IT vs Computer science

1. Computer science deals with creating computer programs while IT deals with the usage of those programs in business.

2. Computer science is at the ‘lower level’ while Information technology is at high level, in computing terms.

3. Information technology integrates computer science into the business world for automated solutions.

4. Computer scientists should have low level workings of computers whereas in IT that’s not necessary.

IT vs Computer science

In almost all schools, computer science courses involve learning about computer programming which involves learning the basics of programming methodology, data structures, algorithms, complexity theory all the way down to learning what makes an operating system work, although at computer science level, low level programming is not usually looked at in detail as it is dealt with in computer engineering courses

.Looking at computing in general we can best organize these terms in a hierarchical manner

. At a lower level we have computer engineering which is at the ‘chip’ level dealing with the internal circuitry, power and the electronics of a computer

. Next level is the computer science level which tends to be quite wide because a computer scientist will actually be acquainted with low level stuff in computer engineering as well as high level programming that integrates with the chips and circuitry to make the machines work

. Then at the high level is Information technology which concentrates with studying the impact of applications or solutions developed at the preceding level to business

. IT finds ways of integrating these solutions into the business framework.

IT vs Computer science

IT vs Computer science

In their most basic terms, Computer Science and Information Technology may not have any difference when being referred to in general and for a good reason, a lot of people do take them to mean more or less the same thing

. However, speaking in strict computing terms, there is indeed a difference between the two terms

.Computer science refers to the processes used to create usable computer programs and applications together with all theory behind those processes

. Information technology on the other hand refers to the application of computer programs to solve business processes

. It is the application of technology in business. Information technology is very vast in terms of scale because it is applied virtually to any type of process that may require automation, from business, scientific research to the music industry, telecoms and banking

.The two terms may also differ depending on school or college, where in some schools they may use one term to refer to a course that combines IT and Computer science modules

. In schools that are more engineering based, they use the computer science term as an umbrella term for all theory relating to information technology

. In such cases they normally use the term ‘computer engineering’ to refer to the process of creating computer programs, both at system level and application level.

Computer Science and Information Technology

 10: Computer Networks Concept of layering
. LAN technologies (Ethernet)
. Flow and error control techniques, switching
. IPv4/IPv6, routers and routing algorithms (distance vector, link state)
. TCP/UDP and sockets, congestion control
. Application layer protocols (DNS, SMTP, POP, FTP, HTTP)
. Basics of Wi-Fi. Network security: authentication, basics of public key and private key cryptography, digital signatures and certificates, firewalls.

Computer Science and Information Technology

 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.

Computer Science and Information Technology

 8: Operating System Processes, threads, inter‐process communication, concurrency and synchronization
. Deadlock. CPU scheduling
. Memory management and virtual memory. File systems.

Computer Science and Information Technology

 7: Compiler Design Lexical analysis, parsing, syntax-directed translation
. Runtime environments. Intermediate code generation.

Computer Science and Information Technology

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

Computer Science and Information Technology

 5: Algorithms Searching, sorting, hashing
. Asymptotic worst case time and space complexity
. Algorithm design techniques: greedy, dynamic programming and divide‐and‐conquer
. Graph search, minimum spanning trees, shortest paths.

Computer Science and Information Technology

 4: Programming and Data Structures Programming in C
. Recursion. Arrays, stacks, queues, linked lists, trees, binary search trees, binary heaps, graphs.

Computer Science and Information Technology

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

CS Computer Science and Information Technology

CS Computer Science and Information Technology Section1: Engineering Mathematics Discrete Mathematics: Propositional and first order logic

. Sets, relations, functions, partial orders and lattices

. Groups. Graphs: connectivity, matching, coloring

. 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: Random variables

. Uniform, normal, exponential, poisson and binomial distributions

. Mean, median, mode and standard deviation. Conditional probability and Bayes theorem. 

Digital Logic Boolean algebra

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

CS Computer Science and Information Technology Section1

CS Computer Science and Information Technology Section1: Engineering Mathematics Discrete Mathematics: Propositional and first order logic

. Sets, relations, functions, partial orders and lattices

. Groups. Graphs: connectivity, matching, coloring

. 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: Random variables

. Uniform, normal, exponential, poisson and binomial distributions

. Mean, median, mode and standard deviation. Conditional probability and Bayes theorem. 

etin meaning

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