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What is pip, Getting Started with Python pip

Pip is a package manager for Python that allows you to install additional libraries and packages that are not part of the standard Python library such as the ones found in the Python Package Index. It is a replacement for easy install. If your version of Python is 2.7.9 (or greater) or Python 3.4 (or greater), then PIP comes pre-installed with Python, in other cases you will have to install it separately. PIP is a recursive acronym for “Preferred Installer Program” or “PIP Installs Packages”. It is a command-line utility that installs, reinstalls, or uninstalls PyPI packages with one simple command: pip. You may be familiar with the term package manager if you have used other languages like Ruby uses Gem, JavaScript uses npm for package management, and .NET uses NuGet. Pip has become the standard package manager for Python. The Python installer installs pip automatically, so it is ready for you to use, unless you have installed an older version of Python. You can also verify if pip is available on your Python version by running the command below:On running the command mentioned above, a similar output should be displayed which will show the pip version, along with the location and version of Python. If you are using an older version of Python, the pip version will not be displayed. Then you can install it separately. You can download pip from the following link: https://pypi.org/project/pip/ Installing pip in PythonFor WindowsFollow the instructions to install pip in Python on Windows 7, Windows 8.1, and Windows 10: Download get-pip.py installer script from https://bootstrap.pypa.io/get-pip.py. For Python 3.2, download from https://bootstrap.pypa.io/3.2/get-pip.py. After that, right-click on the link and select Save As and save it to any safe location on your computer. Open Command Prompt and navigate to the get-pip.py file where you saved it previously. Run the command: python get-pip.py For Mac Modern Mac systems have Python and pip pre-installed but the version of Python tends to be outdated and not the best choice for serious programming in Python. So, it’s highly recommended that you install a more updated version of Python and PIP. If you want to use the pre-installed Python application but don’t have PIP available, you can install PIP with the following commands in Terminal:sudo easy_install pipIf you want to install an updated version of Python, then you can use Homebrew. Installing Python with Homebrew requires a single command:brew install pythonInstalling Python with Homebrew will give you the latest version which should come packaged with PIP but if PIP is unavailable, you can re-link Python using the following commands in Terminal:brew unlink python && brew link pythonFor Linux If your Linux distribution came with Python pre-installed, using your system’s package manager you will be able to install PIP. This is preferable since pre-installed versions of Python do not work well with the get-pip.py script used on Windows and Mac. Given below are the commands you should run in order to install pip in your system depending on the version of Python you are using:Advanced Package Tool (Python 2.x):sudo apt-get install python-pip pacman Package Manager (Python 2.x):sudo pacman -S python2-pip Yum Package Manager (Python 2.x):sudo yum upgrade python-setuptools  sudo yum install python-pip python-wheel Dandified Yum (Python 2.x):sudo dnf upgrade python-setuptools  sudo dnf install python-pip python-wheel Zypper Package Manager (Python 2.x):sudo zypper install python-pip python-setuptools python-wheel Advanced Package Tool (Python 3.x): sudo apt-get install python3-pip pacman Package Manager (Python 3.x): sudo pacman -S python-pip Yum Package Manager (Python 3.x): sudo yum install python3 python3-wheel Dandified Yum (Python 3.x): sudo dnf install python3 python3-wheel Zypper Package Manager (Python 3.x): sudo zypper install python3-pip python3-setuptools python3-wheel For Raspberry Pi You are most likely running Raspbian if you are a Raspberry Pi user as it is the official operating system designated and provided by the Raspberry Pi Foundation. PIP comes pre-installed on with Raspbian Jessie. It is one of the biggest reasons to upgrade to Raspbian Jessie instead of using Raspbian Wheezy or Raspbian Jessie Lite. If you are using an older version of Raspbian, you can still manually install PIP. Given below are the commands you should run in order to install pip on your system depending on the version of Python you are using: On Python 2.x:sudo apt-get install python-pipOn Python 3.x:sudo apt-get install python3-pipRaspbian users, working with Python 2.x must use pip while Python 3.x users must use pip3 while running PIP commands.For Ubuntusudo apt-get install python-pipFor Fedorasudo yum install python-pipHow to use PIP and PyPI? PyPI - the Python Package Index After PIP is installed, we need to find a package to install. Packages are usually installed from the repository of software for the Python programming language which is the Python Package Index.Set environment variable for PIP:You won’t have to reference the pip install directory again and again if you set an environment variable.Set: (default = C:\Python27\Scripts) in your Windows/Linux “PATH” environment variable.Getting Started with PIP Now that we know what PIP is and have successfully installed it on our computer, let's get started on how to use it: Commands in PIP Enter pip in the command terminal and it will show the following output on the screen. Usage:pip [options] Commands:InstallInstall packagesDownloadDownload packagesuninstallUninstall packagesunzipUnzip individual packagesbundleCreate pybundleshelpShow help for commandsconfigManage local and global configurationfreezeOutput installed packages in required formatlistList installed packageswheelBuild wheels from your requirementshashCompute hashes of package archivescompletionA helper command used for command completioncheckVerify installed packages have compatible dependenciesshowShow information about installed packagessearchSearch PyPI for packageszipZip individual packagesCommonly used commands in pip are install, upgrade or uninstall. General Options: -h, --help: Shows help. --isolated: To run pip in an isolated mode by ignoring environment variables and user configuration. -v, --verbose: Give more output. Option is additive, and can be used up to 3 times. -V, --version: Show version and exit. -q, --quiet: Give less output. Option is additive, and can be used up to 3 times (corresponding to WARNING, ERROR, and CRITICAL logging levels). --proxy: Specify a proxy in the form [user:passwd@]proxy.server:port. --trusted-host: Mark this host as trusted, even though it does not have valid or any HTTPS. --cert: Path to alternate CA bundle. --client-cert: Path to SSL client certificate, a single file containing the private key and the certificate in PEM format. --retries: Maximum number of retries each connection should attempt(5 times by default). --timeout: Set the socket timeout(15 seconds by default). --exists-action: Default action when a path already exists: (s)witch,(i)gnore, (w)ipe, (b)ackup, (a)bort). --cache-dir: Store the cache data in <dir>.--no-cache-dir: Disable the cache. --disable-pip-version-check: Don't periodically check PyPI to determine whether a new version of pip is available for download. Implied with --no-index. Finding required packages:To search any package, i.e. Flask command will be as shown below: pip search Flask The following output will be displayed with all packages and description: Flask-Cache - Adds cache support to your Flask applicationFlask-SeaSurf - An update CSRF extension for FlaskFlask-Admin - Simple and extensible admin interface framework for FlaskFlask-Security - Simple security for Flask appsFlask - A microframework based on Werkzeug, Jinja2 and good intentions Installing a package: To install the required package, in our case it is Flask, enter the following command : pip install Flask Pip – Show information To check information about the newly installed packages enter: pip show Flask  --- Name: Flask  Version: 0.10.1  Location: /usr/local/lib/python2.7/dist-packages  Requires: Werkzeug, Jinja2, itsdangerousUninstalling a package:To uninstall any package installed by PIP, enter the command given below. pip uninstall Flask Uninstalling Flask: ... ..... Proceed (y/n)?  Successfully uninstalled Flask That’s all. The PIP application has been uninstalled. How to Upgrade PIP for Python Although PIP application doesn’t receive updates very often, it’s still important to keep the application up to date with the newer versions because there may be important fixes to bugs, compatibility, and security holes. Fortunately, upgrading to the latest versions of PIP is very fast and simple. On Windows python -m pip install -U pip On Mac, Linux, or Raspberry Pi pip install -U pip Certain versions of Linux and Raspberry Pi, pip3 needs to be entered instead of pip. Using Requirement FilesThe pip install command always installs the latest published version of a package, but you should install the particular version that suits your code. You would want to create a specification of the dependencies and versions that you have used while developing and running your application, so that there are no surprises when you use the application in production. Requirement files allow you to specify exactly the packages and versions that should be installed on your system. Executing pip help shows that there is a freeze command that displays the installed packages in requirements format. This command can be used to redirect the output to a file to generate a requirements file: The freeze command is used to dump all the packages and their versions to a standard output, so as to redirect the output to a file that can be used to install the exact requirements into another system. The general convention is to name this file requirements.txt, but it is completely up to you to name it whatever you want. If you want to replicate the environment in another system, run pip install specifying the requirements file using the -r switch:The versions listed in requirements.txt will match those of the packages: $ pip list Package    Version  ----------        ----------  certifi2018.11.29  chardet3.0.4  idna   2.8  pip    19.0.1  requests     2.21.0  setuptools  40.6.2  urllib31.24.1 You may submit the requirements.txt file to source control and can use it to create the exact environment in other machines. Fine-Tuning Requirements The problem with hardcoding the versions of your packages and their dependencies is that the packages receive frequent updates with bug and security fixes, and you probably want to update to them as soon as they are published. The requirements file format gives you a bit of flexibility to ensure that the packages are up to date by allowing you to enter dependency versions using logical operators, although specifying the base versions of a package. Make the following changes by opening the requirements.txt file in your editor: certifi>=2018.11.29  chardet>=3.0.4  idna>=2.8  requests>=2.21.0  urllib3>=1.24.1 Change the logical operator to >= to install an exact or greater version that has been published. While you set a new environment using the requirments.txt file, pip searches for the latest version that supports the requirement and installs it. The packages in your requirements file can be updated by running the install command with the --upgrade switch: In this case nothing was upgraded because latest versions have already been installed, but if a new version was published for a listed package, then the package would’ve been upgraded. New versions can introduce changes that fix bugs and will make or break your application. In order to fine-tune your requirements, the requirements file syntax supports additional version specifiers. Let us assume that a new version 3.0 of requests is published but it breaks your application as it introduces an incompatible change. In such a case, the requirements file can be modified to prevent 3.0 or higher versions from being installed: certifi>=2018.11.29 chardet>=3.0.4 idna>=2.8 requests>=2.21.0, <3.0 urllib3>=1.24.1Changing the version specifier for the requests package ensures that only the versions which are less than 3.0 get installed. Production vs Development DependenciesAll packages which are installed during the development of your applications are not going to be application dependencies. During the development process, there are certain packages published to PyPI that are development tools or libraries that can be useful to you. For example, you would require a unit test framework in order to unit test your application. Pytest is a popular framework for unit testing. You would want to install the unit testing framework in your development environment, but not in your production environment because it is not an application dependency. To set up a development environment, you need to create a second requirements file (requirements_file.txt) to list additional tools: # In requirements_file.txt  pytest>=4.2.0 To do this, you need to install both requirement files using pip: requirements.txt and requirements_file.txt. Pip allows for specifying additional parameters within a single requirements file. The requirements_file.txt can also be modified to install the requirements from the production requirements.txt file: # In requirements_file.txt  -r requirements.txt  pytest>=4.2.0 Notice that the exact same -r switch is being used in order to install the production requirements.txt file. The file format of the requirements file allows you to specify additional arguments right on a requirements file. Alternatives to pipPip is an essential tool for all Pythonistas which is used in developing many applications and projects for package management. This article gives you the basics of Pip for Python but the Python community is very active in providing great tools and libraries for developers using other applications as well. These include alternatives to pip that try to improve and simplify package management. Here are some package management tools other than pip which are available for Python: CondaPoetryPipenvSummaryBy now you know that pip is a package manager for Python that is used in many projects to manage dependencies. It is included with the Python installer, hence it is essential for all Python programmers to know how to use it. Although Python provides a wide range of standard libraries which are suitable for developing all types of applications, the active Python community provides more sets of tools and libraries that speed up the development process of a Python application. In this article, we have covered: The process of installing pip in Python Setting an environment variable for pip Commonly used commands in pip and their functions Finding and installing new packages using pip with requirement files in the command line and getting information about the newly installed package How to uninstall a package in pip? In addition to the above topics we have also covered the importance of keeping dependencies updated and a few alternatives to pip that can help managing those dependencies. To gain more knowledge about Python tips and tricks, check our Python tutorial and get a good hold over coding in Python by joining the Python certification course. 

What is pip, Getting Started with Python pip

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What is pip, Getting Started with Python pip

Pip is a package manager for Python that allows you to install additional libraries and packages that are not part of the standard Python library such as the ones found in the Python Package Index. It is a replacement for easy install. If your version of Python is 2.7.9 (or greater) or Python 3.4 (or greater), then PIP comes pre-installed with Python, in other cases you will have to install it separately. 

PIP is a recursive acronym for “Preferred Installer Program” or “PIP Installs Packages”. It is a command-line utility that installs, reinstalls, or uninstalls PyPI packages with one simple command: pip. You may be familiar with the term package manager if you have used other languages like Ruby uses Gem, JavaScript uses npm for package management, and .NET uses NuGet. Pip has become the standard package manager for Python. 

The Python installer installs pip automatically, so it is ready for you to use, unless you have installed an older version of Python. You can also verify if pip is available on your Python version by running the command below:

PIP in Python

On running the command mentioned above, a similar output should be displayed which will show the pip version, along with the location and version of Python. If you are using an older version of Python, the pip version will not be displayed. Then you can install it separately. 

You can download pip from the following link:
https://pypi.org/project/pip/ 

Installing pip in Python

For Windows

Follow the instructions to install pip in Python on Windows 7, Windows 8.1, and Windows 10: 

For Mac 

Modern Mac systems have Python and pip pre-installed but the version of Python tends to be outdated and not the best choice for serious programming in Python. So, it’s highly recommended that you install a more updated version of Python and PIP. 

If you want to use the pre-installed Python application but don’t have PIP available, you can install PIP with the following commands in Terminal:

sudo easy_install pip

If you want to install an updated version of Python, then you can use Homebrew. Installing Python with Homebrew requires a single command:

brew install python

Installing Python with Homebrew will give you the latest version which should come packaged with PIP but if PIP is unavailable, you can re-link Python using the following commands in Terminal:

brew unlink python && brew link python

For Linux 

If your Linux distribution came with Python pre-installed, using your system’s package manager you will be able to install PIP. This is preferable since pre-installed versions of Python do not work well with the get-pip.py script used on Windows and Mac. Given below are the commands you should run in order to install pip in your system depending on the version of Python you are using:

Advanced Package Tool (Python 2.x):

sudo apt-get install python-pip 

pacman Package Manager (Python 2.x):

sudo pacman -S python2-pip 

Yum Package Manager (Python 2.x):

sudo yum upgrade python-setuptools 
sudo yum install python-pip python-wheel 

Dandified Yum (Python 2.x):

sudo dnf upgrade python-setuptools 
sudo dnf install python-pip python-wheel 

Zypper Package Manager (Python 2.x):

sudo zypper install python-pip python-setuptools python-wheel 

Advanced Package Tool (Python 3.x): 

sudo apt-get install python3-pip 

pacman Package Manager (Python 3.x): 

sudo pacman -S python-pip 

Yum Package Manager (Python 3.x): 

sudo yum install python3 python3-wheel 

Dandified Yum (Python 3.x): 

sudo dnf install python3 python3-wheel 

Zypper Package Manager (Python 3.x): 

sudo zypper install python3-pip python3-setuptools python3-wheel 

For Raspberry Pi 

You are most likely running Raspbian if you are a Raspberry Pi user as it is the official operating system designated and provided by the Raspberry Pi Foundation. PIP comes pre-installed on with Raspbian Jessie. It is one of the biggest reasons to upgrade to Raspbian Jessie instead of using Raspbian Wheezy or Raspbian Jessie Lite. If you are using an older version of Raspbian, you can still manually install PIP. Given below are the commands you should run in order to install pip on your system depending on the version of Python you are using: 

On Python 2.x:

sudo apt-get install python-pip

On Python 3.x:

sudo apt-get install python3-pip

Raspbian users, working with Python 2.x must use pip while Python 3.x users must use pip3 while running PIP commands.

For Ubuntu

sudo apt-get install python-pip

For Fedora

sudo yum install python-pip

How to use PIP and PyPI? 

PyPI - the Python Package Index 

After PIP is installed, we need to find a package to install. Packages are usually installed from the repository of software for the Python programming language which is the Python Package Index.

Set environment variable for PIP:

You won’t have to reference the pip install directory again and again if you set an environment variable.

Set: (default = C:\Python27\Scripts) in your Windows/Linux “PATH” environment variable.

Getting Started with PIP 

Now that we know what PIP is and have successfully installed it on our computer, let's get started on how to use it: 

Commands in PIP 

Enter pip in the command terminal and it will show the following output on the screen. 

Usage:
pip [options] 

Commands:

InstallInstall packages
DownloadDownload packages
uninstallUninstall packages
unzipUnzip individual packages
bundleCreate pybundles
helpShow help for commands
configManage local and global configuration
freeze
Output installed packages in required format
listList installed packages
wheelBuild wheels from your requirements
hashCompute hashes of package archives
completionA helper command used for command completion
checkVerify installed packages have compatible dependencies
showShow information about installed packages
searchSearch PyPI for packages
zipZip individual packages

Commonly used commands in pip are install, upgrade or uninstall. 

General Options: 

-h, --help: Shows help. 

--isolated: To run pip in an isolated mode by ignoring environment variables and user configuration. 

-v, --verbose: Give more output. Option is additive, and can be used up to 3 times. 

-V, --version: Show version and exit. 

-q, --quiet: Give less output. Option is additive, and can be used up to 3 times (corresponding to WARNING, ERROR, and CRITICAL logging levels). 

--proxy: Specify a proxy in the form [user:passwd@]proxy.server:port. 

--trusted-host: Mark this host as trusted, even though it does not have valid or any HTTPS. 

--certPath to alternate CA bundle. 

--client-cert: Path to SSL client certificate, a single file containing the private key and the certificate in PEM format. 

--retries: Maximum number of retries each connection should attempt(5 times by default). 

--timeout: Set the socket timeout(15 seconds by default). 

--exists-action: Default action when a path already exists: (s)witch,(i)gnore, (w)ipe, (b)ackup, (a)bort). 

--cache-dir: Store the cache data in <dir>.

--no-cache-dir: Disable the cache. 

--disable-pip-version-check: Don't periodically check PyPI to determine whether a new version of pip is available for download. Implied with --no-index. 

Finding required packages:

To search any package, i.e. Flask command will be as shown below: pip search Flask 

The following output will be displayed with all packages and description: 

Flask-Cache - Adds cache support to your Flask application
Flask-SeaSurf - An update CSRF extension for Flask
Flask-Admin - Simple and extensible admin interface framework for Flask
Flask-Security - Simple security for Flask apps
Flask - A microframework based on Werkzeug, Jinja2 and good intentions 

Installing a package: 

To install the required package, in our case it is Flask, enter the following command : 

pip install Flask 

Pip – Show information 

To check information about the newly installed packages enter: 

pip show Flask 
--- 
Name: Flask 
Version: 0.10.1 
Location: /usr/local/lib/python2.7/dist-packages 
Requires: Werkzeug, Jinja2, itsdangerous

Uninstalling a package:

To uninstall any package installed by PIP, enter the command given below. 

pip uninstall Flask
Uninstalling Flask:
...
.....
Proceed (y/n)? 
Successfully uninstalled Flask 

That’s all. The PIP application has been uninstalled. 

How to Upgrade PIP for Python 

Although PIP application doesn’t receive updates very often, it’s still important to keep the application up to date with the newer versions because there may be important fixes to bugs, compatibility, and security holes. Fortunately, upgrading to the latest versions of PIP is very fast and simple. 

On Windows 

python -m pip install -U pip 

On Mac, Linux, or Raspberry Pi 

pip install -U pip 

Certain versions of Linux and Raspberry Pi, pip3 needs to be entered instead of pip. 

Using Requirement Files

The pip install command always installs the latest published version of a package, but you should install the particular version that suits your code. 

You would want to create a specification of the dependencies and versions that you have used while developing and running your application, so that there are no surprises when you use the application in production. 

Requirement files allow you to specify exactly the packages and versions that should be installed on your system. Executing pip help shows that there is a freeze command that displays the installed packages in requirements format. This command can be used to redirect the output to a file to generate a requirements file: 

pip install Requirements in Python

The freeze command is used to dump all the packages and their versions to a standard output, so as to redirect the output to a file that can be used to install the exact requirements into another system. The general convention is to name this file requirements.txt, but it is completely up to you to name it whatever you want. 

If you want to replicate the environment in another system, run pip install specifying the requirements file using the -r switch:

The versions listed in requirements.txt will match those of the packages: 

$ pip list 

Package    Version 
----------        ---------- 
certifi2018.11.29 
chardet3.0.4 
idna   2.8 
pip    19.0.1 
requests     2.21.0 
setuptools  40.6.2 
urllib31.24.1 

You may submit the requirements.txt file to source control and can use it to create the exact environment in other machines. 

Fine-Tuning Requirements 

The problem with hardcoding the versions of your packages and their dependencies is that the packages receive frequent updates with bug and security fixes, and you probably want to update to them as soon as they are published. 

The requirements file format gives you a bit of flexibility to ensure that the packages are up to date by allowing you to enter dependency versions using logical operators, although specifying the base versions of a package. 

Make the following changes by opening the requirements.txt file in your editor: 

certifi>=2018.11.29 
chardet>=3.0.4 
idna>=2.8 
requests>=2.21.0 
urllib3>=1.24.1 

Change the logical operator to >= to install an exact or greater version that has been published. While you set a new environment using the requirments.txt file, pip searches for the latest version that supports the requirement and installs it. The packages in your requirements file can be updated by running the install command with the --upgrade switch: 

Fine-Tuning Requirements in Python

In this case nothing was upgraded because latest versions have already been installed, but if a new version was published for a listed package, then the package would’ve been upgraded. 

New versions can introduce changes that fix bugs and will make or break your application. In order to fine-tune your requirements, the requirements file syntax supports additional version specifiers. 

Let us assume that a new version 3.0 of requests is published but it breaks your application as it introduces an incompatible change. In such a case, the requirements file can be modified to prevent 3.0 or higher versions from being installed: 

certifi>=2018.11.29
chardet>=3.0.4
idna>=2.8
requests>=2.21.0, <3.0
urllib3>=1.24.1

Changing the version specifier for the requests package ensures that only the versions which are less than 3.0 get installed. 

Production vs Development Dependencies

All packages which are installed during the development of your applications are not going to be application dependencies. During the development process, there are certain packages published to PyPI that are development tools or libraries that can be useful to you. 

For example, you would require a unit test framework in order to unit test your application. Pytest is a popular framework for unit testing. You would want to install the unit testing framework in your development environment, but not in your production environment because it is not an application dependency. 

To set up a development environment, you need to create a second requirements file (requirements_file.txt) to list additional tools: 

# In requirements_file.txt 
pytest>=4.2.0 

To do this, you need to install both requirement files using pip: requirements.txt and requirements_file.txt. Pip allows for specifying additional parameters within a single requirements file. The requirements_file.txt can also be modified to install the requirements from the production requirements.txt file: 

# In requirements_file.txt 
-r requirements.txt 
pytest>=4.2.0 

Notice that the exact same -r switch is being used in order to install the production requirements.txt file. The file format of the requirements file allows you to specify additional arguments right on a requirements file. 

Alternatives to pip

Pip is an essential tool for all Pythonistas which is used in developing many applications and projects for package management. This article gives you the basics of Pip for Python but the Python community is very active in providing great tools and libraries for developers using other applications as well. These include alternatives to pip that try to improve and simplify package management. 

Here are some package management tools other than pip which are available for Python: 

  • Conda
  • Poetry
  • Pipenv

Summary

By now you know that pip is a package manager for Python that is used in many projects to manage dependencies. It is included with the Python installer, hence it is essential for all Python programmers to know how to use it. 

Although Python provides a wide range of standard libraries which are suitable for developing all types of applications, the active Python community provides more sets of tools and libraries that speed up the development process of a Python application. 

In this article, we have covered: 

  • The process of installing pip in Python 
  • Setting an environment variable for pip 
  • Commonly used commands in pip and their functions 
  • Finding and installing new packages using pip with requirement files in the command line and getting information about the newly installed package 
  • How to uninstall a package in pip? 

In addition to the above topics we have also covered the importance of keeping dependencies updated and a few alternatives to pip that can help managing those dependencies. To gain more knowledge about Python tips and tricks, check our Python tutorial and get a good hold over coding in Python by joining the Python certification course

Priyankur

Priyankur Sarkar

Data Science Enthusiast

Priyankur Sarkar loves to play with data and get insightful results out of it, then turn those data insights and results in business growth. He is an electronics engineer with a versatile experience as an individual contributor and leading teams, and has actively worked towards building Machine Learning capabilities for organizations.

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Numpy As the name implies, this is the library which supports numerical calculations and tasks. It supports array operations and basic mathematical functions on the array and other data types of Python. The basic data type of this library is ndArray object.   Numpy has many advantagesThe base data structure is N –Dimensional array. Rich functions to handle the N-dimensional array effectively. Supports integration of C, C++ and other language code fragments. Supports many functions related to linear algebra, random numbers, transforms, statistics etc. DisadvantagesNo GPU and TPU support. Cannot automatically calculate the derivatives which is required in all ML algorithms. Numpy performance goes down when high complex calculations are required. 2. PandasThis is the most useful library for data preprocessing and preparing the data for the Machine Learning algorithms. The data from various files like CSV, Excel, Data etc. can be easily read using Pandas. The data is available in a spreadsheet like area, which makes processing easy. There are three basic data structures at the core of Pandas library: Series - One-dimensional array like object containing data and label (or index). Dataframe - Spreadsheet-like data structure containing an order collection of columns. It has both a row and column index. Panel – Collection of dataframes but rarely used data structure. AdvantagesStructured data can be read easily. Great tool for handling of data. Strong functions for manipulation and preprocessing of data. Data Exploration functions help in better understanding data. Data preprocessing capabilities help in making data ready for the application of ML algorithms. Basic Plotting functions are provided for visualization of data.  Datasets can be easily joined or merged. The functions of Pandas are optimized for large datasets. DisadvantagesGetting to know the Pandas functionalities is time consuming. The syntax is complex when multiple operations are required. Support for 3D metrics is poor. Proper documentation is not available for study. 3. MatplotlibMatplotlib is an important Python library which helps in data visualization. Understanding the data is very important for a data scientist before devising any machine learning based model. This library helps in understanding the data in a visual way. Data can be visualized using various graphical methods like line graph, bar graph, pie chart etc. This is a 2D visualization library with numerous ways of visualizing data. Image SourceAdvantagesSimple and easy to learn for beginners. Integrated with Pandas for visualization of data in effective way. Various plots are provided for better understanding of data like Bar Chart, Stacked Bar chart, Pie chart, Scatter Plot etc. Forms a base for many advanced plotting libraries. Supports storing of the various graphs as images so that they can be integrated with other applications. Can plot timeseries data (with date) very easily. DisadvantagesComplex Syntax for plotting simple graphs. The code becomes lengthy and complex for visualizations. Support for plotting of categorial data is not provided. It is a 2D visualization library. When multiple fields are required to be plotted and visualized effectively, matplotlib code can become lengthy. Managing multiple figures is difficult. 4. Seaborn Visualizations are made simpler and more advanced with the help of Seaborn library. The base for Seaborn is Matplotlib. It is a boon for programmers as statistical visualizations are simplified. Image sourceAdvantagesBest high-level interface for drawing statistical graphics. Provides support for plotting of categorial data effectively. The library provides default themes and many visualization patterns. Multiple figures are automatically created. The syntax is very simple and compact. There are many methods to integrate with Pandas dataframe, making this library most useful for visualization. DisadvantagesMemory issues due to creation of multiple figures. Less customizable and flexible as compared to Matplotlib. Scalability issues. 5. Scipy   Scipy is a Scientific Python library based on Numpy. It has functions which are best suitable for Mathematics, Science and Engineering. Many libraries are provided for Image and Signal Processing, Fourier Transform, Linear Algebra, Integration and Optimization. The functions are useful for ML algorithms and programs. AdvantagesThe base library is Numpy. Many ML related functions are provided like Linear Algebra, Optimization, Compressed Sparce Data Structure etc. Useful Linear Algebra functions are available which are required for implementation of ML related algorithms. The functions can be applied with Pandas Dataframe directly. DisadvantagesComplex functions are available and domain knowledge is needed to understand and implement these functions. There are performance issues when data size increases. Many other effective alternative libraries are available with the needed functionality. 6. Scikit-Learn Scikit-Learn is a useful open access library for use to Python developers. It is an extensive and popular library with many Machine Learning Supervised and Unsupervised algorithms implemented. These algorithms can be fine-tuned with the help of hyperparameters. This library contains many useful functions for preprocessing of data, useful metrics to measure performance of algorithms and optimization techniques.  AdvantagesIt is a general Machine Learning library built on top of Numpy, Pandas and Matplotlib. Simple to understand and use even for novice programmers. Useful Machine Learning Algorithms, both Supervised and Unsupervised, are implemented. Popular library for doing Machine Learning related tasks. Rich in Data Preprocessing and Data Sampling functions and techniques. Plethora of evaluation measures implemented to track the performance of algorithms. Very effective for quick coding and building Machine Learning Models. DisadvantagesScikit learn, as is based on Numpy, requires additional support to run on GTP and TPU Performance is an issue with size of data. Best suitable for basic Machine Learning applications. This library may be useful if one wants to write easy code, but it’s not the best choice for more detailed learning. 7. NLTK Natural Language processing is a great field of study for developers who like to research and challenge themselves. This library provides a base for Natural Language processing by providing simple functionalities to work with and understand languages.AdvantagesVery simple to use for processing natural language data. Many basic functionalities like tokenizing the words, removal of stop words, conversion to word vectors etc. are provided which forms the basis to start with natural language processing models. It is an amazing library to play with natural language using Python. It has more than 50 trained models and lexical resources like wordnet available for use. Rich discussion forums and many examples are available to discuss how to use this library effectively. DisadvantagesIt is based on string processing, which itself has many limitations. Slower as compared to other Natural Language processing libraries like Spacy.8. Keras Keras is a library written in Python for Neural Network programming. It offers a very simple interface to code the neural network and related algorithms. It is an incredibly popular library for Deep Learning algorithms, models and applications and can also be combined with various deep learning frameworks. It provides support for GPU and TPU computation of algorithms. The API provided is simple, same as Scikit-learn. Keras is totally based on Models and Graphs. A model has Input, output and intermediate layers to perform the various tasks as per requirement. Effective functionalities and models provided to code deep learning algorithms like Neural Network, Recurrent Neural Network, Long Short-Term memory, Autoencoders etc. Allows to create products easily supporting multiple backends Supports multi-platform use. Can be used with TensorFlow, can be used in browser using web based keras and provides native ML support for iPhone app development. 9. TensorFlow TensorFlow is the talk of the town because of its capabilities suitable for Machine Learning and Deep Learning models. It is one of the best, and most popular frameworks, adopted by companies around the world for Machine Learning and Deep Learning. Its support for Web as well as Mobile application coupled with Deep Learning models has made it popular among engineers and researchers. Many giants like IBM, Dropbox, Nvidia etc. use TensorFlow for creating and deploying Machine Learning Models. This library has many applications like image recognition, video analysis, speech recognition, Natural Language Processing, Recommendation System etc. TensorFlow lite and TensorFlow JS has made it more popular for web applications and Mobile Applications. Advantages Developed by Google, it is one of the best deep learning frameworks. Simple Machine Learning tasks are also supported in TensorFlow. Supports many famous libraries like scikit learn, Keras etc. which are part of TensorFlow. The basic unit is Tensor which is an n-dimensional array. The basic derivatives are inherently computed which helps in developing many Machine learning Models easily. The models developed are supported on CPT, TPU and GPU. Tensorboard is the effective tool for data visualization. Many other supported tools are available to facilitate Web Development, App Development and IoT Applications using Machine Learning. Disadvantages Understanding Tensor and computational graphs is tedious. Computational graphs make the code complex and sometimes face performance problems. 10. Pytorch A popular Python framework, Pytorch supports machine learning and deep learning algorithms and is a scientific computing framework. This is a framework which is widely used by Twitter, Google and Facebook. The library supports complex Tensor computations and is used to construct deep neural networks. AdvantagesThe power of Pytorch lies in construction of Deep Neural Networks. Rich functions and utilities are provided to construct and use Neural Networks. Powerful when it comes to creation of production ready models. It supports GPU operations with rich math-based library functions. Unlike Numpy, it provides the functions which calculates gradient of the function, useful for the construction of the neural network. Provides support for Gradient based optimization which helps in scaling up the models easily to large data. Disadvantages It is a complex framework, so learning is difficult. Documentation support for learning is not readily available. Scalability may be an issue as compared to TensorFlow. 11. Theano Theano is a library for evaluating and optimizing the mathematical computations. It is based on NumPy but provides support for both the GPU and CPU. AdvantagesIt is a fast computation library in Python. Uses native libraries like BIAS to turn the code in faster computation. Best suited to handle computations in Deep Learning algorithms. Industry standard for Deep Learning research and development. Disadvantages It is not very popular among researchers as it is one of the older frameworks. It is not as easy to use as TensorFlow.12. CNTK CNTK is Microsoft’s Cognitive Toolkit for the development of Deep Learning based models. It is a commercial distributed deep learning tool. AdvantagesIt is a distributed open-source deep learning framework. Popular models like Deep Neural Network, Convolutional Neural Network models can be combined easily to form new models. Provides interface with C, C++ and Java to include Machine Learning models. Can be used to build reinforcement learning models as wide functions are available. Can be used to develop GAN (Generative Adversarial Networks). Provides various ways to measure the performance of the models built. High accuracy parallel computation on Multiple GPU is provided. Disadvantages Proper documentation is not available. There is inadequate community support. ConclusionPython, being one of the most popular languages for the development of Machine Learning models, has a plethora of tools and frameworks available for use. The choice of tool depends on the developer’s experience as well as the type of application to be developed. Every tool has some strong points and some weaknesses, so one has to carefully choose the tool or framework for the development of Machine Learning based applications. The documentation and support available are also important criteria to be kept in mind while choosing the most appropriate tool. 
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Top 12 Python Packages for Machine Learning

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Top-Paying Programming Certifications for 2021

Programming is at the core of software development, which is why there is a huge demand for programmers—a demand that is growing exponentially and is expected to rise at a steady rate even in the future. In today’s world, just about everything is getting automated and digitization has become the new normal.Recruiters are on the lookout for professionals who have solid programming and full-stack development skills. Every recruiting agency and organizational HR recruiting team has put in place a thorough screening process, and this active hiring in startups, SMEs, and multinational companies has raised the bar for many aspiring programmers. Having a software development, web development, or programming certification will give you an upper hand at the time of recruitment. A certification from a reputed accreditation body will validate your skills and make you stand out among your peers.Having an extra certification apart from your UG or PG degree makes you a better fit for the job role in which you have an interest. But before you opt for any certification, you need to understand which programming language will take you where; and the potential benefits of pursuing a certification course of that particular programming language.In this article, you will get to know about the top programming certifications of 2021 and how to achieve them.What are Programming certifications?Programming certifications are exam-oriented, and verify your skill and expertise in that field. Different organizations provide different programming certification exams that define your level, skills, and abilities vis `a vis that programming language. Having a programming certification will give you an edge over other peers and will highlight your coding skills.Most Popular Programming CertificationsC & C++ CertificationsOracle Certified Associate Java Programmer OCAJPCertified Associate in Python Programming (PCAP)MongoDB Certified Developer Associate ExamR Programming CertificationOracle MySQL Database Administration Training and Certification (CMDBA)CCA Spark and Hadoop Developer1. C & C++ CertificationsRegardless of your specialization in your UG or PG courses, clearing a developer-rated certification will not only make your resume stand out from others but also enhance your skills and boost your confidence. We have curated the top-most and popularly available certifications with descriptions that can help you decide which one is appropriate for your career path.C & C++ Certifications: C and C++ are often called the mother of Procedure-oriented and Object-oriented programming languages, which is absolutely true. These two programming languages have been around for many decades. Colleges and universities all over the world teach these as the base language. To get global recognition for the C and C++ certification, C++ Institute and Pearson VUE decided to carve a niche in this part of the certification landscape by offering the world's first international C/C++ certifications.Aspirants and professionals can choose either C or C++ as a career option/path and climb the certification ladder from associate to professional to senior. The C Programming Language Certified Associate (CLA) and C++ Certified Associate Programmer (CPA) are the core and first-level C and C++ certifications.CLA comprises of topics likeIntroduction to compiling and software development;Basic scalar data types and their operators;Flow control;Complex data types: arrays, structures and pointers;Memory management;Files and streams;Structuring the code: functions and modules;Preprocessor directives and complex declarations.CPA comprises of topics likeIntroduction to compiling and software development;Basic scalar data types, operators, flow control, streamed input/output, conversions;Declaring, defining and invoking functions, function overloading;Data aggregates;String processing, exceptions handling, dealing with namespaces;Object-oriented approach and its vocabulary;Dealing with classes and objects, class hierarchy and inheritance;Defining overloaded operators, user-defined operators, exceptions;Demand and Benefits: Having a CLA certification verifies that the programmer or the aspirant has an understanding of all the necessary and essential universal concepts of computer programming and developer tools. The course also covers all the syntax and semantics of different C constructs plus the data types offered by the language. This course brings crisp knowledge on writing programs using standard language infrastructure regardless of the hardware or software platform.A C++ Certified Associate Programmer (CPA) certification will give you an upper hand because it comprises syntax and semantics of the C++ language plus basic C++ data types. Apart from that, it contains principles of the object-oriented model and C++ implementation. Also, you will get to know about the various C++ standard libraries through this certification process. The average entry-level salary of a C/C++ developer with this certification will be $ 7,415 per annum. With two to three years of experience, the average salary hikes to $ 10,593 annually.Top companies and industries hiring CLA and CPA are Philips, Calsoft Pvt. Ltd., Cognizant, Synopsys Inc., private universities, Mphasis, etc.Where to take Training for Certification: CPP Institute has all the study resources you need to prepare for this examination. Apart from that, you can study from YouTube free resources.Who should take the Training (roles) for Certification: Any programmer or computer science aspirant - who wants to expand their knowledge of C/C++ or start their career as a C/C++ programmer or developer can opt for this certification course. There is no other prerequisite to appear for this exam.Course fees for Certification:CLA Certification: $ 147.50 (50% discount voucher)CPA Certification: $ 147.50 (50% discount voucher)Exam fee for certification:CLA Certification: $ 295CPA Certification: $ 295Retake fee for certification: Aspirants who have paid the complete exam price (USD 295) or have completed a course aligned with certification in the self-study mode (50% discount voucher) can have a free retake of the CPA or CLA exam. There is no limit to the number of times a candidate may retake the exam. You must wait 15 days before being allowed to re-sit that exam.2. Oracle Certified Associate Java Programmer OCAJPThis is a Java programming certification provided by Oracle. Java is among the most popular programming languages. James Gosling is the creator of Java which was earlier named Oak. It is a robust, high-level, general-purpose, pure object-oriented programming language developed by Sun Microsystems (now part of Oracle). Java consistently tops the 'most used programming languages’ list and is one of the most extensively used software development platforms. If you have the plan to get a proper training course online before appearing for the certification exam, KnowledgeHut (https://www.knowledgehut.com/programming/java-training) has that for you.It is the preliminary and most basic certification provided by Oracle for Java. It helps gain fundamental understanding of Java programming and builds a foundation in Java and other general programming concepts. The certification encompasses two subcategories –OCAJP Java Standard Edition 8 (OCAJP 8) and  OCAJP Java Standard Edition 11 (OCAJP 11)It comprises of topics likeJava BasicsWorking with Java Data TypesUsing Operators and Decision ConstructsCreating and Using ArraysUsing Loop ConstructsWorking with Methods and EncapsulationWorking with InheritanceHandling ExceptionsClass Methods and EncapsulationDescribing and Using Objects and ClassesHandling ExceptionsJava Technology and the Java Development EnvironmentInheritance and InterfacesUnderstanding ModulesUsing Operators and Decision ConstructsWorking with Java ArraysWorking with Selected classes, Java Primitive Data Types and String APIsDemand and Benefits: Having an OCAJP certification verifies that the aspirant has all the necessary and essential skills to become an expert Java developer. This certification also helps in getting an internship or entry-level jobs in different organizations. The entry-level salary of a junior Java developer with this certification is $ 3670 per annum; when the candidate gathers two to three years of experience, the average salary hikes to $ 5430 annually.Top companies and industries hiring Oracle Certified Associate Java Programmers are Smart Monitor Pvt. Ltd., Fiserv, Micron Semiconductor Asia Pvt. Ltd., private universities and many others.Where to take Training for Certification: KnowledgeHut has a fascinating course opportunity for beginners in Java programming. It has workshops with hands-on learning and 40 hours of instructor-led online lectures. Apart from that, Oracle also provides exam vouchers for this certification course.Who should take the Training (roles) for Certification: Any programmer or computer science aspirant - who wants to settle as a Java developer or start his/her career as a Java programmer can opt for this certification course. There is no other prerequisite to appear for this exam.Course fee for Certification: $ 245Application fee for certification:OCAJP8: $ 245OCAJP11: $ 249Exam fee for certification:OCAJP8: $ 245OCAJP11: $ 255Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days.3. Certified Associate in Python Programming (PCAP)Python is an interpreted, general-purpose, and high-level programming language developed by Guido Van Rossum. Python released in 1991 and within 5 to 6 years, this programming language become the most popular and widely used programming language in various disciplines. Today, companies use Python for GUI and CLI-based software development, web development (server-side), data science, machine learning, AI, robotics, drone systems, developing cyber-security tools, mathematics, system scripting, etc. PCAP is a professional Python certification credential that measures your competency in using the Python language to create code and your fundamental understanding of object-oriented programming.It comprises of topics likeBasic concepts of PythonOperators & data typesControl and EvaluationsModules and PackagesData AggregatesException HandlingStringsFunctions and ModulesObject-Oriented ProgrammingList Comprehensions, Lambdas, Closures, and I/O OperationsClasses, Objects, and ExceptionsDemand and Benefits: Having a Python certification verifies that the programmer or the aspirant has all the necessary and essential skills needed to become an expert Python developer. This certification also helps in getting an internship or entry-level jobs in different organizations. The average entry-level salary of a Python developer starts at around $100k per annum. With a few years of experience, the average salary hikes to $ 105k annually.Top companies and organizations hiring certified Python programmers are Bank of America, Atlassian, Google, Adobe, Apple, Cisco Systems, Intel, Lyft, IBM, etc.Where to take Training for Certification: KnowledgeHut has a fascinating course opportunity for beginners in Python programming. It has hands-on learning with 24 hours of instructor-led online lectures. Apart from that, the course has 100 hours of MCQs and three live projects.Who should take the Training (roles) for Certification: Any programmer, graduate, post graduate student, or computer science aspirant - who wants to pursue a career as a Python developer or  Python programmer can opt for this certification training. There is no other prerequisite to appear for this exam.Course fees for Certification:  $ 295Exam fee for certification: $ 295Retake fee for certification: If a candidate fails the exam, he/she has to wait for 15 days before being allowed to retake the exam for free. There is no limit to the number of times a candidate may retake an exam.4. MongoDB Certified Developer Associate ExamMongoDB is a NoSQL, document-based high-volume heterogeneous database system. Instead of having tables with rows and columns, MongoDB uses a collection of documents. It is a database development system that provides scalability and flexibility as per query requirements. Its document models are easy to implement for developers and can meet complex demands at scale.MongoDB created this MongoDB Certified Developer Associate Exam for individuals who require to verify their knowledge on fundamentals of designing and building applications using MongoDB. They recommend this certification for those who want to become software engineers and have a solid understanding of core MongoDB along with professional experience.It comprises of topics likeMongoDB BasicsCRUDIndexing and PerformanceThe MongoDB Aggregation FrameworkBasic Cluster AdministrationAggregation & ReplicationShardingMongoDB Performance  MongoDB for Python DevelopersMongoDB for Java Developers or MongoDB for JavaScript DevelopersData ModelingDemand and Benefits: Having a MongoDB Certified Developer Associate Exam certification verifies that the programmer or the aspirant has all the necessary and essential skills to become a NoSQL database expert. The MongoDB certification is inexpensive and in demand. The average salary for a software developer with MongoDB skills starts from $ 8200 per annum.Top companies and organizations hiring certified MongoDB developers are Accenture, Collabera, Leoforce LLC., Adobe, Trigent Software, Lyft, etc.Where to take Training for Certification: KnowledgeHut has a comprehensive course structure for those who want to learn MongoDB & Mongodb Administrator. It has 24+ hours of instructor-led online lectures and 80+ hours of hands-on with cloud labs. This self-paced course also includes capstone projects to give participants a feel of real world working.  Who should take the Training (roles) for Certification: Any programmer, graduate, post graduate student, experienced developer or computer science aspirant - who wants to embark on a career as a MongoDB developer or start his/her career as a NoSQL database expert or do better in their current role as a MongoDB developer can opt for this certification course. There is no other prerequisite to appear for this exam.Course fees for Certification:  $ 150Exam fee for certification: $ 150Retake fee for certification: MongoDB University is no longer allowing a free retake with the exam fee. The candidate has to pay an additional $10 to reschedule or retake the exam.5. R Programming CertificationIt is a part of the data science specialization from Johns Hopkins University under Coursera. This course teaches R programming for efficient data analysis. It covers different R programming concepts like building blocks of R, datatypes, reading data into R from external files, accessing packages, writing functions, debugging techniques, profiling R code, and performing analysis.It comprises of topics like:Basic building blocks in RData types in RControl StructuresScoping Rules - OptimizationCoding StandardsDates and TimesFunctionsLoopingDebugging toolsSimulating data in RR ProfilerDemand and Benefits: Having an R Programming certification verifies that the programmer or the aspirant has all the necessary and essential skills require to get a job role as data analyst. This certification also helps in getting an internship or entry-level jobs in different organizations and firms. The average salary of a certified R programmer with this certification is ₹ 508,224 per annum.Top companies and industries hiring certified R programmers are Technovatrix, CGI Group Inc., Amazon, Sparx IT Solutions, Accenture, Uber, etc.Where to take Training for Certification: KnowledgeHut has a fascinating training course for those who wants to become a R programmer. It has 22+ hours of instructor-led live training and three self-paced live projects.Who should take the Training (roles) for Certification: Any data analyst, graduate, post graduate student, experienced data analyst or computer science aspirant - who wants to settle as a R programmer or data analyst can opt for this certification course. There is no other prerequisite to appear for this exam. Course fees for Certification: FreeFee for certification: $ 60 (Coursera Plus Monthly)Retake fee for certification: Free6. Oracle MySQL Database Administration Training and Certification (CMDBA)It is another course offered by Oracle for SQL developers. Oracle University designed this course for database administrators who want to validate their skills with developing performance, blending business processes, and accomplishing data processing work. Structured Query Language (SQL) is one of the top database management query languages that allows us to access and manipulate databases. If you want to verify your database skills during a job interview or impress your peers at your workplace then this certification is worth getting. This certification path includes Professional, Specialist, and Developer levels. The candidate should pass the MySQL Database Administrator Certified Professional Exam Part 1 & Part 2 to earn the certification.It comprises of topics likeInstalling MySQLMySQL ArchitectureConfiguring MySQLUser ManagementMySQL SecurityMaintaining a Stable SystemOptimizing Query PerformanceBackup StrategiesConfiguring a Replication TopologyDemand and Benefits: Having an CMDBA certification verifies that the programmer or the aspirant has all the necessary and essential skills required to get a job role as SQL developer. This certification also helps in getting an internship or entry-level jobs in different organizations and firms. The average salary of a certified MySQL DBA or backend developer with this certification is $ 66,470 per annum.Top companies and industries hiring Certified MySQL database administrators are Fiserv, IBM, HCL, Adobe, Microsoft, Apple, Accenture, Collabera, and more.Where to take Training for Certification: KnowledgeHut has a cutting-edge curriculum for those who want to become  MySQL database administrators. It has 16+ hours of instructor-led online lectures and 80+ hours of hands-on lab. Apart from that, this self-paced course has Capstone projects.Who should take the Training (roles) for Certification: Any developer, graduate, post graduate student, experienced developer or computer science aspirant - who wants to pursue a career as a DBA or backend developer or start his/her career in database management or backend software development can opt for this certification course. There is no other prerequisite to appear for this exam or course.Course fees for Certification: $ 255Exam fee for certification: $ 255Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days after the initial attempt.7. CCA Spark and Hadoop DeveloperWith the exponential growth in data, IT firms and organizations have to manage this tremendous amount of data generated. So, many companies are actively looking for Big data and Spark developers who can optimize performance. Big Data is the term used to describe enormous volumes of data. Apache Spark supports data management as it is an open-source centralized analytics engine that handles large-scale data processing.It requires prerequisite knowledge of Scala and Python. This certification also verifies and showcases your skills through Spark and Hadoop projects. Passing this certification course gives you a logo and a license to authenticate your CCA status.It comprises of topics likeLoad data from HDFS for use in Spark applicationsWrite the results back into HDFS using SparkRead and write files in a variety of file formatsPerform standard extract, transform, load (ETL) processes on data using the Spark APIUse metastore tables as an input source or an output sink for Spark applicationsUnderstand the fundamentals of querying datasets in SparkFilter data using SparkWrite queries that calculate aggregate statisticsJoin disparate datasets using SparkProduce ranked or sorted dataSupply command-line options to change your application configuration, such as increasing available memoryDemand and Benefits: Passing the CCA Spark and Hadoop Developer Exam (CCA175) by Cloudera verifies that you have all the essential skills required to get a job as a Hadoop developer and handle Big data projects. The average salary of a certified CCA Spark and Hadoop Developer with this certification is $ 74,200 per annum.Top companies and industries hiring Certified Spark and Hadoop Developers are Primus Global, IBM, Collabera, CorroHealth, Genpact, Xerox, Accenture, and more.Where to take Training for Certification: KnowledgeHut has extensive courses for those who want to become Big Data experts and want to work as Hadoop developers. It has different courses on Big Data Analytics, Apache Storm, Hadoop Administration, Apache Spark & Scala, Big Data with Hadoop, and more.Who should take the Training (roles) for Certification: Any Big Data developer, graduate & post graduate students, Hadoop developer or computer science aspirant - who wants to make a career in Big data development or start his/her career as a Big Data or Hadoop project developer can opt for this certification course. There is no other prerequisite to appear for this exam.Course fees for Certification: $ 295Application fee for certification: $ 295Exam fee for certification: $ 295Retake fee for certification: Within 30 to 60 minutes of exam completion, Cloudera will send a scorecard mail with a pass or fail status. If the candidate fails the exam, then they have to wait for 30 days for another try.  Cloudera gives additional discounts on retakes.ConclusionWhether you are starting your career as a coder or are an experienced programmer looking to grow in the industry, having a certification and proper knowledge of any popular programming language is one of the most proven ways to elevate your programming career.  We trust that this article will help you to understand your area of interest. Choose the programming language you wish to make a career in, wisely. This would also depend on your pre-existing knowledge. If you aren't sure which resource will be more informative for doing your certification as per your area of interest, KnowledgeHut (https://www.knowledgehut.com/) has all the support and expert trainers who can guide you, from start to finish—that is in clearing the exam and helping you gain sound knowledge of your preferred subject.Receiving a programming certification is an added bonus which will make you stand out from the rest. Proper training from an institute such as KnowledgeHut will help you gain skills that are relevant and in demand in the industry.
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Top-Paying Programming Certifications for 2021

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Top IT Certifications for Java Developers in 2021

Programming languages are at the heart of computer science and software development. They help developers write efficient code for developing digital solutions through applications and websites. Programming helps in automating, maintaining, assembling, and measuring the processed data.  Java is one such popular programming language. It is a robust, high-level, general-purpose, pure object-oriented programming language developed by Sun Microsystems (now part of Oracle). James Gosling is the creator of Java which was earlier named Oak. Java ranks high in the top programming languages list and is one of the most extensively used software development platforms. It is well suited to developing software solutions and other innovative projects and simulations.  Since Oracle acquired Sun Microsystems in January 2010, they have been responsible for the further development of the Java platform. All the mentioned top Java certifications verify a specific expertise level and knowledge of the Java platform highlighting particular domains. Without further due, let us now dig into the top 5 Java certifications and their details. About Oracle’s Java CertificationsOrganizations and industries consider certifications as proof of knowledge, especially when the certifications are from a recognized body or firm. Aspirants and professionals looking for possibilities in the Java development domain can avail of a plethora of benefits through the certifications mentioned in this article. There are six levels of Oracle Java Certification based on job roles, skills, and responsibilities: Oracle Certified Junior Associate (OCJA) Oracle Certified Associate (OCA) Oracle Certified Professional (OCP) Oracle Certified Specialist (OCS) Oracle Certified Expert (OCE) Oracle Certified Master (OCM) Among them, the top five Java certifications that are in demand for the year 2021 are – 1. Oracle Certified Associate Java Programmer OCAJPIt is the preliminary and most basic certification provided by Oracle for Java. It helps you gain fundamental understanding of Java programming and build a foundation in Java and other general programming concepts. There are two subcategories in this certification – OCAJP Java Standard Edition 8 (OCAJP 8) and  OCAJP Java Standard Edition 11 (OCAJP 11) OCAJP8 comprises of topics like  Creating and Using Arrays Handling Exceptions Java Basics Using Loop Constructs Using Operators and Decision Constructs Working with Inheritance Working with Java Data Types Working with Methods and Encapsulation Working with Selected classes from the Java API OCAJP11 comprises of topics like Applying Encapsulation Creating and Using Methods Creating Simple Java Programs Describing and Using Objects and Classes Handling Exceptions Java Technology and the Java Development Environment Programming Abstractly Through Interfaces Reusing Implementations Through Inheritance Understanding Modules Using Operators and Decision Constructs Working with Java Arrays Working with Java Primitive Data Types and String APIs Demand and Benefits: Having an OCAJP certification verifies that the programmer or the aspirant has all the necessary and essential skills to become an expert Java developer. This certification also helps in getting an internship or entry-level jobs in different organizations. The entry-level salary of a junior Java developer with this certification is $ 3670 per annum; when the candidate gathers two to three years of experience, the average salary hikes to $ 5430 annually.   (Source: Glassdoor) Top companies and industries hiring Oracle Certified Associate Java Programmers are Smart Monitor Pvt. Ltd., Fiserv, Micron Semiconductor Asia Pvt. Ltd., and more. Where to take Training for Certification: KnowledgeHut has a fascinating course, designed for beginners in Java programming. It offers hands-on learning with 40 hours of instructor-led online lectures. Apart from that, Oracle also provides exam vouchers for this certification course. Who should take the Training (roles) for Certification: Any programmer or computer science aspirant - who wants to be a Java developer or start his/her career as a Java programmer can opt for this certification course. There is no other prerequisite to appear for this exam. Course fees for Certification:  $ 245 Application fee for certification: $ 245 Exam fee for certification: $ 245 Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days. 2) Oracle Certified Professional Java Programmer OCPJPIt is a professional-level certification program provided by Oracle for Java developers. It verifies the candidates' knowledge and professional expertise. Using this certification, aspirants and other hard-core Java programmers can distinguish themselves from those Java professionals who are not certified. It comes in the second level of Oracle's Java Certification list. There are two subcategories of this certification – OCPJP Java Standard Edition 8 (OCPJP 8) and  OCPJP Java Standard Edition 11 (OCPJP 11) This certification is preferable if someone has professional experience with Java or has already worked for some years in Java technology.  OCPJP8 comprises of topics like: Advanced Class Design Building Database Applications with JDBC Concurrency Exceptions and Assertions Generics and Collections Java Class Design Java File I/O (NIO.2) Java I/O Fundamentals Java Stream API Lambda Built-in Functional Interfaces Localization Use Java SE 8 Date/Time API OCPJP11 comprises of topics like: Annotations Built-in Functional Interfaces Concurrency Database Applications with JDBC Exception Handling and Assertions Functional Interface and Lambda Expressions Generics and Collections I/O (Fundamentals and NIO.2) Java Fundamentals Java Interfaces Java Stream API Lambda Operations on Streams Localization Migration to a Modular Application Parallel Systems Secure Coding in Java SE Application Services in a Modular ApplicationDemand and Benefits: Once you are a certified Professional Java Programmer (OCPJP), you can switch to better salary slabs and organizations that hire senior Java developers. This certification also helps in getting internal promotions as Java developers in different organizations and firms. The average salary of a certified professional Java developer is $ 5300 - $ 8610 per annum. Top companies and industries hiring Oracle Certified Professional Java Programmers are Oracle, Capgemini, Morgan Stanley, Chetu, Mphasis, etc. Where to take Training for Certification: KnowledgeHut has a fascinating course opportunity for Java developers and professionals for learning intermediate Java topics. It has hands-on learning with 32 hours of instructor-led online lectures. Apart from that, Oracle also provides exam vouchers for this certification course. Who should take the Training (roles) for Certification: Any Java programmer who wants to apply for a senior Java developer's role or start his/her career as a Java programmer can opt for this professional certification course. There is no other prerequisite to appear for this exam. Course fees for Certification: $ 245 Application fee for certification: $ 245 Exam fee for certification: $ 245 Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days.3. Oracle Certified Expert - Web Component Developer OCEWCDIt is an intermediate-level course offered by Oracle for Java web developers. The Oracle Certified Expert Web Component Developer is for web developers who want to write web applications using Java. Through this course, they can prove their expertise in developing web apps using JSP and Servlet technologies. It verifies your expertise in Servlet 3.0 and helps in creating dynamic Web content and Web services.  It comprises of topics like Understanding Java EE Architecture Managing Persistence using JPA entities and Bean Validation Implementing business logic using EJBs Using Java Message Service API Implement SOAP Services using JAX-WS and JAXB APIs Creating Java Web Applications using Servlets and JSPs Implementing REST Services using JAX-RS API Creating Java Applications using WebSockets Developing Web Applications using JSFs Securing Java EE 7 Applications Using CDI Beans Demand and Benefits: You can opt for this course once you are a certified Professional Java Programmer (OCPJP) or certified associated Java programmer. This certification course will help you get a job in organizations having rigorous work in Servlet, Java Server Page, JSF, and web microservices. The average salary of a certified professional Java developer is $ 8,850 - $ 11,930 per annum. Top companies and industries hiring Oracle Certified Web Component Developers are Amdocs, IBM, Oracle, Capgemini, SAP, Shine, Byjus, etc. Where to take Training for Certification: KnowledgeHut has a fascinating course opportunity for Java web developers (. It has hands-on learning with instructor-led online lectures and live projects. Apart from this, you can get online training from Oracle University as wellWho should take the Training (roles) for Certification: Any programmer or computer science aspirant who wants to settle as a Java web developer or start his/her career as a Java web content and web service developer can opt for this certification course. As a prerequisite, you have to pass the OCPJP to opt for this certification.  Course fees for Certification:  $ 245 Application fee for certification: $ 245 Exam fee for certification: $ 245 Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days. 4. Oracle Certified Professional Java Application Developer (OCPJAD)It is an advanced-level course offered by Oracle for Java application developers. The Oracle Certified Professional Java Application Developer (OCPJAD) is for software developers who want to write different applications and automation tools using Java. Through this course, developers can prove their expertise and abilities to develop and deploy applications through Java Enterprise Edition 7. OCPJAD is ideal for desktop application developers, frontend + backend app developers, software engineers, and application architects. It comprises of topics like Creating Batch API Developing CDI Beans Concepts of Concurrency Creating Java Applications with Web-Sockets Creating Java Web Applications with JSPs Developing Java Web Applications with Servlets Developing Web Applications with JSFs Implementing Business Logic with EJBs Performing REST Services with JAX-RS API Implementing SOAP Services with JAX-WS and JAXB APIs Java EE 7 system architecture Java EE 7 Security Techniques Java Message Service API Managing Persistence with JPA Entities and Bean-ValidationDemand and Benefits: Once you pass the Certified Professional Java Application Developer (OCPJAD), you can seek employment in organizations that work on critical application development and command higher salaries. This professional certification will give you exposure to develop APIs, implementing business logic using EJBs, create message services, and apply security systems. The average salary of a certified professional application developer is $ 9,800 - $ 13,910 per annum. Top companies and industries hiring Oracle Certified Professional Java Programmers are Oracle, Capgemini, NetSuite Inc., SAP, Cognizant, etc. Where to take Training for Certification: KnowledgeHut has a fascinating course opportunity with hands-on learning exposure and live projects. Apart from this, you can get online training from Oracle University as well. Who should take the Training (roles) for Certification: Any Java developer or full-stack application developer who wants to become a certified Java application developer or move to the specialized sector of API development using REST, security architect or software engineer can opt for this certification course. As a prerequisite, you should have passed the OCAJP certification.  Course fees for Certification:  $ 245 Application fee for certification: $ 245 Exam fee for certification: $ 245 Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days.5. Oracle Certified Master Java Enterprise Architect (OCMJEA)Large-scale development and service firms have different critical applications and systems to develop, manage, and maintain. Such systems require full-stack developers and specialized professionals with proven skills. Such organizations and MNCs hire only highly experienced professionals and specialists who can supervise the extensive operation, architect the defects, and define & develop systems as per requirements. The Oracle Certified Master Java Enterprise Architect (OCMJEA) is one of the most prestigious Java certifications a Java developer can achieve.  It comprises of topics like Architect Enterprise Applications through Java EE Developing Applications for the Java EE 6 Developing Applications for the Java EE 7 Developing Applications with Java EE 6 on WebLogic Server 12c Java Design Patterns Java EE 6: Develop Business Components with JMS & EJBs Java EE 6: Develop Database Applications with JPA Java EE 6: Develop Web Services with JAX-WS & JAX-RS Java EE 7: New Features Java SE 7: Develop Rich Client Applications Java SE 8: Programming Java SE 8 Fundamentals Object-Oriented Analysis and Design Using UML, etc. Demand and Benefits: Once you pass the Certified Master Java Enterprise Architect course, you get the essential skills and understanding of how to execute application development on an enterprise level. Such an experienced professional gains full-stack Java development skills. They get hired with the responsibility of undertaking Java projects from the very start to their final delivery. Many Certified Master Java Enterprise Architects work as managers or senior managerial roles in industries and firms. The average salary of a certified professional application developer is $ 14,000 - $ 19,210 per annum. Top companies and industries hiring Oracle Certified Professional Java Programmers are IBM, Oracle, Microsoft, HCL, Capgemini, NetSuite Inc., SAP, Cognizant, Atlassian, etc. Where to take Training for Certification: KnowledgeHut has a fascinating Java course  with hands-on learning exposure and a live project. Apart from that, a professional can train himself through ILT (Instructor-Led-in-Class), Learning Subscription, TOD (Training on Demand), LVC (Live Virtual Class), or classes delivered by Oracle Authorized Education Center . Other Oracle Authorized Partner Oracle Academy, Oracle University Training Center, or Oracle Workforce Development Program can also benefit and train you in this course.  Who should take the Training (roles) for Certification: Any Java developer or full-stack application developer who wants to move to a senior role in the enterprise-level or want to become a manager or team lead can opt for this certification course. As a prerequisite, you need to have passed the OCPJP certification.  Course fees for Certification:  $248 Application fee for certification: $ 248 Exam fee for certification: $ 248 Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days. Java is an evergreen programming language and is here to stay, at least for the next couple of decades. A vast community of professionals and entry-level aspirants enjoy the benefit of this pure object-oriented, class-based, multi-paradigm, high-level programming language. Java Certification requires proper training.KnowledgeHut has the required infrastructure and quality education faculty, both online and offline, to train aspirants for these Oracle Certifications. It caters to well-structured, industry-oriented Java certification training, explicitly designed to serve the candidates according to the latest industry needs. Getting proper training from KnowledgeHut will help aspirants master core knowledge of Java plus equip themselves with the industry standards to manage large projects. 
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Top IT Certifications for Java Developers in 2021

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