Computer Science is the study of computers and computational systems.
Unlike electrical and computer engineers, computer scientists deal
mostly with software and software systems; this includes their theory,
design, development, and application.
Principal areas of study within Computer Science include artificial
intelligence, computer systems and networks, security, database
systems, human computer interaction, vision and graphics, numerical
analysis, programming languages, software engineering, bioinformatics
and theory of computing. Although knowing how to program is essential
to the study of computer science, it is only one element of the field.
Computer scientists design and analyze algorithms to solve programs
and study the performance of computer hardware and software. The
problems that computer scientists encounter range from the abstract--
determining what problems can be solved with computers and the
complexity of the algorithms that solve them – to the tangible –
designing applications that perform well on handheld devices, that are
easy to use, and that uphold security measures.
Computer science emerged as an independent discipline in the early 1960s, although the electronic digital computer that is the object of its study was invented some two decades earlier. The roots of computer science lie primarily in the related fields of mathematics, electrical engineering, physics, and management information systems. Computer science is a diverse field; the required skills are both applicable and in-demand across practically every industry in today's technology-dependent world. As such, the field of computer science is divided amongst a range of sub-disciplines, most of which are full-fledged specialized disciplines in and of themselves. The field of computer science spans several core areas: computer theory, hardware systems, software systems, and scientific computing.
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Web development is the work involved in developing a Web site for the
Internet (World Wide Web) or an intranet (a private network). Web
development can range from developing a simple single static page of
plain text to complex web applications, electronic businesses, and
social network services. A more comprehensive list of tasks to which
Web development commonly refers, may include Web engineering, Web
design, Web content development, client liaison,
client-side/server-side scripting, Web server and network security
configuration, and e-commerce development.
Web developers, or ‘devs’, do this by using a variety of coding
languages. The languages they use depends on the types of tasks they
are preforming and the platforms on which they are working. Web
development skills are in high demand worldwide and well paid too –
making development a great career option. It is one of the easiest
accessible higher paid fields as you do not need a traditional
university degree to become qualified. The field of web development is
generally broken down into front-end (the user-facing side) and
back-end (the server side).
All this may sound daunting at first, but you don’t need to know
everything at once. You will grow your knowledge progressively. And
things will begin to click. For example, if you are interested in
front end you can start by learning some HTML and CSS, then start
working on projects as soon as you are comfortable with the basics.
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Mobile app development is a process for building mobile applications
that run on mobile devices. These applications can either be
pre-installed or downloaded and installed by the user later. They use
the network capabilities of the device to work computing resources
remotely. Hence, the mobile app development process requires creating
software that can be installed on the device, and enabling backend
services for data access through APIs, and testing the application on
target devices. To develop scalable mobile apps, you also need to
consider screen sizes, hardware requirements, and many other aspects
of the app development process. With an increasing number of jobs in
the mobile app development industry, it is essential that the process
is well defined and understood by entrepreneurs, startups, and
especially developers.
The two most important mobile app platforms are iOS from Apple Inc.
and Android from Google. iOS is Apple’s proprietary mobile operating
system built specifically for iPhones. Android, however, runs on
mobile devices manufactured by various OEMs, including Google. While
there are many similarities between the two, however different
software development kits (SDKs) are used for different platforms.
Apple uses iOS exclusively for their own devices, while Google has
made Android available for other companies that meet specific
requirements. Developers have built over 1.5 million applications for
both platforms to date.
Mobile app development industry is going through a transformative
phase. With the advancement in micro-processing technologies, you will
be able to run mobile applications on multiple platforms. For example,
apps built for mobiles will run seamlessly on desktops in the coming
years. Moreover, mobile apps built with Flutter or React Native will
work on Android Phones, iPhones, Macs, as well as PCs.
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Competitive programming is a mind sport usually held over the Internet
or a local network, involving participants trying to program according
to provided specifications. Contestants are referred to as sport
programmers. Competitive programming is recognized and supported by
several multinational software and Internet companies, such as Google
and Facebook. There are several organizations who host programming
competitions on a regular basis.
It teaches you how to think?. If you are a programmer you might
have understood the deep meaning of these lines quoted by Steve Jobs
and you might have also experienced that even after shutting your
computer you keep on thinking about programming stuff or code you have
written in your project. Once you enter in programming you just don’t
learn how to code but you also learn the “art of thinking”, by
breaking your code into smaller chunks and then using your logic-based
creativity to solve a problem from different angles. Programming is
fun, programming is an exercise for your brain, programming is a
mental sport and when this sport is held over the internet involving
sport programmer as a contestant then it is called Competitive
Programming.
A programming competition generally involves the host presenting a set
of logical or mathematical problems, also known as puzzles, to the
contestants (who can vary in number from tens to several thousands),
and contestants are required to write computer programs capable of
solving each problem. Judging is based mostly upon number of problems
solved and time spent for writing successful solutions, but may also
include other factors (quality of output produced, execution time,
program size, etc.)
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In computer science, a data structure is a data organization,
management, and storage format that enables efficient access and
modification. More precisely, a data structure is a collection of data
values, the relationships among them, and the functions or operations
that can be applied to the data.
Data structures serve as the basis for abstract data types (ADT). The
ADT defines the logical form of the data type. The data structure
implements the physical form of the data type. Different types of data
structures are suited to different kinds of applications, and some are
highly specialized to specific tasks. Data structures provide a means to manage large amounts
of data efficiently for uses such as large databases and internet
indexing services. Usually, efficient data structures are key to
designing efficient algorithms. Some formal design methods and
programming languages emphasize data structures, rather than
algorithms, as the key organizing factor in software design. Data
structures can be used to organize the storage and retrieval of
information stored in both main memory and secondary memory.
Data structures are generally based on the ability of a computer to
fetch and store data at any place in its memory, specified by a
pointer—a bit string, representing a memory address, that can be
itself stored in memory and manipulated by the program. Thus, the
array and record data structures are based on computing the addresses
of data items with arithmetic operations, while the linked data
structures are based on storing addresses of data items within the
structure itself. The implementation of a data structure usually
requires writing a set of procedures that create and manipulate
instances of that structure. The efficiency of a data structure cannot
be analyzed separately from those operations.
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Game Development is the art of creating games and describes the
design, development and release of a game. It may involve concept
generation, design, build, test and release. While you create a game,
it is important to think about the game mechanics, rewards, player
engagement and level design. This process of Game Development for
commercial games is funded by a publisher (a rich company!) but
independent video games are comparatively cheaper and smaller so they
can be funded by individuals also (That can be you!).
There are many people who assume that if they are good Game Players
then they will definitely be good in Game Development. Well, don’t
make that mistake!!! If you are a good Game Player then you have some
advantage because you already know something about game stories,
players, levels etc. But that’s it! Actually Game Playing and Game
Development are very different fields and the skills you acquire in
the former will not necessarily help you in the latter. For example:
If you love movies, that doesn’t necessarily mean you will be a good
movie director!!! So get into Game Development only if you are
passionate about game programming and really want to develop a game
for fun(Loving game playing is just a bonus!).
There are many different components in Game Development that can
either be handled by a single developer who is individually creating a
game or normally by a team of multiple people. So if you want to get
started with Game Development, it’s best to first understand the
various components in this field so that you can identify the ones
that most interest you. As technology has evolved, so has programming. Early on in video game history, programmers were often responsible for most aspects of development, including design. But as hardware and software improved, and games became increasingly more complex, dev teams grew dramatically.
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Front-end web development, also known as client-side development is
the practice of producing HTML, CSS and JavaScript for a website or
Web Application so that a user can see and interact with them
directly. The challenge associated with front end development is that
the tools and techniques used to create the front end of a website
change constantly and so the developer needs to constantly be aware of
how the field is developing.
The objective of designing a site is to ensure that when the users
open up the site they see the information in a format that is easy to
read and relevant. This is further complicated by the fact that users
now use a large variety of devices with varying screen sizes and
resolutions thus forcing the designer to take into consideration these
aspects when designing the site. They need to ensure that their site
comes up correctly in different browsers (cross-browser), different
operating systems (cross-platform) and different devices
(cross-device), which requires careful planning on the side of the
developer.
A front-end developer architects and develops websites and
applications using web technologies (i.e., HTML, CSS, DOM, and
JavaScript), which run on the Open Web Platform or act as compilation
input for non-web platform environments (i.e., React Native).There are
several tools and platforms, such as WordPress, Joomla, and Drupal,
available that can be used to develop the front end of a website, and
understanding which tools are best fit for specific tasks marks the
difference between developing a hacked site and a well designed,
scalable site.
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Cyber security is the practice of defending computers, servers, mobile
devices, electronic systems, networks, and data from malicious
attacks. It's also known as information technology security or
electronic information security. The term applies in a variety of
contexts, from business to mobile computing, and can be divided into a
few common categories. Maintaining cybersecurity in a constantly evolving threat landscape is a challenge for all organizations. Traditional reactive approaches, in which resources were put toward protecting systems against the biggest known threats, while lesser known threats were undefended, is no longer a sufficient tactic. To keep up with changing security risks, a more proactive and adaptive approach is necessary.
Cyber security is important because government, military, corporate,
financial, and medical organizations collect, process, and store
unprecedented amounts of data on computers and other devices. A
significant portion of that data can be sensitive information, whether
that be intellectual property, financial data, personal information,
or other types of data for which unauthorized access or exposure could
have negative consequences. Organizations transmit sensitive data
across networks and to other devices in the course of doing
businesses, and cyber security describes the discipline dedicated to
protecting that information and the systems used to process or store
it.
The most difficult challenge in cyber security is the ever-evolving
nature of security risks themselves. Traditionally, organizations and
the government have focused most of their cyber security resources on
perimeter security to protect only their most crucial system
components and defend against known treats. Today, this approach is
insufficient, as the threats advance and change more quickly than
organizations can keep up with. As a result, advisory organizations
promote more proactive and adaptive approaches to cyber security.
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Database is a collection of inter-related data which helps in
efficient retrieval, insertion and deletion of data from database and
organizes the data in the form of tables, views, schemas, reports etc.
For Example, university database organizes the data about students,
faculty, and admin staff etc. which helps in efficient retrieval,
insertion and deletion of data from it.
DML is short name of Data Manipulation Language which deals with data
manipulation and includes most common SQL statements such SELECT,
INSERT, UPDATE, DELETE, etc., and it is used to store, modify,
retrieve, delete and update data in a database.
Database Management System (DBMS) is a software for storing and
retrieving users' data while considering appropriate security
measures. It consists of a group of programs which manipulate the
database. The DBMS accepts the request for data from an application
and instructs the operating system to provide the specific data. In
large systems, a DBMS helps users and other third-party software to
store and retrieve data. DBMS allows users to create their own
databases as per their requirement. The term “DBMS” includes the user
of the database and other application programs. It provides an
interface between the data and the software application. Users can construct their own databases using a DBMS to satisfy their business requirements. For example, dBase was one of the first DBMS for micro-computers. Database design also supports the creation, design, implementation, and maintenance of an organization-wide data management system. To interact with a database, a DBMS package generally uses SQL queries. It receives a command from a database administrator (DBA) and prompts the system to perform the necessary action. These instructions can be about loading, retrieving, or modifying existing data in the system. Over the years, new DBMS software has been introduced with different architecture and application focus.
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Data science is an essential part of any industry today, given the
massive amounts of data that are produced. Data science is one of the
most debated topics in the industries these days. Its popularity has
grown over the years, and companies have started implementing data
science techniques to grow their business and increase customer
satisfaction.
Data science is the domain of study that deals with vast volumes of
data using modern tools and techniques to find unseen patterns, derive
meaningful information, and make business decisions. Data science uses
complex machine learning algorithms to build predictive models. The
data used for analysis can be from multiple sources and present in
various formats.
It uses scientific methods, processes, algorithms and systems to
extract knowledge and insights from structured and unstructured data,
and apply knowledge and actionable insights from data across a broad
range of application domains. Data science is related to data mining,
machine learning and big data. Data science is the study that deals
with large volumes of data using modern tools and techniques. Data
science is a "concept to unify statistics, data analysis, informatics,
and their related methods" in order to "understand and analyze actual
phenomena" with data. It uses techniques and theories drawn from many
fields within the context of mathematics, statistics, computer
science, information science, and domain knowledge. Python is the most widely used programming language today when it comes to solving data science tasks and challenges, Python never ceases to surprise its users. Most data scientists are already leveraging the power of Python programming every day. Python is an easy-to-learn, easy-to-debug, widely used, object-oriented, open-source, high-performance language, and there are many more benefits to Python programming. Python has been built with extraordinary Python libraries for data science that are used by programmers every day in solving problems.
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Machine learning is a method of data analysis that automates
analytical model building. It is a branch of artificial intelligence
based on the idea that systems can learn from data, identify patterns
and make decisions with minimal human intervention.
Because of new computing technologies, machine learning today is not
like machine learning of the past. It was born from pattern
recognition and the theory that computers can learn without being
programmed to perform specific tasks; researchers interested in
artificial intelligence wanted to see if computers could learn from
data. The iterative aspect of machine learning is important because as
models are exposed to new data, they are able to independently adapt.
They learn from previous computations to produce reliable, repeatable
decisions and results. It’s a science that’s not new – but one that
has gained fresh momentum.
While many machine learning algorithms have been around for a long
time, the ability to automatically apply complex mathematical
calculations to big data – over and over, faster and faster – is a
recent development. Two of the most widely adopted machine learning
methods are supervised learning and unsupervised learning – but there
are also other methods of machine learning. ML projects differ from traditional software projects. The differences lie in the technology stack, the skills required for an ML-based project, and the necessity of deep research. To implement your ML aspirations, you should use a programming language that is stable, flexible, and has tools available. Python offers all of this, which is why we see lots of Python ML projects today. From development to deployment and maintenance, Python helps developers be productive and confident about the software they’re building. Benefits that make Python the best fit for machine learning projects include simplicity and consistency, access to great libraries and frameworks for neural networks and machine learning (ML), flexibility, platform independence, and a wide community.
