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itssanaya · 4 years ago

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Why Linux administration course is the future Know more about Linux administration.

Why Linux administration path is the future? Identify further about it

A Linux career is always fruitful, and it is evergreen for a lot of scenarios and recession-proof. If you are looking forward to having a career in Linux you can be sure of a great future as Linux certified professionals’ requirement is always zooming up, which is good and quite consistent. A course in Linux is a great option for you and can ensure you a luxurious life. And currently, Linux is seeing an ocean of jobs, and mainly for the professionals with system administration skills. All are in the hunt for Talent in Linux. You will find recruiters caking for anyone who has Linux experience. And hence, the demand for Linux professionals is seeing major growth each day. And the development in the tech world is seeing new colors each day. That has now made Linux the best operating system to explore. And if you want to learn all this, you can contact Naresh I Technologies. We offer complete Linux training for all Linux certifications. Naresh I Technologies also is the number one computer training institute in Hyderabad. And it is among the top five computer training institutes in India.

How much is Linux used?

You will find Linux everywhere. May it be a website, a mobile application, or any device. You should know that all of them are Linux-based infrastructures if we consider the server-side. And all the top companies dealing with web-like Google, Facebook, Amazon, Netflix, and various others operate their infrastructures at scale through Linux servers. And Linux hence is seeing major growth in the corporate world. Also, quite a large part of the Linux publishing business is run on Linux, MySQL, PHP, and Apache, and a hence unlimited number of Linux professionals are in demand. You will also find that Android phones plus tablets are run using Linux. Even the iPhone on Mac and the Windows machine make use of Linux on large scale. Linux hence is rocking undoubtedly,

If you will infer the applications that we use daily like Uber, WhatsApp, Flipkart, Ola, and Zomato, then we can realize that a lot of requirements exist for tendering the Linux server. Either it is the online food ordering, the TV you see the movies on, the smartphones, to book a cab, or to record heath parameters, to a real book or you want to contact a friend, you make use of the Linux technology for all these activities, and what we know in computer terms as operations.

Did you ever think of an idea of how big a Linux market is now? And how many vacancies are there for the Linux professionals for covering the whole requirement? Have you an idea that Linux supports how many users, and where each data is stored, retrieved, and finally goes through processing? And all these require very intensive backend infrastructure that makes use of the Linux servers finally.

Linux Jobs Types

The three main use cases of Linux skills usage are technical support or a system admin or a developer.

The Linux workstations and the Desktops require technical support, the Network, system, and the Admin for webserver requires system administration. And the System and app development requires a System Administrator.

Let’s discuss this one by one.

Technical Support

This kind of job requires carrying out partitioning, services, installations, as well as user management, network troubleshooting, troubleshooting problems related to Operating systems, and basic scripting.

System Administrator

In this, you have to manage various essential services like the creation of file systems, user administration, DNS, HTTP, FTP, backup setup, Cron Jobs, and various other tasks related to administration. You need to secure the systems as well as the servers, ensure firewall management and do the management of packages. And if you acquire a good knowledge of Linux OS, networking, troubleshooting, and administration, you will find huge growth in your career as a DevOps Engineer/Linux Administrator/Site Reliability Engineer/ Operations Engineer/ and so on. The majority of Linux system administrators work on server-based distributions like Debian, CentOS, Red Hat Linux Enterprise edition, and also Ubuntu.

Application and Web-Programmer

Linux programmers have to look after the development, debugging, and documentation of the computer programs for the Linux OS and various relevant software applications. That covers plugin writing, coding in various languages such as C++, Python, or any of the programming languages, database designing, and application designing, formulating add-ons, and scripting in any language plus management of services.

Some of the other job profiles that make use of Linux are like Security Engineers, DevOps Engineers, Network Engineers, Java Engineers, C++ Developers, Python Developers, and so on.

Payscale of the Linux System Administrators

They get in hand a salary pf around INR 390000 per annum if you are in India, and this is an average salary. And if you have experience then PayScale can be highly lucrative. The Skills in Linux that can ensure high pay for you are IBM AIX, Nginx, Python, Tomcat app server, and Shell scripting. And if you look at the current scenarios, we find companies such as CISCO, Amazon, EMC Corporation, and intel offering a very huge PayScale for the employees with Linux knowledge. It’s a challenging, rewarding, and interesting career to select, the Linux administrator.

Certifications You should opt for

Below is the list of Linux certifications, which are recommended for IT professionals. And these are in huge demand in almost each job portal, and you will find numerous jobs in each of them, and hundreds are posted each day.

CompTIA Linux+

RHCSA

RHCA

RHCE

If you are planning to go for a course in Linux then you might end up getting a very good job as the requirement for Linux certified experts is huge, and increase more with time.

You can search through history, and you will find that Linux professionals have always been in great demand. It’s now becoming more and more common. It is turning now into the default OS for the cloud, mobile, and Big data, which are the trending technologies transforming all the industries.

You can contact Naresh I Technologies for your online training in various computer technologies. We provide Linux training in Hyderabad and USA, and in fact, you can contact us from any part of the world through our phone or online form on our site. Just fill it and submit it, and one of our customer care executives will be contacting you. And what else you get:

You have the freedom to choose between the best Linux training institutes and classroom training.

Chance to study from one of the best faculties and one of the best computer training institutes in India

Nominal fee affordable for all

Complete training

You get training for tackling all the nitty-gritty of Linux.

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And a lot more is waiting for you.

You can contact us anytime for your Linux training and from any part of the world. Naresh I Technologies caters to one of the best Linux training in India. Feel free to contact us anytime.

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revanthads · 5 years ago

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ecorptrainings · 6 years ago

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ratusalim · 7 years ago

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Early milestones in AI

The first AI programs

The earliest successful AI program was written in 1951 by Christopher Strachey, later director of the Programming Research Group at the University of Oxford. Strachey’s checkers (draughts) program ran on the Ferranti Mark I computer at the University of Manchester, England. By the summer of 1952 this program could play a complete game of checkers at a reasonable speed.

Information about the earliest successful demonstration of machine learning was published in 1952. Shopper, written by Anthony Oettinger at the University of Cambridge, ran on the EDSAC computer. Shopper’s simulated world was a mall of eight shops. When instructed to purchase an item, Shopper would search for it, visiting shops at random until the item was found. While searching, Shopper would memorize a few of the items stocked in each shop visited (just as a human shopper might). The next time Shopper was sent out for the same item, or for some other item that it had already located, it would go to the right shop straight away. This simple form of learning, as is pointed out in the introductory section What is intelligence?, is called rote learning.

The first AI program to run in the United States also was a checkers program, written in 1952 by Arthur Samuel for the prototype of the IBM 701. Samuel took over the essentials of Strachey’s checkers program and over a period of years considerably extended it. In 1955 he added features that enabled the program to learn from experience. Samuel included mechanisms for both rote learning and generalization, enhancements that eventually led to his program’s winning one game against a former Connecticut checkers champion in 1962.

Evolutionary computing

Samuel’s checkers program was also notable for being one of the first efforts at evolutionary computing. (His program “evolved” by pitting a modified copy against the current best version of his program, with the winner becoming the new standard.) Evolutionary computing typically involves the use of some automatic method of generating and evaluating successive “generations” of a program, until a highly proficient solution evolves.

A leading proponent of evolutionary computing, John Holland, also wrote test software for the prototype of the IBM 701 computer. In particular, he helped design a neural-network “virtual” rat that could be trained to navigate through a maze. This work convinced Holland of the efficacy of the bottom-up approach. While continuing to consult for IBM, Holland moved to the University of Michigan in 1952 to pursue a doctorate in mathematics. He soon switched, however, to a new interdisciplinary program in computers and information processing (later known as communications science) created by Arthur Burks, one of the builders of ENIAC and its successor EDVAC. In his 1959 dissertation, for most likely the world’s first computer science Ph.D., Holland proposed a new type of computer—a multiprocessor computer—that would assign each artificial neuron in a network to a separate processor. (In 1985 Daniel Hillis solved the engineering difficulties to build the first such computer, the 65,536-processor Thinking Machines Corporation supercomputer.)

Holland joined the faculty at Michigan after graduation and over the next four decades directed much of the research into methods of automating evolutionary computing, a process now known by the term genetic algorithms. Systems implemented in Holland’s laboratory included a chess program, models of single-cell biological organisms, and a classifier system for controlling a simulated gas-pipeline network. Genetic algorithms are no longer restricted to “academic” demonstrations, however; in one important practical application, a genetic algorithm cooperates with a witness to a crime in order to generate a portrait of the criminal.

Logical reasoning and problem solving

The ability to reason logically is an important aspect of intelligence and has always been a major focus of AI research. An important landmark in this area was a theorem-proving program written in 1955–56 by Allen Newell and J. Clifford Shaw of the RAND Corporation and Herbert Simon of the Carnegie Mellon University. The Logic Theorist, as the program became known, was designed to prove theorems from Principia Mathematica (1910–13), a three-volume work by the British philosopher-mathematicians Alfred North Whitehead and Bertrand Russell. In one instance, a proof devised by the program was more elegant than the proof given in the books.

Newell, Simon, and Shaw went on to write a more powerful program, the General Problem Solver, or GPS. The first version of GPS ran in 1957, and work continued on the project for about a decade. GPS could solve an impressive variety of puzzles using a trial and error approach. However, one criticism of GPS, and similar programs that lack any learning capability, is that the program’s intelligence is entirely secondhand, coming from whatever information the programmer explicitly includes.

English dialogue

Two of the best-known early AI programs, Eliza and Parry, gave an eerie semblance of intelligent conversation. (Details of both were first published in 1966.) Eliza, written by Joseph Weizenbaum of MIT’s AI Laboratory, simulated a human therapist. Parry, written by Stanford University psychiatrist Kenneth Colby, simulated a human paranoiac. Psychiatrists who were asked to decide whether they were communicating with Parry or a human paranoiac were often unable to tell. Nevertheless, neither Parry nor Eliza could reasonably be described as intelligent. Parry’s contributions to the conversation were canned—constructed in advance by the programmer and stored away in the computer’s memory. Eliza, too, relied on canned sentences and simple programming tricks.

AI programming languages

In the course of their work on the Logic Theorist and GPS, Newell, Simon, and Shaw developed their Information Processing Language (IPL), a computer language tailored for AI programming. At the heart of IPL was a highly flexible data structure that they called a list. A list is simply an ordered sequence of items of data. Some or all of the items in a list may themselves be lists. This scheme leads to richly branching structures.

In 1960 John McCarthy combined elements of IPL with the lambda calculus (a formal mathematical-logical system) to produce the programming language LISP (List Processor), which remains the principal language for AI work in the United States. (The lambda calculus itself was invented in 1936 by the Princeton logician Alonzo Church while he was investigating the abstract Entscheidungsproblem, or “decision problem,” for predicate logic—the same problem that Turing had been attacking when he invented the universal Turing machine.)

The logic programming language PROLOG (Programmation en Logique) was conceived by Alain Colmerauer at the University of Aix-Marseille, France, where the language was first implemented in 1973. PROLOG was further developed by the logician Robert Kowalski, a member of the AI group at the University of Edinburgh. This language makes use of a powerful theorem-proving technique known as resolution, invented in 1963 at the U.S. Atomic Energy Commission’s Argonne National Laboratory in Illinois by the British logician Alan Robinson. PROLOG can determine whether or not a given statement follows logically from other given statements. For example, given the statements “All logicians are rational” and “Robinson is a logician,” a PROLOG program responds in the affirmative to the query “Robinson is rational?” PROLOG is widely used for AI work, especially in Europe and Japan.

Researchers at the Institute for New Generation Computer Technology in Tokyo have used PROLOG as the basis for sophisticated logic programming languages. Known as fifth-generation languages, these are in use on nonnumerical parallel computers developed at the Institute.

Other recent work includes the development of languages for reasoning about time-dependent data such as “the account was paid yesterday.” These languages are based on tense logic, which permits statements to be located in the flow of time. (Tense logic was invented in 1953 by the philosopher Arthur Prior at the University of Canterbury, Christchurch, New Zealand.)

Microworld programs

To cope with the bewildering complexity of the real world, scientists often ignore less relevant details; for instance, physicists often ignore friction and elasticity in their models. In 1970 Marvin Minsky and Seymour Papert of the MIT AI Laboratory proposed that likewise AI research should focus on developing programs capable of intelligent behaviour in simpler artificial environments known as microworlds. Much research has focused on the so-called blocks world, which consists of coloured blocks of various shapes and sizes arrayed on a flat surface.

An early success of the microworld approach was SHRDLU, written by Terry Winograd of MIT. (Details of the program were published in 1972.) SHRDLU controlled a robot arm that operated above a flat surface strewn with play blocks. Both the arm and the blocks were virtual. SHRDLU would respond to commands typed in natural English, such as “Will you please stack up both of the red blocks and either a green cube or a pyramid.” The program could also answer questions about its own actions.Although SHRDLU was initially hailed as a major breakthrough, Winograd soon announced that the program was, in fact, a dead end. The techniques pioneered in the program proved unsuitable for application in wider, more interesting worlds. Moreover, the appearance that SHRDLU gave of understanding the blocks microworld, and English statements concerning it, was in fact an illusion. SHRDLU had no idea what a green block was.

Another product of the microworld approach was Shakey, a mobile robot developed at the Stanford Research Institute by Bertram Raphael, Nils Nilsson, and others during the period 1968–72. The robot occupied a specially built microworld consisting of walls, doorways, and a few simply shaped wooden blocks. Each wall had a carefully painted baseboard to enable the robot to “see” where the wall met the floor (a simplification of reality that is typical of the microworld approach). Shakey had about a dozen basic abilities, such as TURN, PUSH, and CLIMB-RAMP.

Critics pointed out the highly simplified nature of Shakey’s environment and emphasized that, despite these simplifications, Shakey operated excruciatingly slowly; a series of actions that a human could plan out and execute in minutes took Shakey days.

The greatest success of the microworld approach is a type of program known as an expert system, described in the next section.

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smashgaps-blog · 7 years ago

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arittechnologies · 4 years ago

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ecorptrainings · 7 years ago

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IBM POWER8 and AIX Enhancements Online Training at Ecorptrainings Hyderabad

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ecorptrainings · 7 years ago

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smashgaps-blog · 8 years ago

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smashgaps-blog · 8 years ago

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smashgaps-blog · 8 years ago

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smashgaps-blog · 8 years ago

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