2019 2020 2021 Student Forum Phd In Computer Science In IIT Guwahati

#1
23rd May 2015, 12:00 PM
 Unregistered Guest
Phd In Computer Science In IIT Guwahati

I want to do Phd in Computer Science from Indian Institute of Technology Guwahati so tell me the entrance exam for admission in this course? When admission will start in this Institute? Provide me the course structure of Phd Computer Science of this Institute?
#2
30th March 2020, 08:24 AM
 Super Moderator Join Date: Aug 2012
Re: Phd In Computer Science In IIT Guwahati

Ph.D Admission (December 2019): Syllabus for the Written Test

Part A

[Compulsory for all candidates] (1) General Aptitude: Verbal Ability: English grammar, Sentence completion, Verbal analogies, Word groups, Instructions, Critical reasoning and verbal deduction. Numerical Ability: Numerical computation, Numerical estimation, Numerical reasoning and data interpretation.

(2) Discrete Mathematics: Propositional Logic; Probability - Conditional Probability; Mean, Median, Mode and Standard Deviation; Random Variables; Distributions- Uniform, Normal, Exponential, Poisson, Binomial. Set Theory -Sets; Relations; Functions; Groups; Partial Orders; Lattice; Boolean algebra. Combinatorics - Permutations; Combinations; Counting; Summation; Generating functions; Recurrence relations; Graph Theory - Connectivity; Spanning trees; Cut vertices and edges; Covering; Matching; Independent sets; Coloring; Planarity; Isomorphism.

(3) Programming and Data Structures: Programming in C; Structures, Pointers, Functions, Recursion, Parameter passing, Scope, Binding; Abstract data types, Arrays, Stacks, Queues, Linked Lists, Trees, Binary search trees, Binary heaps, Graphs.

Part B

(1) Algorithms: Analysis of algorithms, Asymptotic notation, Notions of space and time complexity, Worst and average case analysis; Design: Greedy approach, Dynamic programming, Divide-and-conquer; Tree and graph traversals, Connected components, Spanning trees, Shortest paths; Hashing, Sorting, Searching. Asymptotic analysis of upper and lower bounds, Basic concepts of complexity classes P, NP, NP-hard, NP-complete.

(2) Formal Languages and Automata Theory: Alphabets, languages, grammars; Finite automata; Regular languages, Regular expressions; Context-free languages: Pushdown automata, Context sensitive languages: Linear bounded automata; Turing machines: recursively enumerable languages; Undecidability; Operations on formal languages and their properties; Chomsky hierarchy; Decision questions on languages.

(3) Computer Organization and Architecture: Logic functions, Minimization, Combinational and sequential circuits; Representation of fixed and floating point numbers; Computer arithmetic. Machine instructions and addressing modes, RISC and CISC paradigms, Instruction pipelining; Memory interface; Memory hierarchy - Cache memory, main memory, secondary storage; I/O transfer techniques: Program controlled, Interrupt controlled, DMA transfer.

(4) Operating Systems: Processes, Threads, Inter-process communication, Concurrency: Mutual exclusion; Synchronization; Semaphores, Deadlock management, CPU scheduling, Memory Management: Allocation, Protection, Paging, Segmentation; Virtual Memory concepts. File Management, File Systems: Allocation, Free space management, Directory management, I/O Management: Device drivers, Disk scheduling algorithms.

(5) Computer Networks: Basics of digital communications, Guided and unguided media, ISO/OSI stack, LAN technologies (Ethernet, Token ring), Flow and error control techniques, Routing algorithms, Congestion control, TCP/UDP and sockets, IPv4 and IPv6, Interconnection devices - Hubs, Switches, Gateways, and Routers; Application layer protocols.

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