GATE Test Series

GATE DA 2026 TEST SERIES

GATE Data Science & Artificial Intelligence 2026 Test Series

Welcome to the most comprehensive and strategic GATE Data Science & Artificial Intelligence 2026 Test Series offered by Mindspan Education …

55+

Tests

1400+

Questions

Mindspan Education - GATE Test Series
Mindspan Education

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GATE DA 2…

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This Test Series Includes:
  • 55+ comprehensive tests
  • Detailed performance analytics
  • Access until the next GATE exam
  • Access on mobile and desktop
  • Detailed Solution
  • Bookmark Question

About This Test Series

GATE Data Science & Artificial Intelligence 2026 Test Series

Welcome to the most comprehensive and strategic GATE Data Science & Artificial Intelligence 2026 Test Series offered by Mindspan Education. Designed to simulate the real exam environment and boost your preparation through step-by-step testing, our test series ensures you cover every topic, every concept, and every type of question that GATE DA demands.

Key Features of Mindspan's GATE DA Test Series

  • 1400+ High-Quality Questions: Curated to match GATE standards with deep concept coverage
  • 60+ Full-Length and Topicwise Tests: Well-planned across topicwise, subjectwise, and mock formats
  • 8 Full Mock Tests: Simulate the actual GATE DA exam with exact 3-hour interface and difficulty level
  • Detailed Solutions & Explanations: Every question comes with step-by-step reasoning
  • Exact GATE Exam Interface: Familiarize yourself with the official GATE exam pattern and UI
  • Bookmark Questions: Save important or tricky questions to revisit anytime
  • Practice Mode: Re-attempt questions in practice mode after submission for stronger retention

Complete Test Structure

1. Topicwise Tests (Tests 1-23)

Master individual topics with focused 15-question tests covering all GATE DA subjects:

Test No. Subject & Topic Questions Marks Time
1 Probability & Statistics - Counting, permutations, combinations, probability axioms, sample space, events, Bayes Theorem 15 20 35 mins
2 Probability & Statistics - Discrete random variables, PMFs, Bernoulli, uniform, binomial, marginal, joint, conditional probability, conditional expectation and variance, standard deviation 15 20 35 mins
3 Probability & Statistics - Continuous random variables, PDFs, CDFs, uniform exponential, Poisson, normal, t, chi-squared, conditional PDF 15 20 35 mins
4 Probability & Statistics - Mean, median, mode, covariance, correlation, CLT, confidence intervals, z-test, t-test, chi-squared test 15 20 35 mins
5 Linear Algebra - Systems of linear equations, Gaussian elimination, LU decomposition, matrices, linear dependence and independence of vectors 15 20 35 mins
6 Linear Algebra - Vector space, subspace, eigenvalues, eigenvectors, determinant, rank, nullity 15 20 35 mins
7 Linear Algebra - Projections, projection matrix, orthogonal matrix, idempotent and partition matrices 15 20 35 mins
8 Linear Algebra - Quadratic forms, SVD 15 20 35 mins
9 Calculus & Optimization - Functions of single variable, limits, continuity, differentiability 15 20 35 mins
10 Calculus & Optimization - Taylor series, maxima and minima, optimization involving a single variable 15 20 35 mins
11 Python & DSA - Programming in Python 15 20 35 mins
12 Python & DSA - Stacks, queues, linked lists, trees, hash tables 15 20 35 mins
13 Python & DSA - Search algorithms: linear search and binary search, basic sorting algorithms: selection sort, bubble sort and insertion sort; divide and conquer: mergesort, quicksort 15 20 35 mins
14 Python & DSA - Introduction to graph theory; basic graph algorithms: traversals and shortest 15 20 35 mins
15 DBMS & Warehousing - ER model, relational algebra, SQL, tuple calculus 15 20 35 mins
16 DBMS & Warehousing - Integrity constraints, normal form, file organization, indexing, data types, data transformation such as normalization, discretization, sampling, compression 15 20 35 mins
17 DBMS & Warehousing - Data warehouse modelling: schema for multidimensional data models, concept hierarchies, measures: categorization and computations 15 20 35 mins
18 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 15 20 35 mins
19 Machine Learning - 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 15 20 35 mins
20 Machine Learning - Clustering algorithms, k-means/k-medoid, hierarchical clustering, top-down, bottom-up: single-linkage, multiple-linkage, dimensionality reduction, principal component analysis 15 20 35 mins
21 Artificial Intelligence - Informed/uninformed/adversarial search 15 20 35 mins
22 Artificial Intelligence - Logic, propositional, predicate 15 20 35 mins
23 Artificial Intelligence - Reasoning under uncertainty topics — conditional independence representation, exact inference through variable elimination, and approximate inference through sampling 15 20 35 mins

2. Subject-wise Tests (Tests 24-52)

Comprehensive subject-level practice with multiple tests per subject:

Test No. Subject Questions Marks Time
24-25 Aptitude (2 Tests) - Numerical reasoning, data interpretation, verbal ability, logical reasoning 20 30 55 mins
26-29 Linear Algebra (4 Tests) - Complete subject coverage 20 30 55 mins
30-33 Python & DSA (4 Tests) - Complete subject coverage 20 30 55 mins
34-37 Probability & Statistics (4 Tests) - Complete subject coverage 20 30 55 mins
38-40 Calculus & Optimization (3 Tests) - Complete subject coverage 20 30 55 mins
41-44 DBMS & Warehousing (4 Tests) - Complete subject coverage 20 30 55 mins
45-48 Machine Learning (4 Tests) - Complete subject coverage 20 30 55 mins
49-52 Artificial Intelligence (4 Tests) - Complete subject coverage 20 30 55 mins

3. Full Syllabus Tests (Tests 53-60)

Complete GATE DA simulation with full syllabus coverage:

Test No. Test Type Questions Marks Time
53-57 Full Syllabus Tests (5 Tests) 65 100 180 mins
58-60 All India Mock Tests 2026 (3 Tests) 65 100 180+ mins

What's Included in the Test Plan?

  1. Topicwise Tests: Practice 15 questions per topic across all GATE DA subjects like Probability, Statistics, ML, AI, Python, DBMS, and Linear Algebra
  2. Subjectwise Tests: Test your depth with multiple focused tests per subject for comprehensive coverage
  3. Full-Length Mock Tests: 8 complete tests with 65 questions and 100 marks each – exactly like GATE DA exam format

Click here to view the complete test plan and activation schedule

Click here to view the test series announcement

Who Is This For?

This test series is designed for serious aspirants aiming for top ranks in GATE DA 2026. Whether you're a final-year student, a working professional, or a repeat aspirant — this is your one-stop practice destination.

Why Choose Mindspan Education?

At Mindspan Education, we believe in smart, structured, and targeted preparation. Our test series is built not just to test, but to teach — by helping you learn from mistakes, sharpen concepts, and improve with every attempt.

Get ready to crack GATE DA 2026 with confidence. Enroll in the Mindspan Test Series today and take the first step toward your dream score.

What You'll Learn

  • Evaluate your knowledge of GATE Data Science & AI topics
  • Practice time management under exam conditions
  • Identify knowledge gaps through detailed analytics
  • Get familiar with the actual GATE exam pattern

Requirements

  • Basic understanding of Gate data science and ai subjects
  • Familiarity with core mathematical principles
  • Regular practice and commitment to improvement

Key Features

GATE Pattern Tests

Designed to exactly match the GATE exam pattern and difficulty level

Detailed Analytics

Comprehensive performance reports with detail solution

Detailed Solutions

Step-by-step explanations for every question to enhance understanding

Available Tests

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