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GATE 2026 IIT Guwahati - TO IITM

Table

Table

Title

Start

Reg starts

08/08/2025

Reg ends(no fine)

28/09/2025

Reg ends with fine

09/10/2025

There are no rows in this table

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CS and DA

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CS_2026_Syllabus.pdf

548.2 kB

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DA_2026_Syllabus.pdf

535.7 kB

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Combined Syllabus: CS & DA

1. Engineering Mathematics

Common Topics:

Probability and Statistics: Random variables, Uniform, normal, exponential, Poisson, binomial distributions. Mean, median, mode, standard deviation. Conditional probability, Bayes Theorem.

Linear Algebra: Matrices, determinants, systems of linear equations, eigenvalues, eigenvectors, LU decomposition.

Calculus: Limits, continuity, differentiability, maxima and minima.

CS Unique:

Discrete Mathematics: Propositional and first order logic. Sets, relations, functions, partial orders, lattices. Monoids, Groups. Graphs (connectivity, matching, colouring). Combinatorics (counting, recurrence relations, generating functions).

Calculus: Mean value theorem, Integration.

DA Unique:

Probability and Statistics: Counting (permutation/combinations), probability axioms, Sample space, events (independent, mutually exclusive), marginal, conditional, joint probability. Conditional expectation and variance, correlation, covariance. Discrete random variables, probability mass functions (Bernoulli). Continuous random variables, probability distribution functions (standard normal, t-distribution, chi-squared). Cumulative distribution function, Conditional PDF, Central limit theorem, confidence interval, z-test, t-test, chi-squared test.

Linear Algebra: Vector space, subspaces, linear dependence/independence. Projection, orthogonal, idempotent, partition matrices. Quadratic forms. Gaussian elimination, rank, nullity, projections, singular value decomposition.

Calculus and Optimization: Taylor series, optimization involving a single variable.

2. Programming, Data Structures & Algorithms

Common Topics:

Data Structures: Stacks, queues, linked lists, trees, graphs.

Algorithms: Graph traversals, shortest path, divide and conquer strategy.

CS Unique:

Programming: Programming in C, Recursion.

Data Structures: Arrays, binary search trees, binary heaps.

Algorithms: Searching (general), sorting (general), hashing. Asymptotic worst case time and space complexity. Algorithm design techniques (greedy, dynamic programming). Minimum spanning trees.

DA Unique:

Programming: Programming in Python.

Data Structures: Hash tables.

Algorithms: Specific search algorithms (linear, binary search). Specific sorting algorithms (selection sort, bubble sort, insertion sort, mergesort, quicksort). Introduction to graph theory.

3. Databases & Data Warehousing

Common Topics:

ER-model, Relational model (relational algebra, tuple calculus, SQL). Integrity constraints, normal forms. File organization, indexing.

CS Unique:

Indexing (e.g., B and B+ trees). Transactions and concurrency control.

DA Unique:

Data types. Data transformation (normalization, discretization, sampling, compression). Data warehouse modelling (schema for multidimensional data models, concept hierarchies, measures: categorization and computations).

4. Computer Systems & Networks (CS Unique)

Digital Logic: Boolean algebra. Combinational and sequential circuits. Minimization. Number representations and computer arithmetic (fixed and floating point).

Computer Organization and Architecture: Machine instructions, addressing modes. ALU, data-path, control unit. Instruction pipelining, pipeline hazards. Memory hierarchy (cache, main, secondary storage). I/O interface (interrupt, DMA mode).

Operating System: System calls, processes, threads, inter-process communication, concurrency and synchronization. Deadlock. CPU and I/O scheduling. Memory management, virtual memory. File systems.

Computer Networks: Concept of layering (OSI, TCP/IP). Packet, circuit, virtual circuit-switching. Data link layer (framing, error detection, MAC, Ethernet bridging). Routing protocols (shortest path, flooding, distance vector, link state). Fragmentation, IP addressing (IPv4, CIDR). IP support protocols (ARP, DHCP, ICMP), NAT. Transport layer (flow/congestion control, UDP, TCP, sockets). Application layer protocols (DNS, SMTP, HTTP, FTP, Email).

5. Theory of Computation & Compiler Design (CS Unique)

Theory of Computation: Regular expressions, finite automata. Context-free grammars, push-down automata. Regular and context-free languages, pumping lemma. Turing machines, undecidability.

Compiler Design: Lexical analysis, parsing, syntax-directed translation. Runtime environments. Intermediate code generation. Local optimization. Data flow analyses (constant propagation, liveness analysis, common sub expression elimination).

6. Artificial Intelligence & Machine Learning (DA Unique)

Machine Learning:

Supervised Learning: Regression and classification problems. Simple/multiple linear regression, ridge regression, logistic regression. k-nearest neighbour, naive Bayes classifier, linear discriminant analysis, support vector machine, decision trees. Bias-variance trade-off. Cross-validation (LOO, k-folds). Multi-layer perceptron, feed-forward neural network.

Unsupervised Learning: Clustering algorithms (k-means/k-medoid, hierarchical: single-linkage, multiple-linkage). Dimensionality reduction, principal component analysis.

AI: Search (informed, uninformed, adversarial). Logic (propositional, predicate). Reasoning under uncertainty (conditional independence representation, exact inference via variable elimination, approximate inference via sampling).

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