GATE 2024: IISc Releases Revised Data Science, AI Sample Paper

The GATE 2024 Data Science and AI examination paper comprises 55 questions. The initial 25 questions carry one mark each, while the subsequent 30 questions are worth two marks each.

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GATE 2024: The examination will be held on February 3, 4, 10, and 11, 2024.
New Delhi:

The Indian Institute of Science (IISc), Bengaluru today released the updated sample question paper for Data Science and Artificial intelligence (AI) for the Graduate Aptitude Test in Engineering (GATE) 2024. Prospective candidates can access the sample papers and syllabus on the official website at gate2024.iisc.ac.in. The examination will be held on February 3, 4, 10, and 11, 2024.

The GATE 2024 Data Science and AI examination paper comprises 55 questions. The initial 25 questions carry one mark each, while the subsequent 30 questions are worth two marks each.
 

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GATE 2024 Data Science and AI Syllabus

The Data Science and AI syllabus includes Probability and Statistics, Linear Algebra, Calculus and Optimization, Programming, Data Structures and Algorithms, Database Management and Warehousing, Machine Learning, and Artificial Intelligence.

Probability and Statistics

This section includes counting (permutations and combinations), probability axioms, sample space, events, independent events, mutually exclusive events, marginal, conditional, and joint probability, Bayes Theorem, conditional expectation, variance, mean, median, mode, and standard deviation, correlation, and covariance, random variables, discrete random variables, and probability mass functions, uniform, Bernoulli, binomial distribution, and more.

Linear Algebra

Subjects covered in this section include vector space, subspaces, the relationship between vectors and their independence, matrices, projection matrix, orthogonal matrix, idempotent matrix, partition matrix, and their characteristics. Additionally, it includes quadratic forms, solving systems of linear equations, methods like Gaussian elimination, eigenvalues, eigenvectors, determinants, rank, nullity, projections, LU decomposition, and singular value decomposition.

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Calculus and Optimisation

This section covers topics such as functions with a single variable, exploring concepts like limits, continuity, and differentiability. It also includes the study of Taylor series, as well as the analysis of maxima and minima, focusing on optimization involving a single variable.

Programming, Data Structures and Algorithms

Candidates need to prepare themselves for programming in Python, basic data structures: stacks, queues, linked lists, trees, hash tables; Search algorithms: linear search and binary search, basic sorting algorithms: selection sort, bubble sort, and insertion sort; divide and conquer: mergesort, quicksort; introduction to graph theory; basic graph algorithms: traversals and shortest path.

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Database Management and Warehousing

This section covers the ER-model, relational model: relational algebra, tuple calculus, SQL, integrity constraints, normal form, file organization, indexing, data types, data transformation such as normalization, discretization, and more.

Machine Learning

Supervised Learning: This includes regression and classification problems, simple linear regression, multiple linear regression, ridge regression, logistic regression, k-nearest neighbor, naive Bayes classifier, linear discriminant analysis, support vector machine, decision trees, 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.

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Unsupervised Learning: Topics covered are clustering algorithms, k-means/k-medoid, hierarchical clustering, top-down, bottom-up: single-linkage, multiple-linkage, dimensionality reduction, principal component analysis.

Artificial Intelligence Search: Informed, uninformed, adversarial; logic, propositional, predicate; reasoning under uncertainty topics - conditional independence representation, exact inference through variable elimination, and approximate inference through sampling.

Click here to access the sample paper.

GATE 2024 Exam Pattern

The GATE 2024 exam pattern includes a duration of 3 hours, 30 sections, and multiple-choice questions (MCQ), multiple select questions (MSQ), and/or numerical answer type (NAT) questions. The distribution of marks varies across different papers, with a total of 100 marks for most papers. Additionally, it's important to note that the exam conducting authority will not entertain queries or provide answer keys for the sample question papers.

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