One of the premier institute , indian Institute Indian Institute of Technology Kanpur is a public engineering institution located in Kanpur, Uttar Pradesh. It was declared to be an Institute of National Importance by the Government of India under the Institutes of Technology Act.
IIT Kanpur takes Mtech Admission through GATE Exam. It has released its first list for Mtech, MS and PHD applicants of shorlisted for Written Test & programming test on 11 April 2018. Note that , second and final list will be declared after last date of application submission gets over.
Criteria (GATE Score cut-off) for Mtech:
GEN & OBC: 725
SC,ST & PD: 478
Interview Date : May 14 , 2018
Criteria (GATE Score cut-off) for MS:
GEN & OBC: 675
SC,ST & PD: 445
Also, note that this year IIT Kanpur has done slight changes in its syllabus. Syllabus for Written Test and Programming Test are as Follows :
Information on the M.Tech/MS/PhD admission Test
Following are two groups of topics. In the admissions test, each candidate will be asked to answer questions from one group of topics. Note that, choice of group here will not restrict an applicant’s choice of allowed courses/research areas in M.Tech/M.S./Ph.D. Click here for a sample test.
Group 1: Theory List
Basic Number Theory:
Data Structures and Algorithms:
Computability and Complexity:
Basic counting techniques (permutation and combination), pigeon-hole principle, simple recurrence relations, generating functions, principle of inclusion and exclusion (set cardinality related problems)
Graphs, Directed Graphs, Trees, Connectivity, Cycles, Paths, Hamiltonian and Eulerian cycles, subgraphs, cliques, graph coloring, planarity
Modular Arithmetic, Fermat’s Little Theorem, principles of RSA (discrete logarithm problem, primality, integer factorization)
propositional logic, tautologies, axiom systems, deduction, soundness and completeness, quantification
Simple Group theory — groups, subgroups, cosets, Lagrange’s theorem, fields, finite fields
Elementary data structures — arrays, lists, queues, stacks, and their applications, algorithms for various manipulations of these data structures (sort, search, insert, delete, computing size), basic paradigms of designing algorithms (greedy algorithms, divide-and-conquer approaches, dynamic programming), analyzing time and space complexity of algorithms (O(n) vs O(logn) vs. O(nlogn) vs. O(n^2) etc.)
P vs. NP, NP-Completeness, simple polynomial time reductions, Turing machines, undecidability.
vector spaces, dot products and their properties, orthogonality, norms and their properties, Cauchy-Schwartz inequality, hyperplanes, halfspaces, balls, ellipsoids.
determinants, eigenvalues-eigenvectors, matrix norms (Frobenius, spectral).
linear combination of vectors (convex combination, conic combination, affine combination), notion of gradient for multivariate functions, convex sets and convex functions (definitions only).
event spaces and their properties, probability measure, cumulative distribution, random variables, marginal and joint distributions, expectation, variance, independence of events and random variables, linearity of expectation. Statistics: distributions and their properties (Bernoulli, Binomial, Multinomial, Poisson, Gaussian).
Some good resources for studying (8-11):
The following scribed notes cover 8), 9), 10), 11) in a succinct manner with examples. However, these notes are merely indicative of the topics and not to be treated as the sole or even recommended sources for these topics. Students are advised to refer to more elaborate treatments of these topics from textbooks as well.
Group 2: Systems List
Data Structures and Programming :
Instruction Set architecture, pipelined implementation of instruction set architecture, caches, cache organization, cache replacement, virtual memory, demand paging, page replacement
Unix/Linux operating system structure, processes, threads, process scheduling, concurrent processes and threads, virtual memory management, unix/linux process memory layout (memory segmentation), program stack, and heap and their roles in program run-time, file system permissions, basic unix/linux commands, system calls, kernel vs. user space programs, shared libraries (static vs. dynamically linked). Familiarity with virtual machines, cloud based computing.
OSI seven layer reference model, TCP/IP protocol stack, division of functionalities in various layers, basic functionalities of TCP and IP, DNS, some protocols (OSPF, BGP, ARP)
Lexical analysis (Deterministic Finite State Automata), Parsing (LALR, LL(1)), peephole optimization, code motion.
Basic SQL queries, relations and relational database
Data structures and programming in C or C++ or Java
Some good resources for studying:
- Computer Organization and Design, Fourth Edition (or any edition) : The Hardware/Software Interface (The Morgan Kaufmann Series in Computer Architecture and Design) 4th Edition by David A. Patterson and John L. Hennessy.
- Computer Architecture: A Quantitative Approach by Hennessy and Patterson.
- Operating Systems: Three Easy Pieces by Remzi H. Arpaci-Dusseau and Andrea C. Arpaci-Dusseau.
- Modern Operating Systems (4th Edition): Andrew S. Tanenbaum, Herbert Bos (any Edition)
- Computer Networks, Andrew S. Tanenbaum, 4th Edition (or any edition), Prentice Hall.
- Iterators, loops, nesting
- Encapsulation primitives (structures, classes – depending on language)
- Proficiency in programming in general
Note : This time there is no Advance (second Round) written test for Mtech Applicants.