We know that we have made crucial and noteworthy investments of both time and money in the tools that we are utilizing today. This is the only reason due to which we’ve intended to combine with almost any tool out there that is being used in life.

We have also made possible to maximize all those crucial investments with our testing integration abilities. Testing Whiz permits us to properly manage better and higher connections across the technical design of our application and extend the automation boundaries to higher levels.

Read Also: Top 5 Bug Fixing Tools For Python Developers!

While seeking the most effective and best testing management platforms, a tool that gives us integration driving check automation tools helps you correct and run tests on every day and regular cycle and also change or automate the entire process of managing tests, which can considerably reduce the effective time & efforts. It also tests if they smoothly and perfectly hook with Continuous Integration (CI) tools to modify the build release cycles and deployment automation.

Let’s take a view at some of the best interesting integration that is available to provide powerful automation experience to test engineers. Some of them are listed below:

Read Also: 10 Challenges That Data Science Industry Still Faces!!

1. Continuous Integration & Test Automation

Continuous Integration & Test Automation

Integration gadgets like Jenkins, TeamCity, Bamboo and many more are there which help us to stimulate automation of build deployment & testing on a continuous basis, quickening your regression and agile release cycles. With a combination of these CI tools, our Test Automation tool decreases complexity and can recognize bugs easily and in a very effective way. Automation in the continuous integration cycle guarantees you maximum coverage and performance while lowering the risks and vulnerabilities of human errors.

Read Also: Best Data Science Certification To Boost Your Career Salary

2. Test Case Management System

Test Case Management System

This tool allows you to explore and execute your test activities properly and enable you to manage good and better reports and insights to optimize the testing process. We consolidate with Test Case Management System which involves Quality Center (QC) & TestRail, And with the help of these tools, we are offered multiple test information which helps in improvement of application that includes handling of bugs, test progress, project tasks, etc. it also assures high-level cooperation throughout the automation process.

Read Also: 10 Free Courses to Learn Python in Depth

3. Automated Defect Creation in Bug/Defect Tracking Tools


“Better the bug finding tool, better is the quality of product that”. Integration for these bug finding tools report bugs as and when they are anticipated during the testing process. All these reports help to recognize, track and fix bugs according to the issues to keep up with the product development process and regression testing cycles, some of the popular integrations are Mantis, Jira, and FogBugz.

Read Also: What is Deep Learning and How Its Changing Our Future?

4. Database Integrations

Database Integrations

Database Integration sanction you to test database properly, form controls & their arrangement and ensure that you validate the entire application from the core and workflow and not just the front-end. Integration with multiple databases helps you monitor data integrity and can even assign a database to load test data during database test automation. We integrate with these databases that include: MS SQL Server, My SQL, Oracle, Teradata Beta, Hadoop Beta, IBM DB2 and PostgreSQL.

Read Also: Best Websites For Learning Computer Science Topics

5. Cloud-Based Executions

Cloud-Based Executions

Management to test the environments and functionality can be really cost-effective and time-consuming. These cloud-based environments can be like BrowserStack and SauceLabs which offers you automated browser testing. So that testing can be done easily, in a proper manner in operating systems and browsers.

Read Also: This is How You Can Become An Ethical Hacker?

Python is becoming one of the most popular languages that let you work quickly and change the features according to your requirements more efficiently. Coding is definitely a time-taking thing and no one can assure that he/she can write error-free code. Experienced developers also spend a good amount of time in fixing the bug.

Here are some best bug fixing tools for python developers. These will help you in fixing bugs while coding and also show you an insight of work and status that how you are doing.

Read Also: 10 Challenges That Data Science Industry Still Faces!!

1. Trac

Bug Fixing Tools for Python

It is one of the best tools for developers. It’s an open-source tool which comes with a lot of useful features. It’s not only a bug-fixing tool but also helps you to organize your projects. It will display all your projects in order to provide better acquisition.

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Trac is actually a multitasking bug-fixing software for development of projects. Trac also provides an interface between Subversion and Git with useful informing facilities. On Trac, you can create your own links as well as build references between bugs, changesets, files, wiki pages, etc. It also allows you to issue descriptions and messages. It is available for Linux, Windows, etc.

You can visit their site here.

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2. Sentry

Bug Fixing Tools for Python

This is another bug fixing tool for python developers that let them find and repair bugs in real-time, it is also an open-source tool. Sentry supports python as well as some other languages such as Ruby, JavaScript, Django, iOS, etc.

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It has a very convenient framework, platform, and language, which you can easily integrate it into your applications. Sentry allows you to see variables in the stack for errors, just like we do in our development environment. You can review more deeply into the runtime for additional data. It also has an option to filter and combine Python executions to reduce the noise. Sentry is trusted most of the famous companies such as Uber, PayPal, Reddit, Microsoft etc.

You can visit their site here.

Read Also: 10 Free Courses to Learn Python in Depth.

3. Airbrake

Bug Fixing Tools for Python

This is another amazing tool for tracking errors and bug fixing in Python. This is a tool which keeps reporting and reviewing your code, it also captures exceptions and informs you before the users are affected. Airbrake allows you to receive alerts either on Jira, Slack, Github or via email.

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Airbrake is very easy to install and can be approached via mobile- can be optimized through the web app. Not only Python, but it also supports famous languages like PHP, Ruby, .NET, JavaScript and many more. It also has some cool features in it to improve the efficiency of the entire team. Airbrake allows you to prioritize, collaborate, etc with its custom workflow integrations.

You can visit their site here.

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4. Rollbar

Bug Fixing Tools for Python

It’s a great tool with great error tracking and the bug-fixing ability for python developer and for people who are looking for complete monitoring of their product or service after deployment. Rollbar will inform you by sending you notifications instantly after the error has occurred.

Read Also: What is Linux? Why Linux is better than Windows?

The good thing about this tool is that it combines similar errors together by using its technology. It ensures that you receive all the required details so that you can change the impact and assign priority.

It also supports languages such as Django, Ruby, JavaScript, Android, Clojure, etc. It is one of the most trusted tools by firms like Uber, Salesforce, Heroku, etc.

You can visit their site here.

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5. Raygun

Bug Fixing Tools for Python

It is also a good bug fixing and management tool that keeps track of errors coming from software. It is very simple, easy and helps you discover and resolve issues users experience. It also assists languages and platforms like Python, iOS, Android, PHP, .NET, Java, etc.

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You can simply add this tool into your production environments and find out bugs and every other performance issues which negatively affecting your users.

You can visit their site here.


These were some of the best bug fixing and management tools you can use for your projects related to python. All the tools are perfect for individuals and for small, medium and large-sized business.

Most of the companies are utilizing data and analytics for attaining tasks that were earlier thought impossible given the size and uneven distribution. It has become an important part of the overall working of most of the industries.

The adoption of data analytics has been increased, it comes due to its own challenges. Keeping with the data science forefront various companies, it has helped in solving various problems whether it is about finding the talent or solving challenges that are revolving around, hidden security risk and vulnerabilities.

In this article, we will talk about 10 such challenges that the data science companies are facing despite the breathtaking growth that has been witnessed with its adoption over the years.

Read Also: Best Data Science Certification To Boost Your Career Salary

1. Hiring People With Relevant Skills:


This is the most faced challenge as most of the industries are struggling with the talent shortage. Many data analysts believe that actual challenge faced by Indian analytics industry is the lack of skills within the workforce. There are a significant amount of professionals that are not equipped with the relevant skills according to the business requirements. There is a need for people who can execute complex data science projects, having the right analytics skills and business domain knowledge.

Industries today are still grappling to build the right team while assuring the right infrastructure of hardware and software implementation. Lack of talent is there in the people who have the right mix of business and programming knowledge.

Read Also: 10 Free Courses to Learn Python in Depth

2. Finding Right Data And Sizing:

Data Sizing


Having  ‘appropriate data’ is a common problem faced by industries and plays an important role in building the appropriate model. The volume and velocity of data are large enough, The biggest challenge is to make sense of it all to drive favourable decisions. It is crucial to capture and correct data to make a strong and perfect analytical model.

Industries need to know if they are equipped to make sense of large data and whether all the data points are going to be utilized. It is crucial to know what is critical and what needs to be measured in order to make organizational decisions. A lot of efforts, time and money are spent on storing and collecting data without determining how data will eventually be consumed and by whom.

 Read Also: What is Deep Learning and How It’s Changing Our Future?

3. Consolidation of information:


All companies have a huge amount of data that is mostly scattered. In such cases, information remains one of the major challenges as most organizations struggle with internal data systems. The companies are struggling with collecting data into a single preview to reap maximum benefits. It is crucial to have a proper view of data while enhancing the information with analytics-infused data elements.

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4. Teaching People About What Data Can Do For You:


Data science has created many opportunities for young talents. Most of the data science leaders believe that it is the major challenges to tell people about what data can do for us. They have to adapt to ask the proper questions so that data can do things beyond counting, reporting, and aggregating numbers.

It is the biggest challenge to convince companies to move to a data-dedicated decision-making process. To overcome through this it is crucial to know the right use, highlighting the impact data analytics can have on their business.

 Read Also: What is Data Security and Data Privacy and Why you should care about it?

5. Identifying The Right Area To Invest:

Areas to invest

Most of the service providers do not consider it as an aspect, but it is crucial to know and engage main stakeholders and ensure that the right commitment is obtained from the side while defining analytics roadmap for them. This is important to have a project move in the right direction and deliver the right business impact.

Read Also: Best Websites For Learning Computer Science Topics

6. Right Storytelling:

Right Storytelling

Analytics is about dealing with tough and complex models that could be difficult for end users to understand. It requires great story narrating skills for a data analyst and team members to able to make the data and make it easy, understandable and to be able to finish how they can work together to be the best for Artificial Intelligence models at hand.

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7. Building Data Science Models:


Data analysts team that is interested in creating the data science models but they might not be necessarily solving business problems. The whole process of acquisition of data science solutions to execution can be quite difficult and it is important to create the models that can solve the challenges in real-time. People should have a strong problem-solving capability to make this happen and again directs back to the point of recruiting the right talent.

Read Also: Best Data Science Certification To Boost Your Career Salary

8. Recognizing Appropriate Analytics:


Industries are still evolving, many data science experts believe that there are not a lot of use cases that actually exist out there. It has become difficult to identify correct data for the appropriate analytics use case. It has become tough for analysts to do all the things by themselves such as inspect the content and convince people to adopt it, especially if it is being done for the first time in an organization.

 Read Also: How You Can Protect Your Data From Hackers!

9. Agility:


The data science functions are build in a way that allows limited interaction with the end business user. Analysts believe that for data science to be generating more meaningful ways to support a business, it needs to be more agile and in sync with business during the decision-making process.

Read Also: The Realm of Mathematics And Machine Learning

10. Knowing The Importance of Data Security:

Data Security

Data Science is all about managing a big amount of data and ensuring the security of data that companies are dealing with remains a big challenge. Industries need to work on privacy and making data as safe as possible from any wrong use.

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Best Data Science Certification To Boost Your Career Salary

1. Apache Hadoop

This certification is an open source project which allows fast processing and insights into huge volumes of structured and unstructured data. Hadoop has appeared as the main force behind all extension of data science, with spin-offs in a BI environment. Big data is a powerful platform that offers the Hadoop expert the capability to grasp the main elements of the Hadoop stack for deep and fast analytics. Hadoop framework learning is important and beneficial, together with the underpinning programming models, such as the Map Reduce, Hive, Pig, and HBase is also critical in earning analytical brownies in big data analytics.

Read Also: Top 10 Hot Artificial Intelligence Technologies.

2. Apache Spark


Expertising in this course is beneficial, In-memory computing permits better-performance algorithms for faster processing. The potential of all the process insights in real- time with sophisticated simulations, there has been increased adoption of this tool by big data practitioners. Conquering and mastering the Apache Spark is considered as a massive challenge for many data scientists, the experts who are having these skills in Spark is sure to command a salary on his terms.

Read Also: 10 Most Popular Machine Learning GitHub Repositories.

3. Machine Learning

Machine Learning

The course of Machine learning is a part of Artificial Intelligence technology it powers big data scientists by learning new rules for improved analytics. Learning ML algorithms and rule defining for spotting patterns is a popular demand in sectors like banking, finance, and trading. The capability to construct predictive analysis in a big data engine for personalized customer experience is a highly sought-after skill.

Read Also: The Realm of Mathematics And Machine Learning.

4. Data Mining

Data Mining

Data mining is a process or technique that integrates structured and unstructured data from multiple channels for big data analytics. It has the potential to pull out any data for a 360-degree view of the customer. If you have relevant skills in data mining, you can bring value to a business.

Read Also: What is Deep Learning and How It’s Changing Our Future?

5. NoSQL


NoSQL powered databases are the best and continue to be the rage. Having NoSQL database skills can increase your chances of getting good salaries, its skill includes power big data analytics from huge data, with quick iterations and coding. It is very much advantageous over the RDBMS which has pushed NoSQL to the forefront. The architecture of the NoSQL database allows high-performance big data analytics at massive scale, making it almost indispensable in recent times. So the data science experts armed with the knowledge of one or more NoSQL databases can certainly boost his salary.

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To have the best salary in data analytics job, single skill development is not enough. Every skill has its own merits. These skills can really help you to boost up your salary in data analyst field. All these above four skills can help you grab a good Data Scientist position. The stipend and career growth in data analytics have never been better! So it’s your chance to go ahead and arm yourself with the necessary technical skills. Learn big data as much as you can, get certification and online training programmes, together with your studies. Get trained by experts on the most relevant big data science tools that best-fit your career opportunities. Increase your skills in a data analytics environment with appropriate weekend programmes, and domain-based management skills for that salary-boosting.

Python is currently on top of the world #1 programming language and its advantage is that it is bringing people into the programming world. Nowadays, you might have seen more people learning Python than any other languages. People are learning Python to explore some awesome Data Science and Machine learning libraries provided by Python. Few people are learning Python for web development and there are still many developers who are learning Python for scripting and automating trivial tasks. Python is very highly versatile.

It has just become a tool, it also allows you to traverse areas like Data Science and Machine learning, which is not easily available on any other mainstream programming language like C++ or JavaScript.

These courses not only contains basic Python programming courses but also OOP in Python and a Data Science with Python course, mainly for a developer who is learning Python for Data Science and Machine learning.

  1. Python Core And Advanced


This is a complex course to learn,  we should thanks to the instructor for keeping it free.

This Python course will help you learn how to install Python, execute your first Python program, logic, programming constructs, python syntax, command line python, and many more advanced concepts.

This course is 8 hours long and teaches topics like regular expression, reading and writing files using files API, building interfaces which are not taught in free courses.

It is a perfect course for beginners to learn Python in details and for free.

  1. Hands-on Python Introduction for Beginners.

Python 3.6

This course motive is to learn Python Programming and as the name suggests it focuses more on hands-on training and for beginners especially than anything else.

This course provides a beginner programmer face while starting with Python. It teaches you how to install Python and write your first program, set up your development environment.

It slowly builds your brain on key Python programming concepts likes Variables and Data types, Numbers, Operators, String, List, Tuple, Dictionary, Loops, Functions, and Exception handling.

3. Deep Learning Preconditions: The Numpy Stack in Python

Deep Learning

This course provides programmer friends who are focused on data science and machine learning using Python.

You will find some of the exciting Python libraries like SciPy, Pandas and Matplotlib stack, which provides a concrete base to explore further on.

This course has also hands-on Data Science and Deep Learning. You will also know about libraries but also understand the pros and cons of various machine learning models.

Read Also: Best Websites For Learning Computer Science Topics.

  1. Learn Programming with Python in 10 Steps


This course will not only help you learn about Python programming concepts but also learns about tools and IDEs like PyCharm and Python Shell.

You will also know how to solve Python topics like data structures, oop concepts, exception handling, file handling, and also develop an awesome python project.

The main Portion of this course will teach you how to think as a Python Programmer. This course is free at this time, the coordinator can convert this to the paid course, so go and grab it fast.

  1. Learn Python 3.6 for Total Beginners

Python 3.6

If you want to learn a new programming language by solving coding problems then this course is best for you.

The good thing about the course is that it will teach you Python but also how to use Jupyter Notebook, and Python IDE. You learn how to install and use Python IDE.

The program covers coding basics like operators, variables,  loops, functions, handling errors, and common String operations like a slice, split, join and formatting.

It explains Python in good details including Lists and Range, Tuples, Dictionaries and then you have to perform the exercises to test your knowledge you have learned.

6.The Pillars of OOP in Python 3 for Beginners


This Python course from Udemy focuses on teaching object-oriented programming using Python 3.

This course will help you learn about essential object-oriented concepts like Class and Objects, Attributes and Methods, Encapsulation and Polymorphism.

At last, you will know how to build a final project to simulate a system using object-oriented design technique.

Read Also: Say Hello to Programming.


  1. Python 3 Bootcamp for Novice: Start Programming for Beginners


This Python course helps you learn Bootcamp style its a free course for you.

This is simple, and straight-forward course for beginning on the Python 3 programming language. It doesn’t matter if you know to write a program or not, this course assumes no experience with programming.

  1. Try Django 1.11 // Python Web Development


Django is a popular library in Python for web development. Python is used for developing a web application, in which Django is very beneficial.

You will know the fundamentals of Django 1.11. Then you can start with web development basics like HTML.  Also, you can move on to more advanced concepts like forms, views, models and more.

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  1. Introduction to Python Programming

Python Programming

It is a good course for beginners. You will know how to download and install Python which is a hard task for beginners and then creating your first program.

This course helps you to know the basics about Python programming language like syntax, operators, functions, loops, class, object, and some standard Python data types etc.

The course is trusted by students and Instructor. A big thanks to Avinash for keeping this course free.

  1. Learn Python: Build a Virtual Assistant

Python Tut

This course will help you build a virtual assistant for your computer. You will know how to get data from Wikipedia, as well as create a GUI. Learn Python course will help you know and add something fun to your portfolio and good practice for python. This was all about the 10 best free Python courses for coders and developers. Anyone who is keen to learn Python for data science, machine learning, deep learning, can get benefit from these free courses.



The idea to develop a truly intelligent computer: one that might understand human language and then can make its inferences and decisions on its own.
It will become obvious that such an effort would require no less than Google-scale data and computing power.
Deep learning copies the activity of neurons in the neocortex, 80 percent of the brain where thinking occurs. It learns, in a very real sense, to understand patterns in digital representations of sounds, images, and other types of data.
The fundamental idea that software can process is the neocortex’s large array of neurons in an artificial “neural network” which is decades old, and it has led to as many disappointments as breakthroughs. But due to improvements in mathematical formulas and increasingly powerful computers scientists can create layers of virtual neurons very easily.

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Building a Brain

Deep Learning

There have been many competing approaches to these challenges. One of them is to feed devices with information and rules about the world. It took lots of time and still left the system unable to deal with debatable data it was limited to controlled applications such as phone menu systems which ask you to make queries by saying specific words.
AI research, looked favorable because they attempt to simulate the way the brain works, though in a simplified manner. A program is a set of virtual neurons and then it is assigned in random numerical values. These weights determine how each simulated neuron responds.
Coders would develop a neural network to detect an object by attacking the network with digitized versions of images containing those objects or sound waves containing those phonemes. If the network isn’t able to accurately understand a particular pattern then an algorithm would adjust the weights.

The goal of this training is to get the network to continuously recognize the patterns in speech or sets of images that we humans can understand. This is the same way a child learns by noticing the details of an object.
The fact that stunned some AI experts was though, was the amount of improvement in image recognition. It was challenging for most humans. The accuracy increased above 50 percent when the software was asked to sort the images into 1,000 more general categories.

Read Also: 10 Most Popular Machine Learning GitHub Repositories.

Big Data

BIg Data

Giving training to the layers of virtual neurons in the experiment took around 16,000 computer processors, the kind of computing infrastructure that Google has made for its search engine and other services is marvelous. About 80% of the advances in AI can be credited to the availability of more computer powers.
Deep learning has changed the way of voice search on our devices. The layers of neurons lead to more precise training on many varieties of a sound, the device can easily recognize sound more reliably, especially in noisy environments such as on metro platforms. It is easy to understand what was actually uttered, the result it returns is accurate as well.
Everyone doesn’t think that deep learning can move AI toward something rivalry human intelligence. Some people say deep learning and AI, in general, ignore too much of the brain’s intelligence in favor of brute-force computing.

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What’s Next?


Google has already started thinking about future applications, the prospects are fascinating. It is a better image search which would help YouTube, for instance. It’s also favorable that more complicated image recognition could make Google’s self-driven cars much better. There are search and ads that underwrite it. There has been betterment from any technology that’s good and faster at recognizing what people are really looking for, maybe even before they realize it.

Everyone wants to have the exact meaning of words, phrases, and sentences that always trip up computers. In turn, it will require a more complicated way to graph the syntax of sentences. Google has already started using these kinds of analysis to improve grammar in translations. Language understanding will require devices to grasp what we humans think of as common-sense meaning. Finally, People plans to apply algorithms to help computers deal with the “boundaries in language.”

Self Driving Car

Microsoft also has there promising research on likely uses of deep learning in machine vision. It also has visualized personal sensors that deep neural networks could use to predict medical problems. Sensors might also help a city it might feed deep-learning systems that could predict where traffic jams might occur.

It is a field that attempts something interpreting the human brain, it’s certain that only one technique won’t solve all the problems. But for now, it is the one which is leading the way in artificial intelligence. Deep learning is a really powerful metaphor for learning about the challenges of the world.

Read Also: Best Websites For Learning Computer Science Topics.

Linux can be an extraordinarily complex for new users. It’s not Linux which brings this complexity. It’s the different Linux distributions that cause this. Not getting wistful, many users didn’t even know what to expect. But it is an upstream swim for everyone initially.

Not knowing where to start can be a problem. Especially for users who do not have any concept of running new software on their PC in place of Windows. Linux can be used in various ways and it is more than an OS. A software where everybody grows together.

Read Also: Best Websites For Learning Computer Science Topics

Here are our top 5 Linux Distros:-

1. Ubuntu


If you google Linux on the internet, you’ll probably get Ubuntu. Ubuntu is the leading and one of the most common Linux distributions. It is the best and probably the easiest path to start your Linux journey.

It has been recommended Linux is for human beings. Now, it is because Ubuntu has made a lot of effort on usability. It does not require you to be the technically perfect person for you to use it. This is the plus points that uplift the Ubuntu to where it is now.

Ubuntu provides a convenient installation method. While installing, it speaks the English language. You can try Ubuntu before going through the installation procedure. The installation provides simple options for you:

  • Install Ubuntu removing and the older OS
  • Install the Ubuntu along with the existing OS
  • Configure everything properly.

There is no installation of the driver on Ubuntu as it comes with a hardware detector which detects, downloads and installs optimal drivers for your PC. It’s highly beginner friendly.


2. Linux Mint Cinnamon

Linux Mint

Linux Mint is the number one Linux on the Users list. Linux Mint is my personal favourites. It is very graceful and provides computing experience.

Linux Mint attribute the Cinnamon desktop environment. Linux users who are new to this process of familiarizing themselves with Linux software will find Cinnamon very useful. All the software is attainable under some categories. New users who don’t know the Linux software, this is a huge bonus.

It is a fast OS. Linux Mint is built upon the Ubuntu base. Ubuntu software pushes software for general use only after substantial testing. This means users did not have to deal with any unexpected crash and errors that some new software might have.

Windows 7 users who are into Microsoft will find Linux Mint lovable. Linux Mint desktop is somewhat similar to Windows 7 desktop.
I personally suggest Linux Mint to someone who is new to Linux world as Linux Mint does impress users enough for them to accept it.

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3. Zorin OS

Zorin OS

A majority of users are Windows friendly. A huge amount of methods has been fixed in our tough memory. For example, the lower left of the corner of the screen (Start) every time if we want to launch any application. So, if we could find anything that pleases us on Linux, it’s half a battle won.

Zorin OS is also an Ubuntu-based Linux entirely made for Windows friendly. Although every Linux is usable for everybody, some people may tend to be resistant when the desktop looks too alien. Zorin OS pass this obstacle because of its similarities with Windows.

Zorin OS comes with extraordinary and impressive themes option called the ‘Zorin look changer’. It offers some heavy upgrading options with presets to make your OS look like as you want. You’re going to feel home.

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Elementory OS

As we have taken look at Linux for Windows users and got knowledge about them, let’s change something for MacOS users also. Elementary OS has risen to fame very quickly and now is always included in of top list of Linux, all thanks to its attractive essence. Inspired by MacOS looks.

Elementary OS is also Ubuntu-based OS which means that the operating system itself is unquestionably stable and environmentally friendly. You can easily notice the resemblance to the MacOS desktop. It is an advantage for MacOS users to switch to Linux as they will be comfortable with the desktop.

The menu can be customized according to user preferences. The OS is zero intrusive so anyone can really focus on their work. It comes with a very small number of installed applications. But it got everything you need to install. For any other software, it provides an AppCenter. Everything is in a sorted manner.


5. Manjaro Linux

Manjaro OS

So, we are up to our last option of being a Linux user. This Linux is considered for experts-only Linux because of its complex installation procedure. Manajro Linux has a common origin with Arch Linux. But they differ mostly in everything else.

Manajro Linux has a beginner friendly installation method. A lot of things are self-driven like driver installation using ‘Hardware detection System’. It hugely neutralizes the hardware driver hassles that torments another Linux.

It contains its own software storage which maintains the latest of software. This is one of the major differences between Arch and Manjaro. Manjaro slows down package releases to make sure that they are absolutely right and no regression will be caused.

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To install any of the above 5 operating systems, you need to use a bootable USB stick.

What Are Your choices for the best Linux for beginners?

Linux may come with a learning curve, but that’s not something anyone will ever regret. Go and get an ISO and check out these amazing Linux Software.

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Everyone struggles to get knowledge or information related to Computer Science topics, As it is not easy to only learn with the help of books. Just need to explore the internet. There are lots of online courses that we can use to improve our knowledge and sharpen our skills in this subject.

Here are some of the best websites for learning computer science topics:

1. Tutorials Point

Tutorials Point

Tutorials point is a tutorial website for the ambitious computer science student. Provides comprehensive and interesting tutorials on various programming languages. It is best for someone who is going to get into the Computer Science field and would like to learn some coding. The website will provide you more than you need.

It also provides a friendly environment where you can edit program, compile and run them. Some of the coding languages that you can learn from this website include HTML 5, Python, PHP, Java, C and C++. You can visit their website here.

Read Also: Top 10 Hot Artificial Intelligence (AI) Technologies

2. Study Tonight

Study Tonight

It is an online learning website that teaches different technical subjects and programming. It is not like other popular online tutorials, it digs deeper into the important topics of computer science. Programming languages that you can learn from this website are C Programming, Java, CSS, SQL, computer network, operating system, Python, Game development with Unity, JSP, Apache Cordova, C++, and many more.
Study tonight provides tutorials in a simple and best manner which can be easily understood by anyone. This site also offers tests which you can use to know your understanding. You can visit their website here.

Read Also: How You Can Protect Your Data From Hackers!

3. Geeks For Geeks


Geeks for Geeks is an online coding website that is used to prepare students who are going for interviews related to computer science. This site offers each and every kind of solutions starting from the easy ones to more technical ones. Geeks for Geeks also have a functional and interactive IDE that we can use to modify and test our program. Some of the programming languages that are available on the website are C, Java, and Python. You can visit their website here.

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4. W3Schools


W3Schools is an ideal website for students who want to learn various types of programming languages such as PHP, PYTHON, SQL, ASP, CSS, and JavaScript. This site has tutorials of these programming languages and they are written in a manner which is easy to understand language. W3School also offers to test your skills where you can test some of the programs that you have written. You can visit their website here.

Read Also: Google I/O Developers Conference Dates are Finally Here.

5. Quora


We can use Quora as a question and answer website. This website provides solutions to each and every question that you have asked even about life, including the ones about Computer Science.
Quora is a reliable resource for computer science students it’s a large community. This site contains some of the best programmers who are best in different programming languages. They can provide you with concrete answers to any questions that you may be having. You can visit their website here.


6. Stack Overflow


Stack Overflow is the website of developers. This community brings together millions of coders or developer who come together to share there different views and issues, while at the same time they teach each other. This site has most of the answers to any programming language issue that you have encountered.
If you have written any program and you got stuck, then you just have to rush to the Stack Overflow Website. You will be provided with the solution on how to go about the problem. You can visit their website here.

Read Also: What Is Blockchain? A Little Guide For Beginners!!

7. Computer Hope

Computer Hope

Computer Hope is a free website for all the problems related to the computer. This website covers both the aspect, hardware and software of the computer. You can search out related to computers even if you have an issue related to the drivers, database or steps for troubleshooting a problem in your computer. It provides you with tips on various problems that you are facing or affecting a computer. You can visit their website here.

Read Also: Other Hackers apart from White Hat and Black Hat hackers?

8. JavaTPoint


It provides videos on various issues that are related to modern technology. JavaTPoint has tutorials on programming languages which includes the new ones such as Kotlin. It also has the latest developments such as Blockchain and AI.
This Website also gives technical solutions for Computer Science interviews. You can visit their website here.

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9. Khan Academy

Khan Academy

This website offers courses on a wide range of subjects especially Math, Physics, and Science. Khan Academy is also rich with computer science videos and tutorials which are offered in the form of YouTube videos. You can visit their website here.

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10. Youtube


YouTube is a giant video platform that contains all types of video. As a student, you can use YouTube as your learning tool. We can use this site search to get tutorials about computer science and programming.
When it comes to programming, you will never get grounded. There are many resources at your disposal. You only need to type and look for what you want and you will get instant answers. You can visit their website here.

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Artificial intelligence (AI) is the activity of human intelligence processes by machines, especially by computer systems. These processes include learning (the addition of information and using information in a productive manner) and self-correction. Particular execution of AI includes expert systems, speech recognition, and machine vision

AI can be categorized as weak or strong. Weak AI, also known as limited AI, is an AI system that is designed and instructed for a particular task. Virtual personal assistants, such as Google Assistant, are an example of weak AI. Strong AI, also known as artificial general intelligence, is an AI system with generalized human concerned abilities. When presented with an unfamiliar task, a strong AI is able to find a solution without human intervention.




In this world of digital revolutions data is flowing in trillions and billions, the advancement in Artificial Intelligence has proved to be the savior. The scale at which people are producing data is humungous, but to tap data and convert it into a piece of meaningful information we need to feed them into a machine and analyze it. Undoubtedly, it’s going to change the fate of how companies and countries will take decisions. Our systems are used for analyzing petabytes of information in seconds, so Artificial Intelligence techniques, when enhanced with right kind of data, can give a distinct advantage for sectors like Science, Healthcare, Banking, Manufacturing and many more. It has endless applications.




It is important to be familiar with basic AI terms and approaches. This is true and the best way to prime yourself for AI would be starting with some free books available on Google. Peter Norvig and Stuart J. Russell’s Artificial Intelligence: A Modern Approach, this is one of the good books to start AI. This book deals with not just the basic AI concepts and algorithms (expert systems, knowledge representation, etc.) but also with the fundamental of mathematics.  For those who are interested in Deep Learning, here’s a book by Ian Goodfellow, Yoshua Bengio and Aaron Courville. Check out this free book also, on Logic for Computer Science which explains the mathematical logic for understanding computer science and algorithmic methods for solving questions. These books can be really helpful in making your base in AI.

You should have a good maths to expertise in AI, as maths is fundamental in solving the problem of AI. You should have command on Calculus and Linear Algebra. AI devotee argues that most machine learning techniques can be reduced to Linear Algebra and Calculus. To get deeper into AI from a research perspective, you’ll probably want to get into all the areas of mathematics and more. But the above should give you an idea of the general study that is probably most important before developing proper AI.


Learn with Google AI – This is a fresh project which was launched by Google to let the general understanding that what AI is and how it works. Although the resource is growing slowly, it already has a machine learning (ML) course for beginners that includes Google’s TensorFlow library. These courses will help those who know nothing or a little bit about AI, covering the basics of machine learning, introducing TensorFlow and explaining the crucial principles of designing a neural network.

You can reach out to online courses that are available on sites like Udemy, those online free courses can help you a lot to start with Artificial Intelligence (AI). When you get to ease into AI and become little expertise in it then you can go for paid courses which can be really helpful in building your own AI.

If there’s one key challenge to learning about Artificial Intelligence, it’s not that raw materials and tools aren’t readily available. It’s that there are so many of them available on the internet. My objective has been to give you start basic AI learning which will be really helpful in the future for you. Happy Learning!

See Also: The Realm of Mathematics And Machine Learning

Artificial Intelligence is changing the way we use to think of technology. It is changing the various aspects of our daily life at a very fast rate. The market for artificial intelligence (AI) technologies is developing. Beyond the exposure and the intense media attention, the countless start-ups and the internet giants competing to acquire them, there is a significant growth in investment and adoption by enterprises.

Recently a study performed by Forrester Research predicted an increase of around 300% in investment in AI.

But that’s not all, IDC estimated that the artificial intelligence (AI) market will grow rapidly from $8 billion dollars to more than $47 billion by 2020.

1. Natural Language Generation


Saying or writing the right words in the right sequence to convey your message that can be easily understood by the listener or writer, it can be a tricky business. For a machine, which processes information in an entirely different way than the human brain does, it can be tricky.

Solving this problem has been the key focus of the burgeoning field of Natural Language Generation (NLG) for many years beyond counting. Natural language generation, a field that has made great steps. It has begun to manifest in many areas of our personal lives. It is recently being used in customer service to provide reports and market summaries.

Sample vendors: Automated Insights, Cambridge Semantics, Digital Reasoning, Narrative Science, SAS.


2. Speech recognition


Transformation of human speech into a format useful for computer applications. It is currently being used in interactive voice response systems and mobile applications. Every day, the number of systems incorporate the transformation of human language into useful formats suitable for computers.

Companies which are offering speech recognition services include Nuance Communications, OpenText and Verint Systems.


3. Machine Learning Platforms


These days, computers can also learn something, and they are incredibly intelligent!

Machine learning is an aspect of computer science and a branch of artificial intelligence. Its goal is to develop techniques that allow computers and devices to learn.

By providing algorithms, APIs (application programming interface), huge data, applications, and other machines. Machine learning platforms are gaining more and more attraction every day.

They are currently being used in a wide range of companies applications, mainly for predicting or classification. Companies focused on machine learning include Amazon, Google, Microsoft and SAS


4. Virtual Agents

Virtual Agents

“The current favorite of media,” from simple chatbots to advanced quality systems that can affiliate with humans. Virtual Agents (VI) are experiencing fabulous popularity in interest, and along with that, a rapid advance in innovation and technology.

Currently used in customer service and support. Some of the companies that provide chatbots (virtual agents) include Amazon, Apple, Assist AI, Google, IBM, Microsoft.


5. Decision Management


Engines that add new rules and logic into AI systems and used for initial setup and ongoing maintenance.

It is used in a wide variety of companies applications, helping in performing automated decision-making. Some of the enterprises that provide this are Advanced Systems Concepts, Informatica, Pegasystems.

6. AI-Optimized Hardware


Enterprises are investing heavily in Machine Learning (ML)/Artificial Intelligence (AI) with hardware designs calculated to greatly accelerate the next generation of applications. Graphics processing units (GPU) and architected to efficiently run AI-oriented computational jobs.

Some of the enterprises focused on AI-Optimized Hardware includes Google, IBM, Intel, Nvidia.


7. Deep Learning Platforms


Deep learning is the rigorously growing field and the new big drift in machine learning. A set of algorithms that use AI neural networks to learn in multi-levels, similar to different levels of abstraction.

There are various applications of deep learning some of them are automatic speech recognition, image recognition, NLP, and prediction of almost any entity that can be sensed & digitized.

Deep learning programme services providers include Deep Instinct, Ersatz Labs, Peltarion, Saffron Technology, Sentient Technologies.


8. Robotic Process Automation


Robotic processes automation is possible thanks to scripts and practice that imitate and automate human tasks to support corporate processes. It is being used in special situations where it’s too expensive to hire humans for a specific job or task.

We need to know that artificial intelligence is not meant to replace humans, but to complement their abilities and support human talent.

Some of the companies that focus on this include Pegasystems, Blue Prism, UiPath, WorkFusion.


9. Text Analytics and NLP (Natural Language Processing)


Natural language processing (NLP) is concerned with the interaction between devices and human (natural) languages. This technology uses text analysis to understand the structure of the sentences, as well as their meaning through statistical methods and machine learning.

Text analytics and NLP are currently used for security systems and fraud detection systems.

It is also being used by a huge formation of automated assistants and apps to extract unstructured data.

Some of the suppliers of these technologies include Basis Technology, Expert System, Indico, Lexalytics, Sinequa, and Synapsify.

10. Biometrics


This deals with the identification and measurement of physical aspects of the body’s structure and form and human behavior.

It helps in more natural interactions between humans and devices, including interactions related to touch, image, speech recognition.

This is currently mostly being used for market researches. The Suppliers of these technologies include 3VR, Agnitio, FaceFirst, and Sensory.

Now you know that it’s time to take the next step.

I would advise you all to take the steps before your competitors do!

Being at the front doesn’t mean to make clever decisions, it means adapting to the latest technologies.

Privacy is what sets us apart from everyone. Nowadays, in a technical world, it’s very important to secure our data from unauthorized access, such as hackers. Hackers are constantly seeking additional unsuspecting victims, making a number of incidences of identity theft, as more and more people are getting into the web created by them. Data can be easily exploited by them.

Hacking is a term which is finding a weakness in someone’s software or networks with a purpose to exploit or to gain unauthorized access to secured data and information. Devices are an important part of our activities. They have become important to run a business, in today’s times. Having isolated computer systems is not sufficient; you need to have a secure network connection to exchange information with other sources. They can sell our important data at a very good prize.

To secure our data from hackers we should take necessary precautions. We can secure our data by finding vulnerabilities, threat, and risk related to it.

Update your Operating System:

Update Software


The very first step is to regularly update your devices. As soon as an update is ready to be downloaded install it on your devices because Un-updated phones and computers become vulnerable to hacking, so you can make your device more secured by regularly updating it. You can constantly check your device settings for new updates. You must update your apps as well so that no one can bypass through them.

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Install Antivirus Software:


You should always install trustworthy and reliable device protection apps that provide complete malware security. It is important to have security software on your devices to protect it from hackers, viruses, and worms. The hackers generally send you emails which contain viruses, worms or trojans through which they can gain access to your device. So, with the help of advanced security software, you can protect your device from such attacks. Some best antivirus software’s for your device are Norton Antivirus, MacAfee Antivirus, Quick Heal Antivirus etc.

Read AlsoWhat is Data Security and Data Privacy and Why you should care about it?

Protect Password:

Password Protect


To improve your device security, it is important to password lock your device carefully. Keep a password that provides you with good strength and which is easy to remember. You can also encrypt your phone to make it more secure. You can choose a personalized PIN or an alphabetical-numeric password for your device. Nowadays various companies are providing fingerprint password and Iris scanner password which are difficult to hack.

Read AlsoGoogle Accused of Protecting Father of Android For This!!

Trustworthy Apps:


It is suggested to you to only download apps or software from reputed sites such as Apple’s App Store and Play Store. Do a secure scan of an app which you have downloaded so that you get notified if there is any malware. First, you should visit a website to get the authentic review about the app, you are planning to install. After that, you can download a new app or any software.

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Exercise Good Browsing Habits:

Secure Icon

While the benefits of the Internet are incalculable, the risks for the unwary are high. Ensure the Website that you Visit is Secure. Use “https://” rather than “http://” in your searches. You should have a good firewall to Block Pop-Up Ads. Pop-ups are a favourite avenue for hackers to gain access to computers. Fortunately, infecting a computer requires some action by the user to install the malware, such as clicking a link, downloading software. Never visit any unsecured Website.

Read AlsoHow Facebook, Instagram and WhatsApp earn money.

Unsecured Wi-Fi Hacking:

Secure Wifi

The unsecured wi-fi connections are open for everyone. Therefore, always use a secured connection for your device. You can install a VPN (Virtual Private Network) so that no one can trace your IP. Never try to access your online banking services on an unsecured network connection, if you try to do so then anyone can get access to your account and you can be in great trouble.

Read AlsoOther Hackers apart from White Hat and Black Hat hackers?

Data Backup:

Backup Device

You can also take a regular backup of your device data in your hard disk or on Google drive. So that you can regularly clean the phone’s data. If in case a hacker hacks your device, it would be a blank file for him and he cannot steal your important data from it. You can also secure your file by providing a password on them also.

Read AlsoHow to know saved WiFi password in the computer?

So, with the rising threat of hacking, here are some of the easy ways to protect your devices from hackers in today’s time. It is important to keep your device safe and secure as it has significant personal details, and many other important information in it. You should have some basic knowledge of your device it secures from unauthorized access.

We board a time, not like the other. With such a large amount of technological advancements at our
fingertips, our lives are created easier, that is lucky considering the fast lives most people lead. In
recent years, nice strides are created in creating homes a small amount additional “tech savvy”.
Home Automation technology, in short, permits the house owner to run his or her home pass
through a far off, usually on a Smartphone or iPad. The ability to “think,” additionally called being an
automatic home, helps householders in an exceeding variety of ways: ten, in fact. What are the
ways that during which a home automation system will profit you?

Reason #1 – Adds Safety Through Appliance and Lighting management

Smart Homes
Another Home Automation advantage is side safety for each your family and residential. you have
got the flexibility to manage the little appliances and lighting, once more with the easy faucet of
your finger on your favourite technological device. Your home and family additionally relish another
life of safety through your ability to manage the lights in your home. This additionally helps increase
the protection and security of your home.

Reason #2 – Secures Home Through Machine-driven Door Locks

Smart Locks
Perhaps one in every of the best edges of {a machine-driven an automatic} system in your house is
automated door locks. Through a Home Automation system, you’ll lock your doors with the faucet
of your finger. This quickly eases your mind; thus, you’ll specialize in your day’s work instead of
World Health Organization could or might not be coming into your home. Often, kids run out the
door to catch the bus and forgot to lock the door. You’ll simply have the management of things by
protection the door from your workplace on a daily basis.

Reason #3. – Will increase Awareness Through Security Cameras

Security Cams
Unfortunately, we have a tendency to simply cannot be everyplace right away. this suggests that we
frequently miss things that happen, maybe even in our own residence or yard. With a home
automation system, you’ll simply see what's happening. Security cameras increase family safety by
recording clips once detection movement or at specific times of the day or night.

Reason#4 – Will increase Convenience Through Temperature Adjustment

Often, we have a tendency to leave for work early within the morning and forget to regulate our
thermostat. As a result, we have a tendency to sink into a house that's severely too hot or too cold.
this can be inconvenient because it typically takes a decent quantity of your time for the ménage
temperature to extend or decrease once being adjusted. However, with a Home Automation
system, you’ll merely change the thermostat from the convenience of your workplace many hours
before heading home

Reason #5 – Saves Time

It is no secret that today’s world is busier than in days past. If you’re like the general public, you’re
perpetually running from place to position, operating to accomplish everything on your endless “to-
do” list, as a result of the advanced nature of a Home Automation system. In short, you simply save
precious time and knowledge of additional daily productivity.

Reason #6 – Saves cash and will increase Convenience


As mentioned earlier, a Home Automation system saves cash. the foremost useful impact the
system can have is on your monthly utility bill. You’ll additionally save on gas prices, as you’ll never
get to stop by the house so as to show one thing off or on. This can be actually convenient.

Reason #7 – Contributes to Economy

Simply put, you’re contributory to the economy after you purchase and utilize a Home Automation
system. You make sure that {you AR you’re} solely exploitation the energy and resources that are
necessary whereas you’re home.

Reason #8 – Will increase Peace of Mind

Perhaps this profit won’t apply to everybody, except for those that routinely worry regarding
whether or not or not they need taken care of everything reception before feat for the day, a Home
Automation system may be a good investment. In short, it offers peace of mind.

Reason #9 – Permits You management once Out of the city

Have you ever gone out of the city and given a key to a neighbour? several try this so as to permit the
neighbour to perform ménage chores that can’t be neglected like feeding the plant, taking care of
the dog, or delivering the mail. You’ll simply come upon a time for the person to enter your home
and let him or her in yourself through your smartphone or iPad.
Home Automation allows you to remain on top of things of things. You got not to worry regarding
the neighbour losing that key or having complete, unrestrained access to your belongings.

Reason #10 – Keeps Tabs On kids

Through the Home Automation system, you’ll simply keep tabs on your kids. You’ll additionally see
their comings and goings on security cameras, still as, make certain the construction is lit after they
arrive home.
This helps you retain them safe, still as helps you recognize what they’re up to every day, which may
be quite useful for a busy parent. It’ll keep you and your family safe and your home secure.

As the name suggests Blockchain is made up of different blocks, Each distributed block is secured with a lock-key pair. The Lock-key pair of one block is based on the Lock-key pair of another block.
Once the data is stored in a blockchain, it becomes complicated to change.

A Block has the following:-

  1. Data,
  2. Hash (the key for each block) for each block and also
  3. Hash for the previous block (the core of the last block).

If the data in a block is changed or tampered it changes the hash value of the block and also all of the following blocks in the chain, The blockchain is formed chronologically. If any Change is to be made in a block, a new block is created saying “X Changed To Y.”


In earlier days the Database file was stored on a single system. Blockchains are decentralized & distributed across a large n/w of computers. This reduces the data tampering. The cryptographic puzzle is to be solved to create a block. The machine that solves the problem shares the solution to all the other computers on the network. It is called Proof of work. All the computers on the network verify proof of work, if it is correct, then the block is added to the chain.

The block chains are distributed ledger technologies that can be programmed to record and track data. A Simple Example of Block Chain can be:

A Book Shelf with different drawers supposes each drawer can hold only one book. We assume that the same book is kept in the same drawer each time.

The book 1 has its hash, but its previous hash is 0000 as it is the first one, also known as the Genesis Block.
The Lock Key of book 2 is dependent on the book1 (previous hash)
& The Lock key for book 3 is dependent on the last hash, i.e., of book 2.

Now Suppose if the data in book 2 tampers. It will cause a change in its hash value and also it affects the following blocks in the chain. Because they no longer store the valid hash value of the previous hash.

Proof of work helps to reduce tampering of data because it takes time to calculate the required evidence of work and add the block.

Therefore, when the data of one block has tampered you need to re-calculate the proof of work for all the following blocks.

So, The Security of the blockchain comes from its creative use of hashing as well as the proof of work.

Blockchains are distributed systems and not a single entity; this makes them more secure. The Blockchains work with trusted Peer to Peer networks. When Someone joins this network, they receive a copy of blockchain. When Someone creates a new block it is sent to everyone on the network, each node then verifies the block to make sure that it has not tampered. And, if it is confirmed it is added to every node’s blockchain.

One of the recent creations using blockchain is Smart Contracts. It can also be used to storing medical records, create digital E-notary & even Collecting taxes

Advantages of Blockchain Technolgy:

  1. Resistance To Failures
  2. Greater transparency
  3. Enhanced security
  4. Increased efficiency and speed
  5. Reduced costs
  6. Users Are More Likely To Trust An Application That Is Not Controlled By One Governing Body Capable Of Deceiving Them For Their Benefit.
  7. If The Peer-To-Peer Network Is Large Enough, Completely Disconnecting The Application Becomes An Impossible Task, Especially If The Nodes Are Scattered Across Different Countries.

Disadvantages of Blockchain Technology:

  1. Difficulties With Updating And Eliminating Errors
  2. Applications Need To Verify The Identity Of The User
  3. Problem Of Development.
  4. Applications Do Not Need Third-Party APIs To Store Or Retrieve Data. Your Decentralized Application (Dapp) Should Not Depend Upon The API Of Centralized Applications

Block Chain Technology helps to cut the middle man, and so it saves time and money of the users.
It is more secure and therefore difficult to hack, i.e., the data can’t be stolen or modified.
It should be understood that blockchain is a revolutionary technology that will rebuild many present business models, completely transform the economy and society.
Nevertheless, the potential for blockchain technology and its full range of use is still in the development stage.

But, It has come to transform our economy and society deeply.