Limits, Standard Limits, Limit Laws
Calculus — Test #7
Continuity & Differentiability: Continuity, Differentiability, Interconnection Between Limits, L'Hopital's rule, Mean Value Theorem, Differentiation
Calculus — Test #8
Taylor Series: Taylor Series Theorem, Taylor series of standard functions, Ratio Test | Maxima, Minima & Optimization: Maxima and Minima, Optimization involving a single variable
Linear Algebra — Test #9
Matrices: Types of Matrices, Matrix Operations, Transpose, Symmetric, Skew-Symmetric, Determinants, Minors, Cofactors, Adjoint, Inverse, Rank
Linear Algebra — Test #10
Systems of Linear Equations: Gaussian Elimination, Gauss-Jordan Elimination, Homogeneous and Non-Homogeneous Systems, Consistency, Cramer's Rule
Linear Algebra — Test #11
Vector Spaces: Vectors, Vector Operations, Linear Independence, Span, Basis, Dimension, Subspaces
Linear Algebra — Test #12
Eigenvalues & Eigenvectors: Characteristic Polynomial, Eigenvalues, Eigenvectors, Diagonalization, Orthogonal Matrices, Quadratic Forms
Artificial Intelligence — Test #13
Search Algorithms: Uninformed Search (BFS, DFS, Uniform Cost Search), Informed Search (Greedy Best-First, A*, Heuristics), Adversarial Search (Minimax, Alpha-Beta Pruning)
Artificial Intelligence — Test #14
Knowledge Representation: Propositional Logic, First-Order Logic, Inference, Resolution, Forward Chaining, Backward Chaining
Artificial Intelligence — Test #15
Planning & Reasoning: Classical Planning, STRIPS, Partial Order Planning, Probabilistic Reasoning, Bayesian Networks
Artificial Intelligence — Test #16
Natural Language Processing: Tokenization, Parsing, Context-Free Grammars, N-grams, Word Embeddings, Sentiment Analysis
Programming in Python — Test #17
Python Basics: Data Types, Variables, Operators, Control Flow (if-else, loops), Functions, Lambda Functions, List Comprehensions
Programming in Python — Test #18
Python Advanced: File I/O, Exception Handling, Modules, Packages, OOP (Classes, Objects, Inheritance, Polymorphism), Decorators, Generators
Data Structures & Algorithms — Test #19
Arrays & Strings: Array Operations, String Manipulation, Searching (Linear, Binary), Sorting (Bubble, Selection, Insertion, Merge, Quick)
Data Structures & Algorithms — Test #20
Linked Lists & Stacks & Queues: Singly Linked List, Doubly Linked List, Circular Linked List, Stack Operations, Queue Operations, Deque, Priority Queue
Data Structures & Algorithms — Test #21
Trees & Graphs: Binary Trees, Binary Search Trees, AVL Trees, Heaps, Graph Representation, BFS, DFS, Shortest Path (Dijkstra, Bellman-Ford), Minimum Spanning Tree (Prim, Kruskal)
Machine Learning — Test #22
Supervised Learning I: Linear Regression, Polynomial Regression, Logistic Regression, Gradient Descent, Cost Functions, Regularization (L1, L2)
Machine Learning — Test #23
Supervised Learning II: Decision Trees, Random Forests, Support Vector Machines (SVM), Kernel Trick, Naive Bayes
Machine Learning — Test #24
Unsupervised Learning: K-Means Clustering, Hierarchical Clustering, DBSCAN, Principal Component Analysis (PCA), Dimensionality Reduction
Machine Learning — Test #25
Model Evaluation: Train-Test Split, Cross-Validation, Confusion Matrix, Precision, Recall, F1-Score, ROC Curve, AUC
Machine Learning — Test #26
Neural Networks & Deep Learning: Perceptron, Multi-Layer Perceptron, Activation Functions, Backpropagation, CNNs, RNNs, LSTMs
DBMS & Warehousing — Test #27
ER Model & Relational Model: Entities, Attributes, Relationships, ER Diagrams, Relational Schema, Keys (Primary, Foreign, Candidate, Super)
DBMS & Warehousing — Test #28
SQL: DDL, DML, DCL, TCL, SELECT Queries, Joins (Inner, Outer, Cross), Subqueries, Aggregation, GROUP BY, HAVING
DBMS & Warehousing — Test #29
Normalization & Transactions: Functional Dependencies, Normal Forms (1NF, 2NF, 3NF, BCNF), ACID Properties, Transactions, Concurrency Control
DBMS & Warehousing — Test #30
Indexing & Query Optimization: B-Trees, B+ Trees, Hashing, Query Processing, Query Optimization, Cost Estimation
DBMS & Warehousing — Test #31
Data Warehousing: OLTP vs OLAP, Star Schema, Snowflake Schema, Fact Tables, Dimension Tables, ETL Process, Data Mining
General Aptitude — Test #32
Quantitative Aptitude: Arithmetic (Percentages, Profit & Loss, Time & Work, Speed & Distance), Algebra, Geometry, Mensuration
General Aptitude — Test #33
Logical Reasoning: Puzzles, Seating Arrangements, Blood Relations, Coding-Decoding, Series, Analogies
General Aptitude — Test #34
Data Interpretation: Tables, Bar Graphs, Pie Charts, Line Graphs, Data Sufficiency
General Aptitude — Test #35
Verbal Ability: Reading Comprehension, Grammar, Vocabulary, Sentence Correction, Para Jumbles
General Aptitude — Test #36
Numerical Ability: Number Systems, HCF & LCM, Simplification, Approximation, Ratio & Proportion
Subject-Wise Tests833264
Subject-Wise Tests — Detailed Topic Coverage
Subject Test #1
Complete Probability & Statistics syllabus
Subject Test #2
Complete Calculus & Optimization syllabus
Subject Test #3
Complete Linear Algebra syllabus
Subject Test #4
Complete Artificial Intelligence syllabus
Subject Test #5
Complete Programming & Data Structures & Algorithms syllabus
Subject Test #6
Complete Machine Learning syllabus
Subject Test #7
Complete DBMS & Data Warehousing syllabus
Subject Test #8
Complete General Aptitude syllabus
Multi-Subject Revision Tests733231
Multi-Subject Revision Tests — Detailed Topic Coverage
Multi-Subject Test #1
Probability & Statistics + Artificial Intelligence
Multi-Subject Test #2
Calculus + DBMS & Warehousing
Multi-Subject Test #3
Linear Algebra + Aptitude
Multi-Subject Test #4
Machine Learning + Programming & DSA
Multi-Subject Test #5
Probability & Statistics + Calculus + Linear Algebra
Multi-Subject Test #6
Machine Learning + Artificial Intelligence
Multi-Subject Test #7
Programming & DSA + DBMS & Warehousing + Aptitude
Grand / Full-Length Mock Tests1065650
Grand / Full-Length Mock Tests — Detailed Topic Coverage
Grand Test #1
Full GATE DA syllabus — Basic Level (65 questions, 3 hours, negative marking for MCQs)
Grand Test #2
Full GATE DA syllabus — Basic Level (65 questions, 3 hours, negative marking for MCQs)
Grand Test #3
Full GATE DA syllabus — Intermediate Level (65 questions, 3 hours, negative marking for MCQs)
Grand Test #4
Full GATE DA syllabus — Intermediate Level (65 questions, 3 hours, negative marking for MCQs)
Grand Test #5
Full GATE DA syllabus — Intermediate Level (65 questions, 3 hours, negative marking for MCQs)
Grand Test #6
Full GATE DA syllabus — Advanced Level (65 questions, 3 hours, negative marking for MCQs)
Grand Test #7
Full GATE DA syllabus — Advanced Level (65 questions, 3 hours, negative marking for MCQs)
Grand Test #8
Full GATE DA syllabus — GATE-Level Difficulty (65 questions, 3 hours, negative marking for MCQs)
Grand Test #9
Full GATE DA syllabus — GATE-Level Difficulty (65 questions, 3 hours, negative marking for MCQs)
Grand Test #10
Full GATE DA syllabus — GATE-Level Difficulty (65 questions, 3 hours, negative marking for MCQs)
GATE DA Test Series Pricing
Buy standalone or get it free with any GATE DA course enrolment
Standalone GATE DA Test Series
61 tests, 1,685 problems — for self-study candidates
- 61 tests (1,685 problems)
- 36 topic-wise tests
- 8 subject-level tests
- 7 multi-subject revision tests
- 10 full-length grand mock tests
- Detailed solutions & All India ranking
GATE DA Course + Test Series
Complete preparation · 6 months validity
- Everything in Standalone Test Series
- Recorded lectures (all 8 subjects)
- Weekly live classes
- DPPs and assignments
- Success Tracker PRO — unlimited practice & PYQs
- Doubt support
- Members-only Discord
Subject-Wise Test Coverage
36 topic tests + 8 subject tests mapped to all GATE DA core subjects
Probability & Statistics
Topic Test #1–5 + Subject Test #1
Artificial Intelligence
Topic Test #6–9 + Subject Test #2
Calculus & Optimization
Topic Test #10–12 + Subject Test #3
DBMS & Warehousing
Topic Test #13–17 + Subject Test #4
Aptitude
Topic Test #18–22 + Subject Test #5
Machine Learning
Topic Test #23–27 + Subject Test #6
Linear Algebra
Topic Test #28–31 + Subject Test #7
Python & DSA
Topic Test #32–36 + Subject Test #8
Multi-Subject Revision Tests
7 tests combining related subjects — trains concept-switching for the real exam
Probability & Statistics + Artificial Intelligence
Calculus + DBMS & Warehousing
Linear Algebra + Aptitude
Machine Learning + Programming & DSA
Probability & Statistics + Calculus + Linear Algebra
Machine Learning + Artificial Intelligence
Programming & DSA + DBMS & Warehousing + Aptitude
Full-Length GATE DA Mock Tests
10 grand tests — progressive difficulty from basic to GATE-level
Basic Grand Tests
3 testsBuild exam stamina at moderate difficulty. All subjects covered.
Advanced Grand Tests
3 testsTricky MCQs, MSQs, and NAT — tests deeper understanding.
GATE-Level Mock Tests
4 testsClosest simulation to the actual GATE DA paper.
Every mock includes 65 questions (MCQ + MSQ + NAT), a 3-hour timer, negative marking, and a GATE-style interface. Instant scoring, subject-wise analysis, and detailed solutions provided after submission.
Why a DA-Specific Test Series Matters
GATE DA tests Python (not C), emphasises probability and machine learning over discrete math, and includes AI as a core subject. Generic GATE CS mocks miss these topics entirely. This test series is built from scratch for the DA pattern — modelled on GATE DA 2024, 2025, and 2026 papers. For a full overview, read our GATE DA complete guide.
| Feature | The ML Hub | Generic Test Series |
|---|---|---|
| Built for | GATE DA (Data Science & AI) | GATE CS or mixed papers |
| Syllabus Match | 100% DA syllabus aligned | Covers CS topics not in DA |
| Programming | Python (DA standard) | C programming (CS standard) |
| ML & AI | Core focus (~22% weightage) | Absent or minimal |
| Question Pattern | Modelled on GATE DA 2024–2026 | Based on older CS patterns |
| Designed By | GATE DA toppers (AIR 9, AIR 6) | CS-focused faculty |
| Solutions | Detailed step-by-step | Brief or answer-only |
Our verified GATE DA toppers consistently credit DA-specific mock test practice as a key factor in their results.
What Toppers Say
Real feedback from GATE DA rankers who used this test series
“The mock tests were incredibly close to the actual GATE DA pattern. The performance analysis helped me identify exactly which topics needed more work in the final weeks.”
Harsh Raja
AIR 16, GATE DA 2026
“Solving problems daily made a huge difference in building speed and accuracy for the actual exam.”
Rohan Khamitkar
AIR 44, GATE DA 2025
“The GDMTs were the closest simulation to the real GATE DA exam I found anywhere. The detailed solutions helped me understand my mistakes properly.”
Anshuman Dangwal
AIR 49, GATE DA 2025
Frequently Asked Questions
What is the best GATE DA test series for 2027?+
The ML Hub GATE DA Test Series 2027 is designed by Jay Bansal (AIR 9 GATE DA 2026) and Sriniwas Paliwal (IIT Bombay). It includes 61 tests with 1,685 practice problems — 36 topic-wise tests, 8 subject tests, 7 multi-subject revision tests, and 10 full-length grand mock tests. Every test includes detailed solutions and performance analysis — all built specifically for the GATE DA exam pattern, not adapted from GATE CS.
Does the GATE DA test series include solutions?+
Yes. Every test — topic-wise, subject-wise, and full-length mock — includes detailed step-by-step solutions. Solutions explain the concept, the approach, and common mistakes so you learn from every question.
Is the test series included in the GATE DA course?+
Yes. The complete GATE DA test series is included with both Core and Elite course enrolments. You can also purchase the test series separately if you only need practice tests without the full course.
How many mock tests are in the GATE DA test series?+
The test series includes 61 tests in total with 1,685 practice problems: 36 topic-wise tests (15 problems each), 8 subject tests (33 problems each), 7 multi-subject revision tests (33 problems each), and 10 full-length grand mock tests (65 questions, 3 hours, negative marking for MCQs). Grand tests progress from basic to advanced to GATE-level difficulty.
Is the GATE DA test series available online?+
Yes. The entire GATE DA test series is online and accessible 24/7 from any device. The interface closely matches the actual GATE exam to help you get comfortable with the test environment.
Can I get unlimited practice questions in addition to the test series?+
Yes, with a full course enrolment. Both the GATE DA Core and Elite programs include a free Success Tracker PRO subscription (worth ₹999/year) on top of this test series. It adds unlimited topic-wise practice, all GATE DA previous-year questions from 2024 to 2026 in test mode with detailed solutions, topic-wise skill scores that update after every question, and an AI copilot for doubt support. The standalone test series purchase covers the 61 tests and 1,685 problems only.
Does the test series cover the full GATE DA syllabus?+
Yes. The test series covers all 8 core GATE DA subjects: Probability & Statistics, Linear Algebra, Calculus & Optimization, Programming in Python, Data Structures & Algorithms, DBMS & Warehousing, Machine Learning, and Artificial Intelligence — plus General Aptitude.
Is this test series different from GATE CS test series?+
Yes, completely. GATE DA has a fundamentally different syllabus from GATE CS — it tests Python (not C), emphasises probability and statistics over discrete math, and includes machine learning and AI as core subjects. Generic GATE CS mock tests will not prepare you for DA. This test series is built from scratch for the GATE DA pattern.
What results have ML Hub test series users achieved?+
In GATE DA 2026, The ML Hub students achieved 5 in Top 100 (including AIR 9, AIR 16, AIR 59, AIR 72 and AIR 97), 12 in Top 200, and 21 in Top 500. Our toppers consistently credit mock test practice and DPP analysis as key differentiators in their preparation.
Ready to Start Practising?
61 tests, 1,685 problems — designed by GATE DA toppers. Join now or explore the full course.