GATE CS/IT & DATA SCIENCE & AI (DA) EXAMINATION HUB
GATE Strategy, Subject Lenses & Weightage
Dual-track exam-oriented preparation for both GATE CS/IT (13 subjects) and GATE Data Science & Artificial Intelligence (DA, 8 subjects). Filter by curriculum branch, inspect high-yield numerical patterns, and dive directly into verified PYQs.
Subject-Wise GATE Lenses & Weightage
Click any subject to open its GATE Exam LensGeneral Aptitude
Verbal, numerical, and logical reasoning for GATE CS/IT & DA.
Numerical ability, Spatial aptitude, Reading comprehension, Syllogisms
Engineering Mathematics
The mathematical foundation behind every CS concept.
Eigenvalues & Eigenvectors, System of Linear Equations, Bayes' Theorem, Calculus
Discrete Mathematics
Sets, relations, logic, and graphs — the language of CS.
Propositional logic & inference, Graph coloring & isomorphism, Generating functions
Digital Logic
From Boolean algebra to sequential circuits.
K-Map minimization, Multiplexers & Decoders, Flip-Flops & Counter state cycles
Computer Organization & Architecture
How the hardware underneath actually works.
Pipelining hazards & speedup, Cache mapping (Direct, Set-Associative), IEEE 754
Programming in C
Pointers, memory, and the art of thinking in C.
Pointer arithmetic, Recursion tree tracing, Operator precedence, Storage classes
Data Structures
The building blocks of efficient programs.
Binary Search Trees, AVL Trees, Heap operations, Hashing collision resolution
Algorithms
Sorting, searching, and solving the unsolvable.
Asymptotic bounds, Divide & Conquer (Master Theorem), DP, Dijkstra & Bellman-Ford
Theory of Computation
What can be computed — and what can't.
DFA minimization, Closure properties, Decidability, Regular expressions
Compiler Design
How your code becomes a running program.
FIRST & FOLLOW, LL(1) / LR(1) parsing tables, Syntax-Directed Translation (SDT)
Operating Systems
Understand the invisible machinery behind every program you run.
CPU Scheduling (RR, SJF), Paging & TLB EMAT, Banker's Safe State, Semaphores
Database Management Systems
From relational schemas to transactions and data warehousing.
B+ Tree index calculations, Normal Forms (BCNF, 3NF), Conflict Serializable schedules, Data Warehousing
Computer Networks
How data travels across the world in milliseconds.
IPv4 Subnetting & CIDR, Sliding Window (Go-Back-N, SR), TCP Congestion Control
Probability and Statistics
Counting, conditional probability, distributions, and hypothesis testing for Data Science.
Bayes' Theorem, Conditional Expectation, Normal/Poisson Distributions, Hypothesis Testing (t-test, z-test, p-value)
Linear Algebra
Vector spaces, projections, SVD, eigenvalues and PCA foundations.
Vector Spaces & Subspaces, SVD Factorization, Eigenvalues & Cayley-Hamilton, Projections & Least Squares
Calculus and Optimization
Multivariable gradients, Hessian matrices, convex sets, and gradient descent.
Gradient Descent & step size, Hessian Matrix, Convex Sets & Functions, Lagrange Multipliers
Machine Learning
Supervised & unsupervised algorithms, neural networks, SVMs, and bias-variance tradeoff.
Bias-Variance Tradeoff, SVM Max-Margin & Kernels, Decision Tree Information Gain, Cross-Entropy Loss, ROC-AUC
Artificial Intelligence
Search algorithms, heuristic A*, adversarial minimax, and logic reasoning.
A* Admissible & Consistent Heuristics, Alpha-Beta Pruning, Minimax Game Trees, Propositional Inference