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What is Python, it's basics and getting started with Python

Learning something new is always interesting and exciting but how to learn makes it challenging. It is believed that learning how to learn is the most critical task while learning a new programming language. A proper strategy to learn makes the journey easier and smooth. Let us look into such essential learning strategies which will help you learn the basics of Python and guide you through the journey of becoming a programmer.Code Regularly: It is important for a beginner to practice Python coding on a regular basis which will develop a muscle memory. At first it might seem to be difficult but a regular practice of half an hour will make your basics stronger.Use Pen and Paper: Many learners have this question in mind, whether they should write codes using a pen and paper or not. It is recommended to write codes or take notes by hand as it is beneficial for long-term retention as you get a firm hold over writing flawless codes. Also, in a lot of interviews, you are asked to write codes on a white board.Program as a Pair: With a friend or another learner completing a task together is called pair programming. It is a technique where two developers work at a single workstation. One of the developers should be the “driver” and the other should be the “navigator”. The “driver” writes the code, while the “navigator” helps guide the problem solving and reviews the code as it is written. Both the developers should switch between the roles.Build new things: There are a lot of short exercises for beginners which will make you confident with Python. You should have good knowledge about basic data structures (strings, lists, dictionaries, sets), object-oriented programming, and writing classes. Here, let us discuss about what Python is all about, how to get started with Python and learn about the basics of Python.What is Python?Python is an interpreted, interactive, object-oriented and multi-purpose programming language created by Guido Van Rossum in the late 1980s. It is a programming language— a language which people and computers both can understand. It is powerful and has an easy-to-use syntax, making it perfect for beginners.Python is a flexible language which has the ability to write simple programs and also create large complex programming solutions. It is used extensively for web and internet developments, for mathematical and scientific computations of data and also in the field of game and graphics development. Some of the popular websites that use Python are Youtube, Instagram, Dropbox, Pinterest etc. Join the certification course on Python Programming to learn more about Python and its capabilities.Why Choose Python?Whether you’re a beginner to programming or an experienced programmer designing a complex application, Python is a great choice because of its easily understandable nature and vast capabilities. Some of the features of Python that make it irresistible to users:Popularity: Python is considered as the 4th most popular and fastest growing programming language according to the Stack Overflow Developer Survey 2019. Python is used by the world’s most renowned Software Companies like Google, YouTube, Instagram, Netflix, Spotify, Quora and much more.Interpretation: Python is an interpreted language which means the programs are passed straight to the interpreter which executes them directly; unlike compilers where the source code is converted to machine code before running.OpenSource: Python is a free language developed under OSI-approved open-source license which makes it free to use and distribute even for commercial purposes.Portability: Python code is portable, which means the code written in one platform will work in any other platform, having the Python interpreter installed.Simplicity: Python’s coding style is very simple and clean which makes it easy to read and learn. It uses less keywords compared to other languages like C++ or Java. Developers tend to use it all the time because of its neat and organized code structure.How to Get Python?Python is an open-source software that comes pre-installed in Mac and works on most distributions of Linux and other platforms. However, you might need to download the latest version to get the most out of it.Choosing Python Presently, there are two major versions of Python - 2.x and 3.x. However, at an early stage, you can use either of the two because there are very few differences between them. Also once you have learned one, the other one won’t be difficult to learn.In simple terms, if you’re starting to learn Python, the latest version 3.7.x would be more suitable since it comes with extra features with a number of bug fixes. On the other hand, you can use the version 2.7.x when you need support from third-party libraries to perform your task.Installing PythonYou can download the specific version of Python that suits your OS and processor (32-bit or 64-bit) from the Python Software Foundation (PSF).Installation pertaining to OS requirement:Windows: In any Windows platform, you can directly download Python software from the PSF.Linux: You can download the latest version of Python on Linux in the same manner. However, you can also use a package manner, if needed.Mac: For Mac systems, download the software from PSF and then install it. Moreover, it is suggested to use a package manager like Homebrew for installing and managing different versions of Python.Python ShellAfter you have successfully installed Python in your system, you can check whether it is installed or not using the Python Interactive Shell:Windows: Open the terminal and type python for Python 2.7 or py -3 for Python 3.Linux: Open your terminal and simply run python.Mac: Depending on the version of Python you’ve installed, open your terminal and run python or python3.The command prompt or the terminal will look somewhat like this:Python 3.7.2 (tags/v3.7.2:9a3ffc0492, Dec 23 2018, 23:09:21) [MSC v.1916 64 bit (AMD64)] on win32 Type "help", "copyright", "credits" or "license" for more information. >>>You can use the exit() to leave the Python shell or you can also use CTRL + D and then press the ENTER key to terminate the command prompt.What are the Basics of Python?Python is a very beautiful language and feels very natural to work with. It consists of a number of coding basics. Let us first start by running the universal Hello World program.The Hello World ProgramIf you want to display a line in the terminal, you can do so by using the print statement:>>> print("HELLO WORLD!")The output will be displayed as follows:HELLO WORLD!VariablesVariables are defined as containers or memory locations for storing data. The syntax of declaring a variable is variable_name = variable_value. However, it is recommended to use variables names like num1, my_int or mystring other than simple variables like x or y.Sensible names gives a clear indication of the type of variable and it is also useful for others to understand your code clearly. Thinking of others while writing your program will improve your coding skills.Built-in Data TypesPython comprises of many built-in data types starting from numbers, strings, lists, tuples and dictionaries.NumbersPython supports many types of numbers like integers (1, 2, 55, 599, -99), floating points (1.0, 5.55,  661.1, -99.9),  Booleans (True or False) or complex numbers. We can perform addition and subtraction with numbers just like normal addition and subtraction we learnt in our school:>>> 1 + 5   # Addition 6 >>> num1 = 5 >>> num2 = 5.01 >>> num3 = num1 + num2 >>> 10 - 5   # Subtraction 5We can also compare numbers that will result in a boolean value:>>> 1 < 3 True >>> 4 > 5 FalsePython consists of a number of built-in functions that you can use to handle numbers:>>> float(13) 13.0A float() function takes an integer and returns a floating point number.Other than functions, Python also has a number of data-type methods connected to each type of number. float.is_integer() is a data-type method which checks whether a floating point number is finite or not:>>> (10.1).is_integer() False >>> (5.0).is_integer() True StringsA String is a list of characters in an organized manner. A character can be a number or letter or even a backslash. In simple words, they are lines enclosed in single or double quotes:>>> string1 = "hello" >>> string 'hello' >>> string2 = 'hey' >>> string2 "hey"In Python, we can combine strings in a series without any gaps. This is called Concatenation:>>> "Python is" + "easy" 'Python is easy'We can also manipulate strings using functions:>>> len('Python') 6Here, len() is a function that takes a string as an input and returns the size of the string.Data-type methods also exist for handling strings. string.capitalize() takes an input string and returns by capitalizing the first string:>>> lower_case_string = 'python' >>> lower_case_string.capitalize() 'Python' >>> ('the Avengers').capitalize() 'The Avengers' ListsA list is an ordered sequence of elements in Python. Each element in a list is known as an item. They are similar to array in C or C++.Lists may consist of any data type like numbers or strings mixed together, or other lists or they may be empty too. The syntax is usual:>>> create_a_list = [] >>> list_of_numbers = [1, 5, 10, 1000] >>> list_of_numbers [1, 5, 10, 1000] >>> list = ["ironman", "thor", "hulk"] >>> list ['ironman', 'thor', 'hulk'] >>> mixed_list = ["Python", [1, 2, 3], True] >>> mixed_list ['Python', [1, 2, 3], True]Elements of lists can be accessed either from the start or the end. Also, you can create a new list just by accessing the elements:>>> list_of_numbers = [1, 5, 10, 1000] >>> new_list = list_of_numbers[0:2] >>> new_list [1, 5]Concatenation of lists using operators:>>> marvel = ["ironman", "thor", "hulk"] >>> dc = ["superman", "batman", "flash"] >>> multiverse = marvel + dc >>> multiverse [‘ironman’, ‘thor’, ‘hulk’, ‘superman’, ‘batman’, ‘flash’]The function of lists works in the same manner as of strings:>>> list_of_numbers = [1, 5, 10, 1000] >>> len(list_of_numbers) 4len() returns the size of the list.Data-type methods like list.sort() and list.append() are used to sort  and append lists:#append >>> stationary = ["inkpen", "pencil", "eraser"] >>> stationary.append("sharpener") >>> fruits ['inkpen', 'pencil', 'eraser', 'sharpener']#sort>>> stationary.sort()>>> stationary[ 'eraser', 'inkpen', 'pencil', 'sharpener']TuplesTuples are sequence of Python objects that cannot be changed after creation. They are similar to lists, the only difference being that lists are mutable.An example of a tuple:my_tuple = ("Alex", "Blanc", 27, "Technical Blogger")You can concatenate two tuples using operators just like lists:>>> tuple1 = (11, 29) >>> tuple2 = (30, 90) >>> tuple3 = tuple1 + tuple1 >>> tuple3 (11, 29, 30, 90)You can convert a tuple into a list by using the function list():>>> tuple1 = (100, 500)>>> list(tuple1)[100, 500]Since tuples cannot be changed after it is created, most of the data-type methods like sort() or append() or reverse() will not work on tuples.DictionaryA dictionary in Python is an unordered collection of associative arrays (or objects).An example of a dictionary of phone numbers:>>> phonebook = {} >>> phonebook["Alex"] = 9038478766 >>> phonebook["Bob"] = 9098379264 >>> phonebook["Charlie"] = 9017652781ConditionsA conditional statement is a statement that handles the flow of execution depending on some condition.Statements can be compared or evaluated in Python using boolean expressions as follows:>>> x = 5 >>> print(x == 5) # prints True >>> print(x == 2) # prints FalseYou can also use the if-else statements to check if a statement is true or not:>>>if 2 > 3:   print("2 is greater than 3")   else:   print("2 is not greater than 3")LoopsYou can use loops when you want to repeat a block of code in a fixed number of time. You can iterate in two different ways, the first is by using the while loop:>>> num = 1 >>> while num <= 5:     print(num)     num = num + 1While the statement is true, the loop will iterate and the code will be executed. It will print the number from 1 to 5.Another way of implementing a loop is using the for statement:>>> for num in range(1, 10):     print(num) Here, the range starts from 1 and goes until 10. The loop iterates 10 times over the statement.FunctionsFunctions in Python are a block of organized code which is useful in performing a single action. Syntax of defining a function is def function_name.An example of a function is:>>> def my_first_function(): print("HELLO WORLD!")You can also return a value to the caller in a function using the return statement:>>> def multiply_by_2(a): return a * 2Classes and ObjectsAn object in Python is a collection of variables and methods. A class is a blueprint for the object.For example, we can consider a prototype of a house as the class. It consists of all the details of the floors, walls, doors, windows etc. We can build the house on the basis of the details. So, house becomes the object. Objects are instances of a class.You can define a class in Python using the keyword class as follows: >>> class My_First_Class:     my_variable = "blah"You can create an object in Python which can be used to access different attributes of a class. This process of creating new object instances is called instantiation.An example to illustrate that:class My_First_Class: def func(self): print('Hello') ob = My_First_Class() #creating a class objectModules and PackagesA module is a single file (or files) that are imported under one import and then used. In simple words, any Python file is a module. On the other hand, packages are simple directories consisting of multiple modules and packages themselves.Python consists of a number of packages and modules to increase the extent of the language. Some of the useful built-in Python modules are:math: This module gives access to mathematical functions from the standard library of C.random: This module is a pseudo-random number generator.datetime: This module comprises of classes by which you can manipulate dates and times.Pip is the standard package manager which is used to handle Python’s third party packages and modules in an efficient manner. It allows you to install the packages that are not part of the Python Standard Library. You can download Pip from pypi.org.CommentsComments can be in the form of module-level docstrings or inline explanations that are used to describe your code in a clear manner so that developers can understand. It starts with a hash (#) character and can extend to the end of the line.An example of a simple comment:# This is a commentAn example of an inline comment:variable = "Hello World"  # This is an inline commentErrors and Exceptions Python consists of two types of errors:Syntax errors.Exceptions or errors during execution.Syntax ErrorsSyntax errors occur when the Python parser is unable to understand a line of code. Most syntax errors occur because of incorrect indentation or arguments.An example to illustrate such:>>> if 2 < 5   File "<stdin>", line 1      if 2 < 5              ^ SyntaxError: invalid syntaxHere, the if statement is missing a colon(:)at the end of the statement which results into a syntax error.ExceptionsErrors that occur during execution are known as exceptions. There are a number of built-in exceptions in Python.An example of an exception:>>> prices = { 'Pen' : 10, 'Pencil' : 5, 'Notebook' : 25} >>> prices['Eraser'] Traceback (most recent call last):   File "<pyshell#1>", line 1, in <module>     prices['Eraser'] KeyError: 'Eraser'Here, dictionary prices is declared with the prices of three items. The KeyError is raised when the item ‘Eraser’ is being accessed which is not present in prices. Learn more about exceptions in our blog- Python KeyError Exceptions and How to Handle Them.Semantic ErrorsA semantic error, also known as logic error, is an error that occurs because of an incorrect logic. They are much more difficult to catch as compared to syntax errors.These type of errors are complex in nature and generate incorrect or no output. The most common example of a semantic error is an infinite loop. Programmers in their early stage of learning encounter an infinite loop at least once.What are the Different ways of Coding in Python?When you’re in the process of learning a new programming language, you might want things to be simple and your path of becoming a good programmer to be smooth and clear. The first approach to this will be choosing an efficient way of running and executing code in Python.There are mainly three primary approaches to coding in Python— the shell, IDLE and the code editor.The ShellPython provides the Python Shell, which is useful for simple, one-line statements. It waits for the input commands from the user and returns the result of the execution. It is the least powerful among the three.You can open shell in your system and run the following command:>>> 11 + 9 20 Here, the Python Shell evaluated the statement 11 + 9 , performed the addition operation and displayed the result 20.Another example of coding in shell:>>> import thisWhen you execute this statement, you can see the Zen of Python. It is a collection of 19 principles which acts as a guide to write idiomatic Python code.However, the shell has a drawback. The code written in a Python Shell is not persistent which means the code cannot be reused. IDLEIDLE stands for Integrated Development and Learning Environment. It is similar to the shell and contains both the Shell window and the Editor Window. You can create and save Python code because the IDLE allows code reusability. However, it still stands second in the rank powerfulness. Code EditorA code editor is the most powerful among all the three. It is a text-editor program that is useful in editing source codes of computer programs. A code editor can be a single application or act as an Integrated Development Environment or IDE.There are a lot of code editors available in the market. Choosing a code-editor for your task might be a time-consuming work. However, you can take into consideration some factors while choosing a code editor like easy to use, line numbering, auto-indentation, highlighting of syntax and availability of adding extra features.One of the most powerful and popular cross-platform code editor is the Sublime Text.  Other code editors might include gedit,  which is a bit simpler than Sublime. You can also use Notepad++, however it is only for Windows.ConclusionLet’s sum up what we have learnt so far in this article:What is Python programming and what is the need.How to install and run Python.What are the primitives of the Python programming language.What are the ways of Python coding.Though you have learned the basics of the Python Programming Language, here are some tricks and tricks for you remember while coding in Python—Good coding is happy coding. Good code depends on the way you write a code. The key to a good code is to maintain a proper style. You can go through the blog on How To Write Beautiful Python Code With PEP 8 which focuses on enhancing the readability and consistency of code.The logic is the most crucial part when you’re writing a program. If you have a clear understanding of the concepts, you can easily shape your code into a logical program. And the most effective way to do that is to logically break your problem into different parts and then solve it one by one.The best way of learning how to code is by building a project-driven learning approach. There are a lot of free resources, online courses, books and tutorials available. You can refer to the official Python documents - Python 2.7 or Python 3 for more information.You can also join the Python certification course offered by KnowledgeHut.And last but not the least, always keep brushing up the concepts. As a beginner, you might face difficulties in every step, but always try and resolve your issues on your own. Test your skills and take up new challenges everyday.

What is Python, it's basics and getting started with Python

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What is Python, it's basics and getting started with Python

Learning something new is always interesting and exciting but how to learn makes it challenging. It is believed that learning how to learn is the most critical task while learning a new programming language. A proper strategy to learn makes the journey easier and smooth. Let us look into such essential learning strategies which will help you learn the basics of Python and guide you through the journey of becoming a programmer.

  • Code Regularly: It is important for a beginner to practice Python coding on a regular basis which will develop a muscle memory. At first it might seem to be difficult but a regular practice of half an hour will make your basics stronger.
  • Use Pen and Paper: Many learners have this question in mind, whether they should write codes using a pen and paper or not. It is recommended to write codes or take notes by hand as it is beneficial for long-term retention as you get a firm hold over writing flawless codes. Also, in a lot of interviews, you are asked to write codes on a white board.
  • Program as a Pair: With a friend or another learner completing a task together is called pair programming. It is a technique where two developers work at a single workstation. One of the developers should be the “driver” and the other should be the “navigator”. The “driver” writes the code, while the “navigator” helps guide the problem solving and reviews the code as it is written. Both the developers should switch between the roles.
  • Build new things: There are a lot of short exercises for beginners which will make you confident with Python. You should have good knowledge about basic data structures (strings, lists, dictionaries, sets), object-oriented programming, and writing classes. Here, let us discuss about what Python is all about, how to get started with Python and learn about the basics of Python.

What is Python?

What is Python? Python is an interactive, object-oriented & multi purpose programming language which is easy to understand & use.

Python is an interpreted, interactive, object-oriented and multi-purpose programming language created by Guido Van Rossum in the late 1980s. It is a programming language— a language which people and computers both can understand. It is powerful and has an easy-to-use syntax, making it perfect for beginners.

Python is a flexible language which has the ability to write simple programs and also create large complex programming solutions. It is used extensively for web and internet developments, for mathematical and scientific computations of data and also in the field of game and graphics development. Some of the popular websites that use Python are Youtube, Instagram, Dropbox, Pinterest etc. Join the certification course on Python Programming to learn more about Python and its capabilities.

Why Choose Python?

Why to Choose Python? Popularity, Interpretation, OpenSource, Portability and Simplicity.

Whether you’re a beginner to programming or an experienced programmer designing a complex application, Python is a great choice because of its easily understandable nature and vast capabilities. 

Some of the features of Python that make it irresistible to users:

  • Popularity: Python is considered as the 4th most popular and fastest growing programming language according to the Stack Overflow Developer Survey 2019. Python is used by the world’s most renowned Software Companies like Google, YouTube, Instagram, Netflix, Spotify, Quora and much more.
  • Interpretation: Python is an interpreted language which means the programs are passed straight to the interpreter which executes them directly; unlike compilers where the source code is converted to machine code before running.
  • OpenSource: Python is a free language developed under OSI-approved open-source license which makes it free to use and distribute even for commercial purposes.
  • Portability: Python code is portable, which means the code written in one platform will work in any other platform, having the Python interpreter installed.
  • Simplicity: Python’s coding style is very simple and clean which makes it easy to read and learn. It uses less keywords compared to other languages like C++ or Java. Developers tend to use it all the time because of its neat and organized code structure.

How to Get Python?

Python is an open-source software that comes pre-installed in Mac and works on most distributions of Linux and other platforms. However, you might need to download the latest version to get the most out of it.

Choosing Python 

Presently, there are two major versions of Python - 2.x and 3.x. However, at an early stage, you can use either of the two because there are very few differences between them. Also once you have learned one, the other one won’t be difficult to learn.

In simple terms, if you’re starting to learn Python, the latest version 3.7.x would be more suitable since it comes with extra features with a number of bug fixes. On the other hand, you can use the version 2.7.x when you need support from third-party libraries to perform your task.

Installing Python

You can download the specific version of Python that suits your OS and processor (32-bit or 64-bit) from the Python Software Foundation (PSF).

Installation pertaining to OS requirement:

  • Windows: In any Windows platform, you can directly download Python software from the PSF.
  • Linux: You can download the latest version of Python on Linux in the same manner. However, you can also use a package manner, if needed.
  • Mac: For Mac systems, download the software from PSF and then install it. Moreover, it is suggested to use a package manager like Homebrew for installing and managing different versions of Python.

Python Shell

After you have successfully installed Python in your system, you can check whether it is installed or not using the Python Interactive Shell:

  • Windows: Open the terminal and type python for Python 2.7 or py -3 for Python 3.
  • Linux: Open your terminal and simply run python.
  • Mac: Depending on the version of Python you’ve installed, open your terminal and run python or python3.

The command prompt or the terminal will look somewhat like this:

Python 3.7.2 (tags/v3.7.2:9a3ffc0492, Dec 23 2018, 23:09:21)
[MSC v.1916 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>>

You can use the exit() to leave the Python shell or you can also use CTRL + D and then press the ENTER key to terminate the command prompt.

What are the Basics of Python?

Python is a very beautiful language and feels very natural to work with. It consists of a number of coding basics. Let us first start by running the universal Hello World program.

The Hello World Program

If you want to display a line in the terminal, you can do so by using the print statement:

>>> print("HELLO WORLD!")

The output will be displayed as follows:
HELLO WORLD!

Variables

Variables are defined as containers or memory locations for storing data. The syntax of declaring a variable is variable_name = variable_value. However, it is recommended to use variables names like num1, my_int or mystring other than simple variables like x or y.

Sensible names gives a clear indication of the type of variable and it is also useful for others to understand your code clearly. Thinking of others while writing your program will improve your coding skills.

Built-in Data Types

Python comprises of many built-in data types starting from numbers, strings, lists, tuples and dictionaries.

Numbers

Python supports many types of numbers like integers (1, 2, 55, 599, -99), floating points (1.0, 5.55,  661.1, -99.9),  Booleans (True or False) or complex numbers. We can perform addition and subtraction with numbers just like normal addition and subtraction we learnt in our school:

>>> 1 + 5   # Addition
6
>>> num1 = 5
>>> num2 = 5.01
>>> num3 = num1 + num2
>>> 10 - 5   # Subtraction
5

We can also compare numbers that will result in a boolean value:

>>> 1 < 3
True
>>> 4 > 5
False

Python consists of a number of built-in functions that you can use to handle numbers:

>>> float(13)
13.0

A float() function takes an integer and returns a floating point number.

Other than functions, Python also has a number of data-type methods connected to each type of number. float.is_integer() is a data-type method which checks whether a floating point number is finite or not:

>>> (10.1).is_integer()
False
>>> (5.0).is_integer()
True 

Strings

A String is a list of characters in an organized manner. A character can be a number or letter or even a backslash. In simple words, they are lines enclosed in single or double quotes:

>>> string1 = "hello"
>>> string
'hello'
>>> string2 = 'hey'
>>> string2
"hey"

In Python, we can combine strings in a series without any gaps. This is called Concatenation:

>>> "Python is" + "easy"
'Python is easy'

We can also manipulate strings using functions:

>>> len('Python')
6

Here, len() is a function that takes a string as an input and returns the size of the string.

Data-type methods also exist for handling strings. string.capitalize() takes an input string and returns by capitalizing the first string:

>>> lower_case_string = 'python'
>>> lower_case_string.capitalize()
'Python'
>>> ('the Avengers').capitalize()
'The Avengers' 

Lists

A list is an ordered sequence of elements in Python. Each element in a list is known as an item. They are similar to array in C or C++.
Lists may consist of any data type like numbers or strings mixed together, or other lists or they may be empty too. The syntax is usual:

>>> create_a_list = []
>>> list_of_numbers = [1, 5, 10, 1000]
>>> list_of_numbers
[1, 5, 10, 1000]
>>> list = ["ironman", "thor", "hulk"]
>>> list
['ironman', 'thor', 'hulk']
>>> mixed_list = ["Python", [1, 2, 3], True]
>>> mixed_list
['Python', [1, 2, 3], True]

Elements of lists can be accessed either from the start or the end. Also, you can create a new list just by accessing the elements:

>>> list_of_numbers = [1, 5, 10, 1000]
>>> new_list = list_of_numbers[0:2]
>>> new_list
[1, 5]

Concatenation of lists using operators:

>>> marvel = ["ironman", "thor", "hulk"]
>>> dc = ["superman", "batman", "flash"]
>>> multiverse = marvel + dc
>>> multiverse
[‘ironman’, ‘thor’, ‘hulk’, ‘superman’, ‘batman’, ‘flash’]

The function of lists works in the same manner as of strings:

>>> list_of_numbers = [1, 5, 10, 1000]
>>> len(list_of_numbers)
4

len() returns the size of the list.

Data-type methods like list.sort() and list.append() are used to sort  and append lists:

#append
>>> stationary = ["inkpen", "pencil", "eraser"]
>>> stationary.append("sharpener")
>>> fruits
['inkpen', 'pencil', 'eraser', 'sharpener']

#sort
>>> stationary.sort()
>>> stationary
[ 'eraser', 'inkpen', 'pencil', 'sharpener']

Tuples

Tuples are sequence of Python objects that cannot be changed after creation. They are similar to lists, the only difference being that lists are mutable.

An example of a tuple:

my_tuple = ("Alex", "Blanc", 27, "Technical Blogger")

You can concatenate two tuples using operators just like lists:

>>> tuple1 = (11, 29)
>>> tuple2 = (30, 90)
>>> tuple3 = tuple1 + tuple1
>>> tuple3
(11, 29, 30, 90)

You can convert a tuple into a list by using the function list():

>>> tuple1 = (100, 500)
>>> list(tuple1)
[100, 500]

Since tuples cannot be changed after it is created, most of the data-type methods like sort() or append() or reverse() will not work on tuples.

Dictionary

A dictionary in Python is an unordered collection of associative arrays (or objects).
An example of a dictionary of phone numbers:

>>> phonebook = {}
>>> phonebook["Alex"] = 9038478766
>>> phonebook["Bob"] = 9098379264
>>> phonebook["Charlie"] = 9017652781

Conditions

A conditional statement is a statement that handles the flow of execution depending on some condition.
Statements can be compared or evaluated in Python using boolean expressions as follows:

>>> x = 5
>>> print(x == 5) # prints True
>>> print(x == 2) # prints False

You can also use the if-else statements to check if a statement is true or not:

>>>if 2 > 3:
  print("2 is greater than 3")
  else:
  print("2 is not greater than 3")

Loops

You can use loops when you want to repeat a block of code in a fixed number of time. You can iterate in two different ways, the first is by using the while loop:

>>> num = 1
>>> while num <= 5:
    print(num)
    num = num + 1

While the statement is true, the loop will iterate and the code will be executed. It will print the number from 1 to 5.

Another way of implementing a loop is using the for statement:

>>> for num in range(1, 10):
    print(num) 

Here, the range starts from 1 and goes until 10. The loop iterates 10 times over the statement.

Functions

Functions in Python are a block of organized code which is useful in performing a single action. Syntax of defining a function is def function_name.

An example of a function is:

>>> def my_first_function():
print("HELLO WORLD!")

You can also return a value to the caller in a function using the return statement:

>>> def multiply_by_2(a):
return a * 2

Classes and Objects

An object in Python is a collection of variables and methods. A class is a blueprint for the object.

For example, we can consider a prototype of a house as the class. It consists of all the details of the floors, walls, doors, windows etc. We can build the house on the basis of the details. So, house becomes the object. Objects are instances of a class.

You can define a class in Python using the keyword class as follows: 

>>> class My_First_Class:
    my_variable = "blah"

You can create an object in Python which can be used to access different attributes of a class. This process of creating new object instances is called instantiation.

An example to illustrate that:

class My_First_Class:
def func(self):
print('Hello')
ob = My_First_Class() #creating a class object

Modules and Packages

A module is a single file (or files) that are imported under one import and then used. In simple words, any Python file is a module. On the other hand, packages are simple directories consisting of multiple modules and packages themselves.

Python consists of a number of packages and modules to increase the extent of the language. 

Some of the useful built-in Python modules are:

  • math: This module gives access to mathematical functions from the standard library of C.
  • random: This module is a pseudo-random number generator.
  • datetime: This module comprises of classes by which you can manipulate dates and times.

Pip is the standard package manager which is used to handle Python’s third party packages and modules in an efficient manner. It allows you to install the packages that are not part of the Python Standard Library. You can download Pip from pypi.org.

Comments

Comments can be in the form of module-level docstrings or inline explanations that are used to describe your code in a clear manner so that developers can understand. It starts with a hash (#) character and can extend to the end of the line.

An example of a simple comment:
# This is a comment

An example of an inline comment:

variable = "Hello World"  # This is an inline comment

Errors and Exceptions 

Python consists of two types of errors:

  • Syntax errors.
  • Exceptions or errors during execution.

Syntax Errors

Syntax errors occur when the Python parser is unable to understand a line of code. Most syntax errors occur because of incorrect indentation or arguments.

An example to illustrate such:

>>> if 2 < 5
   File "<stdin>", line 1
     if 2 < 5
             ^
SyntaxError: invalid syntax

Here, the if statement is missing a colon(:)at the end of the statement which results into a syntax error.

Exceptions

Errors that occur during execution are known as exceptions. There are a number of built-in exceptions in Python.

An example of an exception:

>>> prices = { 'Pen' : 10, 'Pencil' : 5, 'Notebook' : 25}
>>> prices['Eraser']
Traceback (most recent call last):
  File "<pyshell#1>", line 1, in <module>
    prices['Eraser']
KeyError: 'Eraser'

Here, dictionary prices is declared with the prices of three items. The KeyError is raised when the item Eraser is being accessed which is not present in prices. Learn more about exceptions in our blog- Python KeyError Exceptions and How to Handle Them.

Semantic Errors

A semantic error, also known as logic error, is an error that occurs because of an incorrect logic. They are much more difficult to catch as compared to syntax errors.

These type of errors are complex in nature and generate incorrect or no output. The most common example of a semantic error is an infinite loop. Programmers in their early stage of learning encounter an infinite loop at least once.

What are the Different ways of Coding in Python?

When you’re in the process of learning a new programming language, you might want things to be simple and your path of becoming a good programmer to be smooth and clear. The first approach to this will be choosing an efficient way of running and executing code in Python.

There are mainly three primary approaches to coding in Python— the shell, IDLE and the code editor.

The Shell

Python provides the Python Shell, which is useful for simple, one-line statements. It waits for the input commands from the user and returns the result of the execution. It is the least powerful among the three.

You can open shell in your system and run the following command:

>>> 11 + 9
20 

Here, the Python Shell evaluated the statement 11 + 9 , performed the addition operation and displayed the result 20.

Another example of coding in shell:

>>> import this

When you execute this statement, you can see the Zen of Python. It is a collection of 19 principles which acts as a guide to write idiomatic Python code.

However, the shell has a drawback. The code written in a Python Shell is not persistent which means the code cannot be reused. 

IDLE

IDLE stands for Integrated Development and Learning Environment. It is similar to the shell and contains both the Shell window and the Editor Window. You can create and save Python code because the IDLE allows code reusability. However, it still stands second in the rank powerfulness. 

Code Editor

A code editor is the most powerful among all the three. It is a text-editor program that is useful in editing source codes of computer programs. A code editor can be a single application or act as an Integrated Development Environment or IDE.

There are a lot of code editors available in the market. Choosing a code-editor for your task might be a time-consuming work. 

However, you can take into consideration some factors while choosing a code editor like easy to use, line numbering, auto-indentation, highlighting of syntax and availability of adding extra features.

One of the most powerful and popular cross-platform code editor is the Sublime Text.  Other code editors might include gedit,  which is a bit simpler than Sublime. You can also use Notepad++, however it is only for Windows.

Conclusion

Let’s sum up what we have learnt so far in this article:

  • What is Python programming and what is the need.
  • How to install and run Python.
  • What are the primitives of the Python programming language.
  • What are the ways of Python coding.

Though you have learned the basics of the Python Programming Language, here are some tricks and tricks for you remember while coding in Python—

  • Good coding is happy coding. Good code depends on the way you write a code. The key to a good code is to maintain a proper style. You can go through the blog on How To Write Beautiful Python Code With PEP 8 which focuses on enhancing the readability and consistency of code.
  • The logic is the most crucial part when you’re writing a program. If you have a clear understanding of the concepts, you can easily shape your code into a logical program. And the most effective way to do that is to logically break your problem into different parts and then solve it one by one.
  • The best way of learning how to code is by building a project-driven learning approach. There are a lot of free resources, online courses, books and tutorials available. You can refer to the official Python documents - Python 2.7 or Python 3 for more information.You can also join the Python certification course offered by KnowledgeHut.
  • And last but not the least, always keep brushing up the concepts. As a beginner, you might face difficulties in every step, but always try and resolve your issues on your own. Test your skills and take up new challenges everyday.
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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3 comments

Ravichandran 13 Aug 2019

Clearly explained about the basics of python & different ways of coding in python thanks for the article.

Prasad 13 Aug 2019

Presented well thanks for the article.

kavya 16 Aug 2019

fabulous article, i am searching for this type of article only.

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Top 12 Python Packages for Machine Learning

Lovers of vintage movies would have definitely heard of the Monty Python series. The programming language that it inspired continues to remain among the most popular languages. Guess why Python has consistently topped the charts of the most popular programming languages? Because of its rich environment of libraries and tools, its easy code readability and the fact that it is so easy to pick up.  You name the domain, and you will get Python libraries available, to help you out in solving problems. Right from Artificial Intelligence, Data Science, Machine Learning, Image Processing, Speech Recognition, Computer Vision and more, Python has numerous uses. These libraries and frameworks are open source and can be easily integrated with the development environment that one has.These software frameworks, the platforms which provides necessary libraries and code components, are backbones for devloping applications. Read on to see which are the top ML frameworks and libraries in Python.1. 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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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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