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GATE Computer Science and Information Technology (CS) Syllabus
Section 1: Engineering Mathematics
Discrete Mathematics: Propositional and first order logic. Sets, relations, functions, partial orders and lattices. Monoids, Groups. Graphs: connectivity, matching, colouring. Combinatorics: counting, recurrence relations, generating functions.
Linear Algebra: Matrices, determinants, system of linear equations, eigenvalues and eigenvectors, LU decomposition.
Calculus: Limits, continuity and differentiability, Maxima and minima, Mean value theorem, Integration.
Probability and Statistics: Random variables, Uniform, normal, exponential, Poisson and binomial distributions. Mean, median, mode and standard deviation. Conditional probability and Bayes theorem.
Section 2: Digital Logic
Boolean algebra. Combinational and sequential circuits. Minimization. Number representations and computer arithmetic (fixed and floating point).
Section 3: Computer Organization and Architecture
Machine instructions and addressing modes. ALU, data‐path and control unit. Instruction pipelining, pipeline hazards. Memory hierarchy: cache, main memory and secondary storage; I/O interface (interrupt and DMA mode).
Section 4: Programming and Data Structures
Programming in C. Recursion. Arrays, stacks, queues, linked lists, trees, binary search trees, binary heaps, graphs.
Section 5: Algorithms
Searching, sorting, hashing. Asymptotic worst case time and space complexity. Algorithm design techniques: greedy, dynamic programming and divide‐and‐conquer. Graph traversals, minimum spanning trees, shortest paths.
Section 6: Theory of Computation
Regular expressions and finite automata. Context-free grammars and push-down automata. Regular and context-free languages, pumping lemma. Turing machines and undecidability.
Section 7: 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.
Section 8: Operating System
System calls, processes, threads, inter‐process communication, concurrency and synchronization. Deadlock. CPU and I/O scheduling. Memory management and virtual memory. File systems.
Section 9: Databases
ER‐model. Relational model: relational algebra, tuple calculus, SQL. Integrity constraints, normal forms. File organization, indexing (e.g., B and B+ trees). Transactions and concurrency control.
Section 10: Computer Networks
Concept of layering: OSI and TCP/IP Protocol Stacks; Basics of packet, circuit and virtual circuit-switching; Data link layer: framing, error detection, Medium Access Control, Ethernet bridging; Routing protocols: shortest path, flooding, distance vector and link state routing; Fragmentation and IP addressing, IPv4, CIDR notation, Basics of IP support protocols (ARP, DHCP, ICMP), Network Address Translation (NAT); Transport layer: flow control and congestion control, UDP, TCP, sockets; Application layer protocols: DNS, SMTP, HTTP, FTP, Email.
Examination Mode – Computer-Based Test (Online)
Duration – 3 Hours
Sections – 2
General Aptitude (GA) and Course Subject
Type of Questions – Multiple Choice Questions (MCQs), Multiple Select Questions (MSQ), and Numerical Answer Type (NAT) Questions.
Design of Questions – Application, Analysis, synthesis, Comprehension, and Recall
Number of Questions
10 (GA) + 55 (subject) = 65 Questions
Total Marks – 100 Marks
Marking Scheme – All of the questions will be worth 1 or 2 marks
Negative Marking
Multiple Choice Questions (MCQ)
There is NO negative marking for
Preparing for GATE Data Science & AI is not an easy task and if you are going with self preparation it needs a lot of discipline. There is a lot of confusion about where to start and what to read. There is always a way out of this confusion and that is what this section is all about. Read the following articles to get an idea…
Early Revision Technique
There is no substitute for early revision. You need to start early.
You really want to give yourself sufficient time to revise all that you have contemplated and ensure that you grasp it. Last moment revision is considered useless. Revise each subject as you go, and ensure that you revise it completely as this will make modification a lot more straightforward. Eventually, the best tip is to focus on and know your syllabus, and beginning early is the most effective way to accomplish this.
Vary your revision techniques
Continuously revising, for example, reading your notes regarding a topic, is probably going to be very dull. Brighten up your revision period by revising various topics and methods.
Practice old question papers
Doing revision on previous papers will test your comprehension skills. Revise all previous year’s papers as much as you can.
Draw maps and keep techniques
Drawing mind maps or other synopsis charts to test what you can revise, and afterward, really look at them on your notes. Notice where you have left out a detail or where you forgot.
Take Regular breaks in between study schedule
Take regular breaks and don’t study continuously for hours. Basically, it is very hard to study for more than half an hour and keep concentrated.
Find those days when you can do more and utilize that day. self-preparation
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