GATE 2027 Data Science and Artificial Intelligence Official Syllabus
Section 1: General Aptitude (Common to All Papers • 15 Marks)
Verbal, Quantitative, Analytical & Spatial Reasoning
Verbal Aptitude, Quantitative Aptitude, Analytical Aptitude, and Spatial Aptitude (Common 15 Marks).
Section 2: Engineering Mathematics (Core Component)
Mathematical Foundations
Probability and Statistics (Counting, axioms of probability, conditional probability, Bayes theorem, independent events, discrete random variables, continuous random variables, expectation, variance, covariance, correlation, Law of Large Numbers, Central Limit Theorem); Linear Algebra (Vector spaces, linear independence, basis, dimension, linear transformations, matrices, determinants, eigenvalues, eigenvectors, projection, singular value decomposition SVD); Calculus and Optimization (Functions of single variable, limit, continuity and differentiability, Taylor series, maxima and minima, functions of several variables, partial derivatives, gradient, directional derivative, Hessian, unconstrained optimization, gradient descent).
Section 3: Subject-Specific Core Syllabus (85 Marks)
Technical Domain Breakdown
Programming, Data Structures and Algorithms (Python programming, basic data structures: stacks, queues, linked lists, trees, hash tables; search algorithms: linear search, binary search, basic sorting algorithms, divide and conquer, greedy algorithms, dynamic programming); Database Management and Warehousing (ER-model, relational algebra, SQL, querying, relational database design: normal forms, indexing, data warehousing concepts: schema design, OLAP); Machine Learning (Supervised learning: linear regression, logistic regression, k-nearest neighbours, naive Bayes, decision trees, support vector machines, neural networks; Unsupervised learning: k-means clustering, hierarchical clustering, PCA; Evaluation metrics: accuracy, precision, recall, F1-score, ROC-AUC, cross-validation); Artificial Intelligence (Search: informed, uninformed, adversarial search, heuristic search; Logic: propositional logic, predicate logic; Reasoning under uncertainty: conditional independence, exact inference, probabilistic reasoning).