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Introduction Cryptography is the study and application of secure communication techniques within the presence of third parties known as adversaries. It deals with developing and analysing protocols those malicious third parties from retrieving info being shared between 2 entities, thereby following the assorted aspects of data security. A human being from ages had two inherent wants to speak and share information and speak by selection. These two want to rise to committal's art to writing the messages in such the most straightforward way that solely the meant individuals might have access to the data. Unauthorized individuals couldn't extract any info, even though the disorganized messages fell in their hands. The art of concealing the messages to introduce secrecy in info security is recognized as cryptography. The word 'cryptography' was coined by combining 2 Greek words, 'Krypto,' which means hidden, and 'graphene,' which means writing. History of Cryptography The art of cryptography is taken into account to change the state of the art of writing. As civilizations evolved, people, in general, got organized into tribes, groups, and kingdoms. This junction rectifier leads to the emergence of concepts like power, battles, supremacy, and politics. These concepts more oxyacetylene the natural want of individuals to speak in secret with selective recipients that successively ensured the continual evolution of cryptography. The roots of cryptography are found in Roman and Egyptian civilizations. Secure communication refers to the situation wherever the message or information shared between 2 parties can't be accessed by an associate human. In Cryptography, an assistant human could be a malicious entity that aims to retrieve precious info or information, thereby undermining data security principles. Core principles of contemporary cryptography   Confidentiality It refers to specific rules and pointers typically dead underneath confidentiality agreements that ensure that the data is restricted to particular individuals or places. Information Integrity It refers to maintain and ensure that the information stays correct and consistent over its entire life cycle. Authentication It is the method of creating positive that the piece of knowledge being claimed by the user belongs to it. Non-repudiation It refers to the ability to form positive that someone or a celebration related to a contract or a communication cannot deny their signature's genuineness over their document or the causation of a message. Evolution of Cryptography Within the digital age, cryptography has evolved to handle the encoding and decipherment of personal communications through the web and pc systems, a branch of cyber and network security, in a much more complicated manner than something the planet of cryptography had seen before the arrival of computers. Importance in Cyber Security The most basic uses of pc cryptography are for scrambling a chunk of text and causation it over the web to a far off location, wherever the information is unscrambled and delivered to the receiver. In this manner, pc cryptography and cybersecurity go hand-in-hand. Certificate Authorities (CAs) area unit answerable for passing out digital certificates to validate the possession of the encoding key used for securing Communication on a trust basis.   Written by Ms. Sonali Thakur B.Tech 2nd Year RBIENT, Hoshiyarpur, Punjab  

Introduction The thought of traditional training has changed drastically in the last couple of years. It is undoubtedly the final off. Being physically contained in a classroom isn't the discovery. It is indeed just anymore — not with all the risk associated with net and brand new technologies, at the least. Nowadays, you have access to a good education whenever and wherever you prefer,  as long as you get access to a computer. We're today entering an age that is brand new to the change of web education. There's no have to discount the skepticism training that is surrounding online. It's hard to comprehend the notion of abandoning the mainstream class, especially if it is to handle this vast space labeled as the Internet. Nevertheless, that's not reason enough to shy away from this alternative, which is helpful and suitable for all students. Following the most recent Babson research analysis Group, over 30 % of higher education students take one or more distance training courses. Online education is an option that makes sense you're an adolescent or a grown-up. It is often a helpful way of sharpening your skills in a complicated topic or discovering a brand new ability as being a pupil. Why don't we take a glance at the advantages of on the web learning:   1.It's flexible Education enables the instructor; therefore, the student setting their particular learning is undoubtedly very own rate. There's the additional mobility of setting a schedule that fits everyone's schedule. As a result, utilizing a web system is certainly academic for much better work and scientific studies. Therefore there's no need to offer anything up. Studying online teaches you time. It is an undoubtedly essential skill, which makes getting an excellent work-study balance simpler. Having a standard schedule with the student and instructor can also prompt both parties to accept brand new responsibilities and have more autonomy.   2. It offers a vast selection Within a wide space on the internet, you can find limitless skills and subjects to instruct and learn. A number of this is undoubtedly growing, and higher education schools offer web versions of the programs for various amounts and disciplines. From music composition to quantum physics, you will find choices for all types of students. Learning your program on the net is also a good option for getting the state certificate, diploma, or level without literally establishing foot for a college university.   3. It's accessible Online education enables you to learn or instruct from anywhere in the world. It means that there's no need to commute from 1 destination to another or follow a routine. It is undoubtedly rigid. In addition to that, not only do you save time,  but also save money, which you can use for other concerns. The virtual classroom is also available anywhere; there's a web connection, and a great way to take advantage of this is traveling. For example, if you're studying abroad and want to get a task, online education is a great option. There's no reason at all to stop working or studying while checking out brand new and exotic locations.   What Are Massive Open Online Courses? Massive Open Online Courses (MOOCs) offer accessible and inexpensive discovering that is remote to students worldwide. Numerous famous degree institutions, including Harvard University and the Massachusetts Institute of Technology, deliver these web programs for a variety of topics and at a variety of academic amounts. You can have a course this is certainly solitary delve deeply as a specific topic and take a sequence of courses to gain a comprehensive understanding of a location of research.   If you are looking forward to acquiring a validated certification of completion when you can access many MOOCs platforms. Most of these platforms offer free courses. However, particular systems charge a little cost. Relatedly, some universities provide program credit for these classes, which can be online. As his or her title proposes, MOOCs frequently enlist hundreds, also thousands, of learners at any given time. These courses typically offer available enrollment — in other words., year-round enrollment or inside a designated time framework — and a self-paced learning format to support such a vast student population.   Canvas Network Canvas system focuses primarily on expert development classes for teachers, school administrators, and other knowledge leaders. Topics include leading and assessing; this is undoubtedly using pupil affairs, encouraging females in STEM industries, and studying information administration for librarians. Students can access MOOCs in English, Chinese, Portuguese, and Spanish.   Cognitive Class Formerly known as Big Data University, Cognitive Class is an effort by IBM to distribute data literacy through no-cost courses for students and experienced Information Technology professionals alike. People can pursue coursework at their speed; this is undoubtedly own with time limitations for completion. These MOOCs cover individual topics like Python for information research, reactive architecture, and digital analytics and regression.   Coursera Coursera ended up being launched in 2012 by two Stanford teachers, and it is one of the most considerable massive accessibility this is undoubtedly available providers on earth. The working platform lovers with 190 companies and universities to provide remote and understanding that is self-paced, leading to digital certificates at the undergraduate, graduate, and postgraduate amounts. Coursera is globally trusted and provides a high level of user satisfaction. It has approximately 87% of people stating professional benefits.   edX Created as being a joint venture of Harvard and MIT, edX is another leading MOOC platform. Students have access to more than 2,500 courses from 140-degree institutions addressing topics that are well-known data research and humanities. The platform now offers computer system technology classes in Python, front-end, and development, along with full-stack development courses and cybersecurity courses.   FutureLearn FutureLearn is a massive open online course platform created in the U.K. in 2012 by 12 college lovers, including King's College London and the University of Leeds. Students can select and complete finish one of 418 courses and develop additional skills in areas like digital product management, ecology, wildlife technology, and the future of globalization. They may also get significant certifications from leading universities and organizations.   Khan Academy Khan Academy bases its business goal on the belief that training is just a right of every human. The platform provides entirely free online courses that integrate instructional movies, rehearse exercises, and a customized learning dashboard to this end. Unlike many other MOOC providers, Khan Academy mainly supports K-12 pupils, with content for pre-algebra, English language education, A.P. chemistry, and U.S government and civics.   Udacity Udacity is just a MOOC platform that focuses on professional development through technical and vocational online classes. It offers multiple courses in the latest technologies, information science, cloud computing, independent systems, etc. Students can also take development and development courses in C++, Blockchain, and Android os creator.   Udemy When it comes to MOOC platforms, Udemy is undoubtedly the biggest. Udemy provides over 150,000 courses in 65 languages. While some courses are provided free of cost, there are a few with minimal charges. By paying for premium content, users also gain access to features like direct texting, Q&A, and completion certificates.   A digital classroom (VC) can be a web platform that replicates physical classrooms; however, it is in a digital space. It's an online learning environment. VCs make it possible for teachers to use tools to involve students and enhance their learning experience. VCs can often be used as stand-alone discovering systems or product classrooms. In a few cases, VCs are more interactive and convenient in various ways. Virtual classrooms Virtual Classrooms or VCs are different from online courses which are for self-paced learning. They connect students and instructors in real-time. They provide the opportunity to remotely collaborate with the instructor while learning. Features of Virtual Classrooms 1. Mobility Digital classes enable teachers and students to develop learning at their own pace. Courses could be planned per a flexible time-table as easiest for teachers and students. 2. Accessibility Online discovering via classrooms expands the get to of knowledge. Pupils and educators from various areas of the country (and, in reality, the planet) can come collectively virtually for learning. The essential requirement of a digital classroom is a net connection as well as a device. This mode of learning is certainly suitable. 3. Economical A digital understanding has proven to become cost-effective in several situations. Instructors from various areas of the world can teach students from remote places without any need of visiting any campus or institution. Students can learn brand-new skills, spending money on additional tuition and publications. 4. Personalized Training Experience These online classes can be customized as per the requirements of the students. It includes deciding the length of the course or any additional requirements that can be utilized. Teachers can recognize the talents and requirements of students and employ sources that are offered. 5. Wide Reach A platform that is online be used by different grades and for various academic and non-academic topics.   How online learning has become an integral part of the current education system: Virtual Class and Traditional Training Environments can be functional concurrently. For several years, educators have discussed whether digital classrooms will replace physical classrooms. Nevertheless, digital classrooms and conventional classrooms can co-exist to enjoy combined benefits. They can be used collectively to augment and improve the learning experience of students. 1. supplement courses which can be existing Digital classrooms are around for exclusive learning. Online classrooms act as supplementary mediums to aid offline classrooms. Traditional learning has yet not changed with online learning. These two kinds can co-exist and help learners in gaining knowledge. 2. Inclusive Learning Digital classrooms tend to be enablers of understanding, which can be all-encompassing and comprehensive. Several pupils throughout the world aren't able to gain access to knowledge because of physical limitations. The education imparted virtually can expand its Reach to pupils who're challenged or lack specific requirements to go to a classroom; this is certainly regular. 3. Extended Reach Virtual classrooms are undoubtedly unidirectional quality education. Now students in different parts of the world have access to the same information provided by the best instructors and they have the flexibility to collaborate on numerous projects without the need to travel from remote locations to big cities or compromise with mediocre training available to them in their small towns. 4. Continuity Of Education In Unforeseen Circumstances Mastering with digital courses can carry on even though schools tend to be closed temporarily or even for longer intervals. The present circumstance that is COVID-19 has places education systems to check. The schools and colleges around the globe needed to adapt online learning in order to continue seamless education.   Written by Ms. Amanpreet Kaur B.Tech - IT Rayat Bahra Institute of Engineering & Nano Technology Hoshiarpur, Punjab

Over time, the expansion of the internet is epidemic. Every other person has access to the internet. In this situation, the easiest way to advertise any brand is online. Digital marketing is conveyed through digital medium. These mediums can be social media, mobile applications, emails, text message, electronic billboards etc. In more professional way, any form of marketing of products or services that indulge electronic devices. Often people believe that digital marketing needs to be online, which is not true. Digital marketing can be both online and offline. OFFLINE DIGITAL MARKETING Radio marketing While listening to radio, you hear various types of ads; it is a type of marketing technique. It is one of the initial forms of digital marketing. Many people think it is not relevant anymore but as long as you understand your audience and know their requirement it is still a relevant unique. Television marketing It is one of the most popular forms of advertising. There are so many times you see a product on television and you buy it. It attracts most of the audience. Phone marketing These days, phone marketing is trending. Smartphones are killing it. As you know, more people are accessing mobile instead of desktops and laptops. Much money is spent on mobile ads rather than television ads. Cold calling is calling an unknown person who has no prior knowledge of the product and trying to sell them. Text message marketing This type of marketing also helps in also helps to gain the customer's attention. Enhanced offline marketing While you scroll in your vicinity, various electronic billboards and posters grab your attention. This is called enhanced offline marketing. These are some of the easiest and obvious marketing tricks. ONLINE DIGITAL MARKETING Search engine optimization It is a process of increasing the rank of your website on any search engine. With SEO, the content of the page will be optimized and it makes sure it appears on a couple of pages of the search engines. It is the best way to gain organic traffic on your website. Content marketing These days, customers are just not satisfied with my websites only, which opens the door to various other options for ex- blog posts, brochures, eBooks, articles and guides etc. If your content is really interesting and genuine it will get awareness and attention. Social media marketing These days the most popular thing in this whole world is social media. Almost all the people hold a social media account. So, the easiest target audience is this audience. If you want to increase brand awareness, come across as a market leader, generate leads, and communicate with customers, these platforms need to be utilized. You just need to find which platform has the most number of audiences. Affiliate marketing In affiliate marketing, you ask a famous personality or YouTuber to promote your product and sell them on your behalf because they have a big audience and in return you give them some amount of commission. Pay-per-click advertising You see various sponsored ads on your Instagram, Facebook, and LinkedIn.  When clicking on them, advertisers pay a fee each time you click on them. Search engine advertising is one of the most popular forms of PPC. It allows advertisers to bid for ad placement in a search engine's sponsored links when someone searches on a keyword that is related to their business offering. Email marketing Emails can be a good option for promotion, follow-up messages, newsletters, upcoming sales, and more. IMPORTANCE OF DIGITAL MARKETING When it comes to marketing people still opt the older version like printing pamphlets and print ads. The potential customer can be found more on-line instead of locally. Using Digital marketing, you can interact with an enormous amount of audience effortlessly. You can interconnect with so many people which will ultimately increase your reach. This will be very essential for your business. You can compete on a larger scale and with big industries. You can target your ideal audience. You can be accessible to your audience every time. You will be aware of your competition and do changes according to trends and needs. Using digital marketing you can get your customers feedback. You will get to know what your audience wants from you. You can do your business on a global platform. By embracing digital marketing, online and offline, you will increase brand awareness and give your consumers multiple channels by which to access your products and services. You will get the return of your investment. SCOPE OF DIGITAL MARKETING Digital marketing provides a good job opportunity all over the world. So the career growth in this field is very impressive. It is one of the fastest modes of marketing and promotion all over the world. Due to the global pandemic, many economists suggest that the scope of digital marketing is very high. A report in Indian Express suggests that 85% marketers are tracking revenues generated through digital marketing and 50% of them reported that e-marketing activities are contributing to more than 10% of their revenues. “Digital marketing is no more a medium, it is a business”. Written by: Farheen Hussain B.Tech – Integral University, Lucknow

Agile Project Management (APM) is an iterative method to planning and managing project processes that values human communication and opinion, adapting to change, and producing working results. Agile was first conferred in the 1970s by William Royce. Later in 2001, the Agile was published by 17 software developers. Agile Methodology The Agile Method and methodology is a specific approach to project management that is used in software development. Agile methodologies should go along with the software development cycle – planning, execution and final delivery – therefore permit software to be developed in stages; this makes it easier to recognise and fix bugs. There are many methodologies that follow this Agile mind-set. Here are the five main agile methodologies and their advantages in the software development universe. The most widely-used Agile methodologies include: 1. Agile Scrum Methodology Scrum refers to a framework that makes for effective collaborations among teams that are working on complex products. Agile scrum methodology focuses on delivering several iterations of a product to provide stakeholders with the highest business value in the least amount of time. Here are some of the inclusively benefits of agile scrum methodology: Flexibility and adaptability Creativity and innovation Lower costs Quality improvement Organizational synergy Employee satisfaction Customer satisfaction 2. Lean Software Development Lean Software Development is an iterative Agile methodology that focuses the team on delivering value to the customer through essential value stream depict. It is a highly flexible, evolving methodology without rigid guidelines, rules, or methods. There are 7 principles to Lean software development, each aiming to fast delivery and bring higher value to end-user: Eliminating Waste Building Quality In Amplifying Knowledge Delaying Commitment Delivering Fast Respecting people Optimizing the whole thing Advantages of Lean Software Development The elimination of waste leads to the overall efficiency of the development process Delivering the product early is a definite advantage. It means your development team can deliver more functionality in a shorter period of time. Empowerment of the development team helps in developing the decision making ability of the team members which in turn, creates a more motivated team. 3. Kanban Kanban is a highly visual workflow management method that is popular among Lean teams. Like Scrum, Kanban is a process designed to help teams work together more effectively. Kanban is based on 3 basic principles: Visualize what you’ll do today (workflow automation): Seeing all the items within the context of each other can be very informative Limit the amount of work in progress (WIP): This helps balance the flow-based approach so teams don‘t start and commit to too much work at once Enhance flow: When something is finished, the next highest priority item from the backlog is pulled into play. Here are some of the benefits of Kanban: Better visibility Improved efficiency Increased productivity Preventing team overburden Increased team focus Reduced waste 4. Extreme Programming (XP) XP is a disciplined approach for high-quality agile software development, focused on speed and continuous delivery. It is intended to improve software quality and responsiveness in the face of changing customer requirements. It promotes high customer involvement, rapid feedback loops, continuous testing, continuous planning, and close teamwork to deliver working software at very frequent intervals, typically every 1-3 weeks. The original XP method is based on four simple values: Simplicity Communication Feedback Courage Advantage of Extreme Programming Reduces the risks Save costs and time Process is visible and accountable Constant feedback Working software faster Employee satisfaction and retention. Teamwork 5. Crystal The Crystal methodology is one of the most sheer, adaptable approaches to software development. Crystal actually embraces a family of Agile process models, including Crystal Clear, Crystal Yellow, Crystal Orange and others. Each has isolated characteristics driven by several factors, such as team size, system criticality, and project priorities. Crystal includes joint action, communication, and simplicity, as well as reflection to frequently adjust and boost the process. Like other Agile frameworks, Crystal assists early, frequent delivery of working software, high user involvement, adaptability, and the removal of authorities or distractions. Advantage of Crystal It ensures frequent deliveries, in order to identify eventual problems in every stage There is always space to improve characteristics, taking some time from software development and allowing for a discussion about how to perfect processes. Allows for a closer communication and promotes interaction and sharing of knowledge between team members. Requires a technical environment with automated tests, configuration management and frequent integration. Scope and the future of Agile Project New reports are showing that Agile is increasing in popularity and winning over waterfall users into the new incremental development in Agile. Agile Project Management is an interactive process that drives focus on consumer satisfaction first, team harmony over the tasks, and adapting to the current business requirements rather than just sticking to a textbook plan. Written by: Ankita Kashyap B.Tech - CSE UIET, Kanpur

Natural language processing is the segment of Artificial Intelligence that is focused on enabling automatic manipulation of language. Natural Language Processing is a very popular field pertaining to Artificial Intelligence and provides the capabilities to machines to read, understand, and derive a meaning from a sentence written in human language, that actually makes sense. NLP primarily depends on machine learning algorithms for deriving meanings from words and sentences. NLP is one of the hottest and trendiest topics these days. Companies are investing an enormous amount of money in this as its outcomes are remarkable. One of the most familiar examples of NLP is Google Voice Search. Benefits of Natural Language processing Search Autocorrect and Autocorrect - There are several times you search anything on google and it automatically completes the sentence and even corrects your grammar. Ever thought how it happens? It's NLP which is behind all this. Isn't it a blessing? Language translator – Language is a requisite part of the global world. It allows us to share our ideas and information with everyone. It helps to communicate and eliminates the language barrier. NLP is the main reason behind such translators. Social Media Marketing – Millions of data are generated by blogs, articles, and searches. Some companies gather searches for users and give it to companies to amend their plans. Companies have applied this technology to achieve work-oriented goals to improve productivity or job progression. Chatbots – It is impossible to reply to all the queries manually. In such situations, chatbots come handy. Chatbots are robots which interact with humans to answer their query. It reduces the cost and no. of the people and surely increases customer experience. Target Audience – Often you search for anything online for example a T-shirt and you will realize you are seeing its advertisement on several other websites as well. This is called target advertising. It works on the mechanism of keyword matching which is also a part of NLP. Voice Assistant – Alexa, Siri, Google assistant are the most amazing inventions and very popular these days. It is a digital assistant that uses a voice recognition system and natural language processing to work. Challenges of Natural Language Processing The most considered problem is human language. It is hard for computers to understand human language especially when people start using their specific lingo. When a customer asks several questions in one question, then it is hard for the application to answer it. Computers sometimes fail to answer all the inquiries at once. People sometimes surmise that computers will understand their context and it has a memory which is untrue. The same word having different meanings also causes strain to the computer. Misspellings also cause trouble for the system.                            Scope and future of NLP The scope of Natural Language processing is very high. It is definitely an evolution in the field of Data Science. It will have human potential in text and speech analysis which will be convenient in scrutinizing large quantities of data. As NLP makes Data more user-friendly and more intractable it can be a game-changer in the field of computer science and business as well. Several estimations have been that in the future most of the application will be NLP-platform driven. Written by- Farheen Hussain B.Tech 4th year Integral University, Lucknow

Python is an open source, high level and object-oriented programming language, which is widely used in computer industries due to its versatility, ever-growing community, and continuous development, which in turn results in release of new and updated libraries, that are very essential for complex tasks. Hence, python has become the most preferred programming language among the developers in the recent years. Python is a multipurpose language used for various tasks, such as web development, ethical hacking, data science and related fields like machine learning and artificial intelligence etc. Since the first release of Python, it has been undergoing continuous upgrades. As a result, multiple versions have been launched so far with updates features, bug fixes etc. The latest release of Python 3.8.5 has come up with some significant improvements and updates, and also witnessed some new features such as: •    Assignment expressions There is new syntax := that assigns values to variables as part of a larger expression. It is affectionately known as “the walrus operator” due to its resemblance to the eyes and tusks of a walrus. In this example, the assignment expression helps avoid calling len() twice: if (n := len(a)) > 10:    print(f"List is too long ({n} elements, expected <= 10)") A similar benefit arises during regular expression matching where match objects are needed twice, once to test whether a match occurred and another to extract a subgroup: discount = 0.0 if (mo := re.search(r'(\d+)% discount', advertisement)):     discount = float(mo.group(1)) / 100.0   The operator is also useful with while-loops that compute a value to test loop termination and then need that same value again in the body of the loop: #Loop over fixed length blocks while (block := f.read(256)) != '':     process(block)   •    Positional-only parameters There is a new function parameter syntax / to indicate that some function parameters must be specified positionally and cannot be used as keyword arguments. This is the same notation shown by help() for C functions annotated with Larry Hastings’ Argument Clinic tool. In the following example, parameters a and b are positional-only, while c or d can be positional or keyword, and e or f are required to be keywords: def f(a, b, /, c, d, *, e, f):     print(a, b, c, d, e, f) The following is a valid call: f(10, 20, 30, d=40, e=50, f=60) However, these are invalid calls: f(10, b=20, c=30, d=40, e=50, f=60)   # b cannot be a keyword argument f(10, 20, 30, 40, 50, f=60)                   # e must be a keyword argument One use case for this notation is that it allows pure Python functions to fully emulate behaviors of existing C coded functions. For example, the built-in divmod() function does not accept keyword arguments:   def divmod(a, b, /):     "Emulate the built in divmod() function"     return (a // b, a % b) •    Parallel filesystem cache for compiled bytecode files The new PYTHONPYCACHEPREFIX setting (also available as -X pycache_prefix) configures the implicit bytecode cache to use a separate parallel filesystem tree, rather than the default __pycache__ subdirectories within each source directory. The location of the cache is reported in sys.pycache_prefix (None indicates the default location in __pycache__ subdirectories). •    Debug build uses the same ABI as release build Python now uses the same ABI whether it’s built in release or debug mode. On Unix, when Python is built in debug mode, it is now possible to load C extensions built in release mode and C extensions built using the stable ABI. •    f-strings support = for self-documenting expressions and debugging Added an = specifier to f-strings. An f-string such as f'{expr=}' will expand to the text of the expression, an equal sign, then the representation of the evaluated expression. For example:   >>> user = 'eric_idle' >>> member_since = date(1975, 7, 31) >>> f'{user=} {member_since=}' "user='eric_idle' member_since=datetime.date(1975, 7, 31)"   •    Python Runtime Audit Hooks The PEP adds an Audit Hook and Verified Open Hook. Both are available from Python and native code, allowing applications and frameworks written in pure Python code to take advantage of extra notifications, while also allowing embedders or system administrators to deploy builds of Python where auditing is always enabled. List being almost endless, many other crucial features and updates are introduced with the release of Python 3.8.5 version which would surely be beneficial for developers. So, these are some of the new updates in the recent version of Python, which are surely going to help the programmers to try out something different. I hope this article will help you out if you are interested in knowing about the recent developments in features of Python, and are looking forward to use it. Written By:  Amit Kumar B.Tech - ECE Birla Institute of Technology, Mesra  

What is Data Science? Data Science can be called as a blend of algorithms, machine learning principles and various other tools with the goal to discover the hidden patterns by making use of raw data. Data science can also be explained as the concept that unifies statistics, data analysis, machine learning principles, domain knowledge and other related methods. It makes use of techniques and theories which are drawn from many sub branches of mathematics, statistics, computer science, domain knowledge and information science and is related to various technologies such as artificial intelligence, data mining, machine learning, and big data. The role of a Data Analyst is to basically explain the processing history of the data. On the other hand, a Data Scientist not only does the explanatory analysis to discover insights from history of the data, but also plays a vital role in using various machine learning principles to analyse the data and make decisions to predict about the futuristic events.  Frameworks, programming languages and visualization tools are the three most import pillars which help a data scientist for strengthening the foundation and development of data science and other related fields. There are various frameworks and platforms which are very important for a data scientist when it comes to development of data science, and other related fields such as artificial intelligence and machine learning such as: •    TensorFlow, which is a framework developed by google for the purpose of creating machine learning models. •    Pytorch is another framework which was developed by Facebook for machine learning and data science. •    Jupyter Notebook is a free, open-source, interactive web interface for Python that allows can user to combine software code, faster experimentation and, computational output. •    Anaconda is a free and open source platform which provides provides a comprehensive distribution of the Python and R programming languages. •    MATLAB is a very famous computing environment which is very commonly and heavily used in industry and academia. •    Apache Hadoop is another software framework which is being used for big data analysis to process data over large distributed systems.   Data scientists also make use various kinds of visualization tools for analysing data and development of data science.  Some of them are: •    AnyChart is a tool that provides JavaScript libraries for data visualization in charts and dashboards. •    Google Charts, developed and supported by Google is a JavaScript-based web service for creating graphical charts. •    Tableau makes a variety of software that is used for data visualization. •    PowerBI, developed by Microsoft is an analytics service for businesses. •    Qlik produces software such as QlikView and Qlik Sense used for data visualization and business intelligence. •    Sisense is a visualization tools which provides the user a front-end for building data visualizations. Programming languages are the most crucial and important part when it comes to data science and other related fields. Some programming languages like Python, R, Julia are among programming languages preferred by data scientists. Among which Python is the most preferred choice by data scientists among all the other programming languages in this list. It is the most famous and widely used programming language for the purpose of data science, machine learning, and artificial intelligence. Why Python for Data Science? Python is one of the most popular high-level object-oriented programming languages with simple syntax that is commonly used for data science by a huge number of data scientists and developers. Guido van Rossum invented and designed python in 1991, and Python software foundation has further developed it. Python is an open-source and portable language which supports a large standard library. The main advantage of python over other programming languages is its ability to emphasize code readability due to its simple syntax and scientific and mathematical computing through libraries which plays a major role in data science. There are a number of python libraries that are used in data science including NumPy, SymPy, Orange, Scipy etc. Data analysis and Python programming are complementary to each other. Python is an incredible language for data science and those who want to start in the field of data science. It supports a huge number of array libraries and frameworks to give a choice for working with data science in a clean and efficient way. The various frameworks and libraries come with a specific purpose for use, and must be chosen according to your requirement. Here we have listed some of the best Python frameworks used for data science. These are several reasons for which data scientists and developers prefer Python over the other programming languages. Presence of various kinds and a number of libraries in Python make it the most preferred programming language for data science. Some of the widely used python libraries are:  •    NumPy, which is abbreviation for Numerical Python. It is the one of the most popular library and base for higher level tools and utilities in Python programming for data science. NumPy arrays help us in using Pandas which is another library for python effectively. NumPy can also be used to work with multidimensional arrays and matrices along with its functions related to statistical, numerical computation, linear algebra, Fourier transform, etc.  •    Pandas provide data frames in Python programming language. Pandas is a very powerful library for analysis of raw data. Pandas makes it easy to handle missing data and supports manipulation of differently indexed data and also has the capability to support automatic data alignment. Pandas is also rich in tools related to data analysis and data structures like merging, shaping, or slicing the data. •    SciPy used for computing purposes such as image processing, integration, interpolation, special functions, optimizations, linear algebra and many other tasks. This library is an open source library and is used with NumPy to perform efficient numerical computation. •    SciKit is a very popular library which is used for data science and machine learning with various regression and clustering algorithms. The role of SciKit is to interoperate with SciPy and NumPy. •    Matplotlib is a python library which stands for Mathematical Plotting Library in Python, which is mostly used for data visualization, 3D plots and graphs, histograms, image plots, scatterplots, bar charts etc. It is supported on all platforms such as Windows, Mac, and Linux. This library can also be considered as an extension for the NumPy library.  These libraries are among the best and widely used python libraries for data science. There are several other Python libraries such as NLTK for natural language processing, Pattern for web mining, Theano for deep learning, IPython, Scrapy for web scraping, Mlpy, Statsmodels etc. Other than the presence of a variety of libraries, Python also has some extraordinary features and qualities that have settled Python on the top choice for developers & data scientists, including: •    Python is versatile programming language and supports almost all platforms like Windows, Mac, Linux etc. •    Python is extremely strong and straightforward programming language having simple syntax.   •    Python being a high-level programming language, helps you to write program in simple way nearly English and it gets internally converted in low level code. •    Python can perform some complex tasks like data visualization, data analysis and data manipulation. NumPy and Pandas are a some of the libraries in python which are used for manipulation of the data. •    Python contains various other powerful libraries other than libraries for machine learning and scientific computations. •    Python helps in various complex scientific calculations and machine learning algorithms which are often performed using this language easily in relatively simple syntax. •    Python is faster than many other languages like Matlab and Stata which is a great benefit for developers and data scientists. •    Python has emerged as a programming language that can be used for various usages in several industries and for rapid development of applications of all types. •    Python comes with a variety of data visualization options among which is Matplotlib that provides the solid foundation for other libraries like Seaborn, Pandas etc. are build. •    The Python community also plays a vital role in exceptional rise of Python. As Python is extending its reach, more and more volunteers are creating data science libraries. •    The Python community promotes quick access for people who want to find out solutions to their coding problems. The landscape of data science is changing rapidly, and likewise the tools which are being used for extracting values from data science are also growing rapidly.  The use of Python programming language in Data science has empowered the data scientists to accomplish more in less time which is very crucial for the fast-moving tech world. Python is highly adaptable programming language and can work in any environment effectively and can even be integrated with other programming languages very efficiently. With the tech giants like Google making the learning curve short and easy for enlightening the path to use Python, it becomes the most popular language in the data science world.   Witten By: Shryansh Nigam B.Tech – IT Birla Institute of Technology, Mesra  

Introduction "Ethical Hacking" is a security practice where an expert hacker is hired in an organization to perform certain tasks like hacking into systems, cracking passwords, performing penetration testing, etc. Just to analyse the weaknesses of the system, search for any possible vulnerabilities, and try to eradicate them. We can also say that Ethical Hacking is a legal variation of hacking. If we talk about hackers then they can be categorized into 3 groups. White hat - They are the "Ethical Hackers" and they perform hacking for the good of the organization they are working in. Black hat - They willingly perform hacking just for the sake of doing criminal activities like stealing money, identity theft, etc. Grey hat - They lie between both white and black hat hackers. They have the skills of hacking but neither they use them to do criminal activities nor they improve the security of systems. They find hacking challenging and fun for them and there is no other motivation. Web application security Before discussing web application security first let's talk about what is a web application? Well, basically a web application is a program that is stored somewhere on a server and we can access it using a browser. Web applications consist of two sides front-end which is developed by using languages like HTML, CSS, JavaScript, etc. and back-end which is developed by using languages like PHP, .NET, etc. Now web application security is simply a process of securing web applications against different kinds of cyber-attacks by detecting and fixing the possible vulnerabilities. and according to OWASP(Open Web Application Security Project) which is an organization dedicated to web application security, some of the web application attacks are - SQL injection. Cross-Site Scripting (XSS).  Broken Access Control. Distributed denial of service (DDoS). cross-site request forgery (CSRF). A developer who is developing a web application must be aware of these web attacks because websites become vulnerable only when there are some loopholes left unrecognized by the developer. and it would be best if the developer works in collaboration with an ethical hacker. As soon as the developer is done with a module, an ethical hacker can perform penetration testing and find possible vulnerabilities. web application security is of higher concern for the businesses which are totally dependent on a web application because even a single vulnerability can cost them a lot if exploited by a black hat. Now let's dive deeper into one of the web application attacks i.e, SQL injection, which when exploited can cause damage to the database of the website. SQL injection SQL injection as its name suggests is the process of injecting malicious SQL queries into vulnerable websites so that the database can be hacked. as we know database is the core of any website and it stores critical information like user credentials and even their bank account details. So, SQL injection can be seen as one of the most destructive cyber web attacks. If you are wondering what does the term "SQL" means then SQL is basically a programming language used to perform operations on databases like creation, updating, deletion, etc. How SQL injection works? To understand how does it works, let's consider a scenario in which a user is trying to login to a website by entering his/her username and password in the login form. He enters username as 'Alex' and password as '123'. Meanwhile in the backend of the website a SQL query will be executed which may look like - SELECT * FROM users WHERE username='Alex' AND password='123'; Now suppose this website is SQL vulnerable and the attacker injects the string ' OR 1=1 into the username and password fields. The SQL query now formed would look like - SELECT * FROM users WHERE username=' ' OR 1=1 ' AND password=' ' OR 1=1 '; As we know 1=1 is always TRUE, so the above WHERE clause will be executed as TRUE, and this query will return all rows from the users table. How to prevent SQL injection? In order to prevent websites from these attacks, the developer should never take the data from the input field and directly pass it into the SQL query. Instead, the approach should be to eliminate the delimiters if present in the string and then do the SQL work. Another approach can be to use encryption. Whatever will the input supplied by the user firstly, should be converted into a hash for ex - MD5 or SHA. Then, this hash value should be compared with the hash present in the database. Doing so will eliminate all the possibilities of SQL injection done by exploiting input fields. Scope and future of Ethical Hacking In India, after the Digital India campaign, almost everyone uses the internet for important transactions and companies are also transforming their traditional business model into a digital one, where all the critical business and customer information is stored on some server. From the perspective of a black hat, it's a great opportunity and it leads to an increase in the number of cyber-attacks.  Now here comes the need of an expert certified Ethical Hacker who can monitor the internet based applications of an organization and protect their valuable data against hacking attempts. This need will continue to grow in the future. Career opportunities and growth in this field will keep on increasing as more people will use the internet and almost every work will be done on some network that needs to be secure.   Article Written By: Sanchit Gupta Sudent - MCA 2nd Year Jagran Institute of Management, Kanpur

When dealing with strings of data, at times we need to find specific value or data in the string. This is where you create a substring of the data that you need. This can be extremely useful for stripping out certain values from lists or getting a substring of characters from a string. There are various ways in which you can get a substring from a string in Python.  Watch the video above to learn how exactly it can be done with the help of a live example.   

If you want to learn Python to become a Python programming expert then this Python fundamental video is a great place to start with. Since this Python tutorial and examples, video can be taken by anybody, so if you are a computer programmer then you can also watch this Python tutorial to take your coding skills to the next level. Meanwhile check out our channel for more upcoming tutorial videos.

  K-Nearest Neighbors (K-NN) is one of the simplest machine learning algorithms. Like other machine learning techniques, it was inspired by human reasoning. For example, when something significant happens in your life, you memorize that experience and use it as a guideline for future decisions. Let us understand this with an example, you know and have seen a piece of glass break when it falls on ground. While the glass is falling, you’ve made the prediction that the glass will break when it hits the ground. But how can you do this? Watch the above video to know more

Java includes a very robust framework for data storage and manipulation. This framework is known as the collections framework, which consists of interfaces and their concrete implementations in the form of classes. Map is an interface in this Java collections framework which is used to store objects in the form of key value pairs. This key value pair is referred to as an entry in the map. Map doesn't allow duplicate values, and neither it maintains the insertion order because each value is associated with a key, and the values can be accessed easily with the help of their corresponding keys. So if you are looking to store key-value pairs in Java program,  you have a wide range of choices available depending upon your requirement. The main difference between Linked Hash Map, Tree Map, and Hash Map comes in their internal implementation and specific features, which makes them useful in certain scenarios.  Find out more in the above video.   

  Java String split method is used for splitting a String into its sub strings based on the given delimiter or regular expression. Mostly this attribute will be a space or a comma with which you want to break or split the string.Java offer two methods to split an string using regex and integer limit. First method is to use string [] split (string regex). This method returns an array of strings after splitting an input string based on the delimiting regular expression. Second method is use string [] split (string regex, int limit). This method is used when you want to split strings at a particular length. The only difference between this and the first method is it limits the number of strings returned.  Refer the above video to know more how you can split strings in java with a example.

  Strings in Java are objects used to represent a sequence of characters. They can be either created using the String Literal or by using the NEW keyword. Strings are immutable in Java are represented in the UTF-16 format. When a new String is created, it looks for the String with the same value in the JVM string pool. If it finds the same value, then it returns the reference else it created a String object and places that object in the String. Since Strings are immutable in Java, whenever String manipulations are performed, automatically a new String would be generated by discarding the older one. But, don’t you think, this is cumbersome when we have large applications? Well, to avoid garbage in heap, Java came up with StringBuffer and StringBuilder Click on the above video to understand the difference in details with the help of live example.  

  In this video, we will see how we can convert a string into an integer. As we all know the String in is a sequence of characters, for example Hello is a string of 5 characters. In java, a string is an immutable object which means it is constant and can not be changed once it has been created. And integer is a data type in Java. One point to note here is if you want to manipulate a string made up of digits like one two three, you need to convert to an integer value for any further arithmetic operations. So how can we convert a string into integer in Java ? There a two ways in which you can convert the string to int in Java.   1. Integer.parseInt(String) method 2. Integer.valueOf(String) method   Refer to the linked video for more detailed and live demonstration of conversion of string to integer in Java.

“Is ruby dying”, “Is ruby dead”, “Who cares about ruby “, Ruby is dead “. These are the frequently asked question in the past couple of years whenever one searches about ruby on Google. Well, answer to this no. In fact Ruby on Rails has fragmented into various market segments.  Ruby on Rails is still pretty much active and has nearly 2,420,813 websites built on it. Major websites such as Airbnb, Github, Shopify, and Hulu are based on this framework. There's a huge community backing it up and at the same time working on the framework itself. The major advantage RoR brings to the table is the speed of development, websites that took months to be built and developed with RoR takes merely days. It has continually proved how it has solved problems, improvised itself and made it even better. The fact is that ruby isn't dying but maturing itself overtime.  Ruby on Rails has also been adopted by major companies, and with the latest release of ruby 3.0, it fixes all the shortcomings it had in its previous version.  More reasons why Ruby on Rails won't die : 1.Created for the developers by the developers :  It is fast to write the codes in. Essentially making it at least 30-40 % faster than other languages. It provides flexibility for programmers through gems and usability of the code from other programs. 2.Presence of Large Community:   The presence of the RoR community and contributors is all over the world, who actively contribute and maintain the framework. The community has crafted lots of open source tools and libraries that developers can take advantage of and build functional, cost-effective applications from scratch.  3. Code Quality is the primary focus:   RoR provides a set of common norms and standards of code structure that is approved by the global community. This makes it easy for anyone to understand the code that's written and following a common structure debugging gets easy and as well as reusing the existing code or modifying it becomes an easy task. Lastly, with the help of powerful library developers, don't have to write code from scratch thereby focusing on the quality of code and less on quantity. Many major programming languages are still used or used for many years because :  1. There is a huge amount of old/legacy software that depends on older language and needs to be maintained.  2. The number of users and applications is growing.  3. There’s a host of ecosystems and tools that are built to assist and help with building applications with the framework.  4. The amount of investment the organization or business makes in developing and maintaining the system is simply too huge to be disposed off and start from scratch  Languages that have proven to be useful once shall remain useful in certain ways in the future. For example, COBOL, Fortan, APL, Basic and Pascal are still used as they live on their iteration that is built on the same. Languages vary in their popularity over time but its use depends on how the framework tackles its shortcomings and emerges to be even more powerful. Ruby on Rails is doing the same. With constant updates and immense backing amongst developers and growing code-base isn’t going to let ruby die that easily.   

Blockchain Technology took the world by storm with the introduction of bitcoin and ethereum cryptocurrency. Both these cryptocurrencies wouldn't have been in existence without this technology that was conceptualized by Satoshi Nakamoto in 2008. A lot is going in and around this technology and many are trying to adopt it reap benefits of it.  However, the finance domain was the first one to adopt this technology. And with the growing popularity, it has started to spread in various other domains of the industry.  Here are 10 practical application of blockchain technology :  1.Healthcare :  To track and maintain medical records of patients and as well as medical supplies and inventory of drugs and their supply orders. 2.Smart Contracts :  Smart contracts are those that are digitally enforced the terms of a contract. And since making changes to contract can’t be done without the approval of both sides, there’s a mutual trust maintained. 3.ICO's : ICO stands for Initial Coin Offering. A mechanism for startups to raise funds by offering tokens in exchange for bitcoin. 4.Voting : Since data in blockchain can’t be easily tampered or altered it makes a very secure way of recording votes and resolve the underlying issue of tampered votes. 5.Logistics : In logistics, it can help in pinpoint tracking of the shipment without involving tedious paperwork.  6.Payment Gateways : With crypto exchanges and secure payment process anyone can send and receive from across with worrying about exchange rates and commissions of 3rd party payment services. 7.Data Storage : For data storage blockchain provides great security from getting compromised as compared to cloud storage. Also, it maintains previous iterations of the altered data so just in case you want to revert the changes made are also feasible. 8.Copyrighting Protection :  In the age of digital media, piracy has always been an issue with the media industry. Here blockchain can ensure that artist gets the due royalty and cut down on piracy. 9.Digital ID's :  In the online world maintaining one’s identity has always been crucial. Blockchain ensures that your digital identification isn’t tampered or spoofed. 10.Real estate :  Blockchain is used here to help buyers search for properties to buy or rent and automatically implement the terms of the contract and allow users to pay using digital currencies. Blockchain helps in making the entire process more transparent and quick without the involvement of brokers or other intermediaries. What is makes this technology so lucrative for the industry?  The answer is SECURITY.  The security blockchain provides in real-world applications is currently unmatched by anyone.  How does it do it?  Blockchain offers an immutable decentralized ledger. The data is stored in blocks assigned with cryptographic hashes that are further linked to other blocks. This entire chain is encrypted. To access these blocks or the chain you need to a set of digital keys ie :  1. Private Keys : To grant authorization and encryption over the blocks 2. Public Keys : Address or an identification of the chain.  Any changes made to blocks are stored onto the new block and is linked to its older iteration. Here no alterations can be done to older blocks and new changes made need the authorization of all the members/owners in the chain without each again no changes can be made. To add more security data integrity the blockchain saves a copy of each block on every computer in the network thereby making it more secure and almost impossible to hack into.  Lastly, it tracks and stores all the activity happening on the chain and makes it easy to track back the changes and pinpoint the source of the problem The impact that Blockchain technology brings  1.Building Trust : The transparency of the records helps in establishing trust amongst parties.  2.Data Protection : The data or records stored in blocks are not easily accessible or prone to alteration by anyone. Thereby protecting your sensitive data such as ID and other information. 3.Applications : Various applications of this technology will be replacing the old school process that includes middlemen or intermediaries making it a more time-efficient and transparent process.    Well, there's a lot of good things blockchain brings with, BUT no technology comes with 0 drawbacks and blockchain has it's own.  1.Scalability : At present, Blockchain isn't very friendly when it comes to scaling it up. But this also largely depends on the scale of application, private applications of blockchain see's no problem in terms of performance, the same when applied on a global level can have slack in performance.  2.Storage : As we all know by now that blockchain stores the entire history of chain on all the computers present in the network it leads to having higher latency and requires a huge amount of storage space to function smoothly with progression in time. So smaller portable devices aren't quite apt for the same. Blockchain is still developing, yet being so young, has bought notable impacts in real-world applications. There are few areas where it needs to work on but right now it is ready for limited applications such as providing cross border payment gateway's, digital currencies, logistics, etc.  Many experts say that the future of blockchain will take another 5 years or so to show exactly where it's headed and all of this depends on how current issues are dealt with. But with time it is gaining traction just like how the internet did in its early stages.  Private blockchains will be welcomed by organizations but the public blockchain is still a question. No government will willingly adopt blockchain to make things transparent be in the coming 5 years or the next 15 years.  In conclusion, blockchain will remain popular and with time as business leaders keep digging into and keep innovating, it'll be a much mature technology than it is now. If you are a blockchain developer the future looks bright for you and the demand for the people having the right skills is going surely seeing a rise as the time passes-by.