HSC Exam Routine HD PDF QUality Download Free

HSC Exam Routine HD PDF QUality Download Free

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Dollar Rate Today Live

Today Dollar rate is given below :

1 USD  = 83.89  Bangladeshi Taka

1 USD = 7.24  Indian Rupee

23 January 2019

BRAC university tuition fees

BRAC University Credit Fee - Per Credit  BDT 6000 For All Program (EMBA/BMB- 6500)


BRAC University -  136 Credits, 4 Year, Admission Fee 17500
                                             Per Credit 5000, Total Fee 757500 BDT

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Education Board Result 2018 JSC PSC

Education Board Result 2018 JSC PSC

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Aiub tuition fee

American International University of Bangladesh (AIUB) CSE Tuition Fees and Credit :

Aiub tuition fees cse (Americal International University cse tuition fees) : AIUB is one of the good university in Bangladesh. After North South University AIUB is the top lebel university in Dhaka. AIUB has 148 credit of Computer Science and Engineering (CSE) departments.

Admission fees of CSE is 20000 BDT. Per credit price is BDT 5000 and Total cost if CSE course is 851000 BDT  If someone choose Computer Information System (CIS) then the amount of course fee may increase or decrease. 

American International University of Bangladesh (AIUB) CSE Tuition Fees and Credit 

At a Glance :

University Name : American International University of Bangladesh (AIUB) 

Department : Computer Science and Engineering

Total Credit : 148 Credits

Duration :  4 Year 

Admission Fees : 20000 BDT 

Per Credit : 5000 BDT 

Total Fees :  851000 BDT

The Science Wars: a way out

When the May 1996 issue of the journal Social Text appeared, an issue devoted to the understanding of ‘‘Science Wars,’’ the editors became targets in these ‘‘wars’’ in ways they had not imagined. The issue included a bogus article by New York University mathematical physicist Alan Skoal, who feigned an earnest resection on the political and philosophical implications of recent physics research for cultural studies. Asoka re-leaved the hoax himself, and it immediately became a hotly debated issue in academic and popular media around the world. The appearance of the article was not only taken as a sign of shoddy scholarship by the Social Text editors but as an expose´ of cultural studies and social science in general. For instance, Nobel prize-winning physicist Steven Weinberg used the hoax to identify what he calls a fundamental ‘‘opposition’’ between natural and social scientists, especially regarding what Weinberg sees as dangerous anti-rationalism and relativism in social science and cultural studies. 

Those on the other side of the ‘‘wars’’ countered by criticizing Skoal and calling Weinberg and like-minded natural scientists ‘‘per-Kantian shaman[s]’’ repeating the ‘‘mantras of particle physicists,’’with their ‘‘reductionist view of science’’ .The year before Skoal's hoax, the ‘‘wars’’ had raged over the scientist status of a high-prole US National Opinion Research Center study,

which had been launched as a ‘‘deWnitive survey’’ of sexual practices in the United States

.Here, too, doubts were raised not only about the status of scholarship of the study in question, but of sociology and social science as such. The study had received the doubtful honor of becoming

the topic of an editorial in The Economist under the heading ‘‘74.6% of Sociology is Bunk.’’6 In The New York Review of Books, Harvard biologist and statistician R. C. Continent criticized the researchers behind the

What is Computer Science

The study of information, protocols and algorithms for idealized and real automate. I automaton: “self moving” – in our context, self “deciding” or autonomous mechanism with bounded resources (time and space) I information: knowledge represented in a form suitable for transmission, manipulation, etc. I protocol: rules for exchanging information without problems I algorithm: an unambiguous, finite description in simple steps or actions Computer Science is not the study of computers, nor is it the practice of their use. The study of information, protocols and algorithms for idealized and real automate. 

I automaton: “self moving” – in our context, self “deciding” or autonomous mechanism with bounded resources (time and space) I information: knowledge represented in a form suitable for transmission, manipulation, etc. I protocol: rules for exchanging information without problems I algorithm: an unambiguous, finite description in simple steps or actions Computer Science is not the study of computers, nor is it the practice of their use. The study of information, protocols and algorithms for idealized and real automate. I automaton: “self moving” – in our context, self “deciding” or autonomous mechanism with bounded resources (time and space) I information: knowledge represented in a form suitable for transmission, manipulation, etc. I protocol: rules for exchanging information without problems I algorithm: an unambiguous, finite description in simple steps or actions Computer Science is not the study of computers, nor is it the practice of their use. The study of information, protocols and algorithms for idealized and real automate. I automaton: “self moving” – in our context, self “deciding” or autonomous mechanism with bounded resources (time and space) 

Information: knowledge represented in a form suitable for transmission, manipulation, etc. I protocol: rules for exchanging information without problems I algorithm: an unambiguous, finite description in simple steps or actions Computer Science is not the study of computers, nor is it the practice of their use. The study of information, protocols and algorithms for idealized and real automate. I automaton: “self moving” – in our context, self “deciding” or autonomous mechanism with bounded resources (time and space) I information: knowledge represented in a form suitable for transmission, manipulation, etc. I protocol: rules for exchanging information without problems I algorithm: an unambiguous, finite description in simple steps or actions Computer Science is not the study of computers, nor is it the practice of their use. The study of information, protocols and algorithms for idealized and real automate. I automaton: “self moving” – in our context, self “deciding” or autonomous mechanism with bounded resources (time and space) I information: knowledge represented in a form suitable for transmission, manipulation, etc.

Algorithms and Data Structures

We agree with decades of common wisdom that familiarity with common algorithms and data structures is one of the most empowering aspects of a computer science education

. This is also a great place to train one’s general problem-solving abilities, which will pay off in every other area of study

.There are hundreds of books available, but our favorite is The Algorithm Design Manual by Steven Skiena

. He clearly loves this stuff and can’t wait to help you understand it

. This is a refreshing change, in our opinion, from the more commonly recommended Cormen, Leiserson, Rivest & Stein, or Sedgewick books

. These last two texts tend to be too proof-heavy for those learning the material primarily to help them solve problems

.For those who prefer video lectures, Skiena generously provides his online

. We also really like Tim Roughgarden’s course, available from Stanford’s MOOC platform Lagunita, or on Coursera

. Whether you prefer Skiena’s or Roughgarden’s lecture style will be a matter of personal preference

.For practice, our preferred approach is for students to solve problems on Leetcode

. These tend to be interesting problems with decent accompanying solutions and discussions

. They also help you test progress against questions that are commonly used in technical interviews at the more competitive software companies

. We suggest solving around 100 random leetcode problems as part of your studies.

Finally, we strongly recommend How to Solve It as an excellent and unique guide to general problem solving; it’s as applicable to computer science as it is to mathematics.

Computer Architecture

Computer Architecture—sometimes called “computer systems” or “computer organization”—is an important first look at computing below the surface of software. In our experience, it’s the most neglected area among self-taught software engineers. The Elements of Computing Systems, also known as “Nand2Tetris” is an ambitious book attempting to give you a cohesive understanding of how everything in a computer works. Each chapter involves building a small piece of the overall system, from writing elementary logic gates in HDL, through a CPU and assembler, all the way to an application the size of a Tetris game. We recommend reading through the first six chapters of the book and completing the associated projects. 

This will develop your understanding of the relationship between the architecture of the machine and the software that runs on it. The first half of the book (and all of its projects), are available for free from the Nand2Tetris website. It’s also available as a Coursera course with accompanying videos.In seeking simplicity and cohesiveness, Nand2Tetris trades off depth. In particular, two very important concepts in modern computer architectures are pipelining and memory hierarchy, but both are mostly absent from the text. Once you feel comfortable with the content of Nand2Tetris, our next suggestion is Patterson and Hennessy’s Computer Organization and Design, an excellent and now classic text. Not every section in the book is essential; we suggest following Berkeley’s CS61C course “Great Ideas in Computer Architecture” for specific readings. The lecture notes and labs are available online, and past lectures are on the Internet Archive.

Subject guides Programming

Most undergraduate CS programs start with an “introduction” to computer programming. The best versions of these courses cater not just to novices, but also to those who missed beneficial concepts and programming models while first learning to code.

Our standard recommendation for this content is the classic Structure and Interpretation of Computer Programs, which is available online for free both as a book, and as a set of MIT video lectures. While those lectures are great, our video suggestion is actually Brian Harvey’s SICP lectures (for the 61A course at Berkeley) instead. These are more refined and better targeted at new students than are the MIT lectures

We recommend working through at least the first three chapters of SICP and doing the exercises

For additional practice, work through a set of small programming problems like those on exercise.

For those who find SICP too challenging, we recommend How to Design Programs

For those who find it too easy, we recommend Concepts, Techniques, and Models of Computer Programming.

Why learn computer science

Type 1 engineers find ways to learn computer science in depth, whether through conventional means or by relentlessly learning throughout their careers.  Type 2 engineers typically stay at the surface, learning specific tools and technologies rather than their underlying foundations, only picking up new skills when the winds of technical fashion change. Currently, the number of people entering the industry is rapidly increasing, while the number of CS grads is essentially static. 

This oversupply of Type 2 engineers is starting to reduce their employment opportunities and keep them out of the industry’s more fulfilling work. Whether you’re striving to become a Type 1 engineer or simply looking for more job security, learning computer science is the only reliable path.

Why learn computer science.

There are 2 types of software engineer: those who understand computer science well enough to do challenging, innovative work, and those who just get by because they’re familiar with a few high level tools

.

Both call themselves software engineers, and both tend to earn similar salaries in their early careers

. But Type 1 engineers grow in to more fulfilling and well-remunerated work over time, whether that’s valuable commercial work or breakthrough open-source projects, technical leadership or high-quality individual contributions

.

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Type 1 engineers find ways to learn computer science in depth, whether through conventional means or by relentlessly learning throughout their careers

. Type 2 engineers typically stay at the surface, learning specific tools and technologies rather than their underlying foundations, only picking up new skills when the winds of technical fashion change

.

Currently, the number of people entering the industry is rapidly increasing, while the number of CS grads is essentially static

. This oversupply of Type 2 engineers is starting to reduce their employment opportunities and keep them out of the industry’s more fulfilling work

. Whether you’re striving to become a Type 1 engineer or simply looking for more job security, learning computer science is the only reliable path.

Data Communication Fundamentals

In this module we shall discuss various aspects of data link control has been considered
. Lesson  deals with framing and synchronization along with how one can interface the machine to the media
. Error detection and error correction techniques are presented in Lesson 
. Lesson  introduces various protocols used for flow control and error control
. Finally, lesson  provides an overview of HDD, the most popular data link control protocol
. Module Switched Communication Networks In this module switched communication networks has been considered
. First, various switching techniques have been presented in Lesson . In this lesson various aspects of circuit switching and the operation of Public Switched Telephone Network (PST), which is based on circuit switching, have been discussed
. Various aspects of message switching, packet switching and virtual circuit switching have been addressed in Lesson Lesson  presents the Synchronous Optical Network (TONES) that defines a technology for carrying many signals of different capacities through a synchronous, flexible, optical hierarchy
. It utilizes the enormous bandwidth of optical fiber to achieve date transfer at a very high rate
. X.25 is a packet-switched network developed by ITS-T in 1976
. It defines how a packet-mode terminal can be interfaced to a packet network for data communication
. However, X.25 does not satisfy the present day requirements of higher data rate
. To overcome these limitations, a new standard, known as frame relay was introduced
. Lesson introduces these two packet switching networks
. In the last section of this module, ATM (Asynchronous transfer mode), which can be used both as a LAN or WAN standard has been introduced
. Various network devices used in ATM, concept of cell transfer and cell format have been discussed. 

Data Communication Fundamentals

Lesson  deals with various multiplexing techniques such as Frequency division multiplexing (FEM), time division multiplexing (TAM), Statistical TAM, Wave Division multiplexing (WPM) and Orthogonal Frequency Division Multiplexing (OFFEND)
. So, this module provides necessary background to the students for understanding the topics to be covered in the subsequent lessons dealing with different aspects of computer networks.

Data Communication Fundamentals

Module  Data Communication Fundamentals This module is concerned with some of the important issues of the physical layer, which provides services to the layer above it, namely the data link layer
. In the data link layer, the data consists of es and 1st, which are organized into frames to be sent through some transmission media
. It is necessary to convert this data into another entity called signal
. After introducing the fundamental model of communication, Lesson introduces the basic elements of communication such as data, signal and channel characteristics
. Different data types, concept of time domain and frequency domain representation of signal, various channel characteristics such as bandwidth, bit interval and bit rate of a digital signal are considered in this section
. Lesson  introduces different transmission media, which are broadly divided into two categories, namely guided and unguided media
. Typical characteristics and uses of each type of media starting from twisted-pair cables, coaxial cable, and optical fiber to line-of-sight and satellite communication have been covered in this lesson
. Lesson  will introduce various sources of impairments, such as attenuation, distortion and noise, that a signal suffers as it passes through a communication media
. This lesson also will introduce the concept of channel capacity, which specifies the amount of information that can be sent through a medium
. Lesson deals with the transmission of digital signals, which involves encoding of data
. Encoding of digital data involves two types of coding namely line coding and block coding
. Various line coding techniques such as uni polar, polar, and bipolar and block coding techniques are presented in this lesson
. Encoding of analog data involves conversion to digital form by using techniques like pulse code modulation and delta modulation, which are also discussed in this lesson
. Transmission of analog signals is discussed in Lesson 
. It is necessary to perform modulation to convert analog data to analog signal
. Various aspects of the three possible modulation techniques, namely amplitude, phase and frequency have been discussed in this lesson
. Similarly, to convert digital data to analog signal, possible approaches such as amplitude, phase and frequency shift keying have been covered in lesson