Python Training in Nagpur

Python Programming is one of the easiest programming languages among all the top programming languages.  Python Programming is expressively very simple to code and it is designed to promote the readability of the code. 

Topics Covered in this module are:

• What is Python Programming
• History of Python
• Python Installation
• Python Environmental Setup
• Python Syntax
• Key Features of Python

Learning Outcome: By the end of this section, you will be able to get a clear idea about Python, How to set up an environment for Python, How to install Python and basic syntax of Python.

Python Fundamentals are the basics that are required for every learner to know in detail about the Python Programming language. Course fundamentals are the strength of an individual to code in Python.

Topics Covered in this module are:

• Python Comments
• Keywords
• Python Indentation
• Basic programs
• Limitations of Python

Learning Outcome: How to use comments in Python, What is the use of keywords,  How to write basic programs in Python.

Data Types are the major concept in Python. There are mainly used to define the type of variables by assigning the type of data. Python has many built-in data types by default.

Topics Covered in this module are:

• What are Data Types
• Built-in Data Types
• Setting Data Types
• Integer Data type
• String Data Type
• Float Data Type
• Character Data Type

Learning Outcome: How to assign Data Types to a variable, What are the built-in Data Types, Use and representation of each data type.

Operators are mainly used to carry out various assignments, logical, and arithmetic operations. They are considered as the special symbols in the Python Programming language. The value on which the operator performs its functioning is called the operand.

Topics Covered in this module are:

• Arithmetic Operators
• Comparison Operators
• Python Assignment Operators
• Logical Operators
• Bitwise Operators
• Shift operators
• Membership Operators
• Identity Operators
• Ternary Operator
• Operator precedence

Learning Outcome: Where to use the correct operator based on the operator functioning, and How the operator functions according to the given expression.

Strings in Python are used to represent the Unicode characters and they are considered as the arrays of bytes. The String literals in Python are represented in single quotes or double-quotes. Python Boolean is a data type that is mainly used to represent True or False for the given expression.

Topics Covered in this module are:

• String Literals
• Use of Strings
• Multiline Strings
• Unicode characters
• Negative Indexing
• Slicing
• String Methods
• Boolean Values
• Evaluation of Variables and Values

Learning Outcome: How to assign String to a variable, and How to evaluate variables and values using boolean data type.

Looping Statements in Python are mainly used to execute the condition until the block of statements gets satisfied with that particular condition with an accurate output. If the condition is false, the statements after the loop get executed. All the Conditional Statements in Python are handled and executed with the help of the IF statement. Conditional Statements working depends on boolean constraints.

Topics Covered in this module are:

• For loop
• While loop
• Do-while loop
• If statement
• If-Else statement
• Nested If Statement
• Switch case Statement
• Break 
• Continue
• Nested loops
• Branching Statements

Learning Outcome: How to execute the looping statements based on the condition, How the IF statement is used to handle conditional expressions in Python programming.

Functions in Python are the group of statements that takes particular inputs to do some specific computations. The function runs only when it is called. You can pass parameters into a function.

Topics Covered in this module are:

• What is Function
• How to create a Function
• Call a Function
• Arguments
• Recursive Function
• Python argument type functions
• Keyword argument functions
• Lambda functions
• Nested functions

Learning Outcome: How to create a function, How to call a function, and how to pass arguments into a function.

Python Arrays are mainly considered as a storage unit to store multiple values in a single variable. An array is also a variable that has the capacity to hold more values at a time.

Topics Covered in this module are:

• What is an Array
• Accessing Array Elements
• Looping of Array Elements
• Array Methods
• Add and Remove Array Elements

Learning Outcome: What is an Array, How to access the elements of an array, How to loop the Array elements, and how to add and remove elements from Array.

JSON is a built-in package in Python. It is mainly used for exchanging and storing data. JSON is a text that is written in javascript.

Topics Covered in this module are:

• JSON
• Parse JSON
• Formatting results using JSON
• Ordering

Learning Outcome: How to make use of JSON, How to convert from JSON to Python or vice versa, and How to format the result using Python JSON.

Collections in Python are called containers. This is mainly used to store huge collections of data like tuple, list, set, etc. The collection module acts as a Data Structure in Python to store a huge collection of data. 

Topics Covered in this module are:

• Types of Collections
• The need for List Collection
• List Indices
• Mutable List
• Nested Lists
• Tuple
• Immutable Tuple
• List vs Tuple
• Various methods of Tuple
• Creation of Tuple
• Set
• Union of Sets
• Iteration Over Sets
• Set Operations
• Dictionary
• Hashing Technique
• Read values from the Dictionary
• Dictionary Methods and Functions

Learning Outcome: How to store collections of data, Use of List, Tuple, Set, etc.

A Module in Python is considered as an object with an attribute. The module is mainly used to store the code in the file format or set of functions in a file. The module has the capability to define variables, functions, and classes. Moreover, runnable code can also be included in the Python module.

Topics Covered in this module are:

• Module Creation
• Types of Modules
• Modular Programming importance
• Import modules
• Connecting modules
• class-based modules
• Module built-in properties 

Learning Outcome: How to create a Module, Use of a Module, and How to name a Module.

Python Packages are mainly used to import a single module or any number of modules. When you import a package or subpackage in Python, it searches the whole tree of directories that are looking for a particular package and then proceed by the dot operator.

Topics Covered in this module are:

• Python Directories
• Import Python Packages
• py file
• PIP
• Installation of PIP
• Importance of Python Packages

Learning Outcome: What is Directory, How to import a Package, How to download a package, and how to install a package manager.

Regular Expression is defined as a sequence of characters that in turn forms the pattern. A regular expression is mainly used to check the string whether it contains that particular search pattern or not. 

Topics Covered in this module are:

• Regular expression Module
• Functions of regular expressions
• Metacharacters for making patterns
• Re flags
• Sets and special sequences

Learning Outcome: How to check the string having search patterns or not, How to make use of the RegEx module, and Different RegEx functions.

An exception is defined as an event that occurs when the flow of the program is normally interrupted by an, disrupt or an error. The handling of such exceptions in Python is called Exception Handling. Python script the capability to encounter such exception situations and raises an exception. 

Topics Covered in this module are:

• Exceptions Introduction
• Why exception handling?
• Runtime error v/s Syntax error
• Exception codes – AttributeError, ValueError, etc
• Handling exception – try-except block
• Try with multi except
• Handling multiple exceptions with single except block
• Finally block
• Try-except-finally
• Try with finally
• Case study of finally block
• User-defined exceptions
• Need to Custom exceptions

Learning Outcome: What is an Exception, How to handle Exceptions, Which blocks are used to handle exceptions, the importance of try and catch blocks.

File Handling in Python is considered a key part of any web application. The working of files in Python is based on the key function called open() function. File handling in Python also read files, write files, and delete files. 

Topics Covered in this module are:

• Introduction to files
• Opening file
• File modes
• Reading file data
• Writing file data
• Appending data into files
• Line count in File
• CSV module
• Creating a CSV file
• Reading from CSV file
• Writing into CSV file
• Object serialization – pickle module
• XML parsing

Learning Outcome: How to handle files in Python, How to read, write and delete files in Python, How important is File Handling for web application development.

Python’s OS Module provides a way of using the dependent functionality of the Operating System. The functions performed by the OS module provide an interface with an underlying Operating System. 

Topics Covered in this module are:

• Importance of OS module
• Different OS operations
• Restarting systems
• Functioning of OS
• Creation of an interface

Learning Outcome: By the end of this section you will be able to understand how to use the dependent functionality of the Operating System using the OS module.

Python MySQL Connector is the driver released by Oracle to easily connect MySQL Database with Python. The MySQL Database supports all the latest and old versions of Python. In order to install the MySQL, Python Connector makes use of PIP to install that particular package. 

Topics Covered in this module are:

• MySQL Database
• How to establish MySQL Connection with Python
• Creation of MYSQL Database
• Insert operation
• Select Operation
• Delete Operation
• Drop-Table
• Order By
• Join
• Limit
• Update

Learning Outcome: What is MySQL Database, How to establish MySQL Database connection with Python, What is PIP, and How to install MySQL connector using PIP.

Multiprocessing is referred to as the system’s ability to support more than one processor at a time. Multiprocessing applications are broken into smaller routines and they run independently. These threads are assigned to the processors by the operating system to improve the performance of the system. Multi-threading in Python is defined as the ability of the processor to execute multiple threads at a time. BOth multiprocessing and multi-threading are the multitasking operations performed in Python Programming.

Topics Covered in this module are:

• Introduction to multithreading and multiprocessing
• Different Threading modules
• Thread Life Cycle
• Run()
• Sleep()
• Join()
• Thread Synchronization
• Threading applications
• Creation of a Thread

Learning Outcome: How to perform multiprocessing, what is a thread, How to perform multithreading, and What are methods used in performing multi-threading. 

Python Logging is a function that is mainly used to track the events when the software runs. Logging is considered as an important aspect for debugging software, and for developing software. If you don’t have a Logging record your programs will be crashed. 

Topics Covered in this module are:

• What is Logging
• Different Logging levels
• Logging Implementation
• Program exceptions to Log File
• Customized Logger
• Configuring Log files

Learning Outcome: How to track events while the software is running and How important logging is for programming.

The most trending study Machine Learning makes use of Python code because it is easily understandable by a human and also you can build models very easily. Python is mainly used to perform various complex tasks of Machine Learning and enables the building of prototypes very easily and quickly. 

Topics Covered in this module are:

• Machine Learning Introduction
• Building Machine Learning models
• Performing Complex Tasks
• Human understandable Python coding

Learning Outcome: How to make use of Python programming to work on Machine Learning complex tasks and How to write human-understandable Python code.

Python NumPy is one of the core libraries in Python Programming and it is abbreviated as Numerical Python. It is mainly used for scientific computing in Python. This Python library provides many tools and various multi-dimensional objects to work with arrays. 

Topics Covered in this module are:

• Python Libraries
• NumPy Introduction
• Array indexing
• Data Types
• Slicing
• Array iteration
• Array Split
• Random
• Creating Arrays

Learning Outcome: How to work with arrays using NumPy in Python.

Python has become one of the crucial programming languages for Data Science and for performing data analytics. It can easily understand various data patterns and will be able to correlate huge data sets. It is considered as the essential concept for self-service analytics. Most of the data mining companies use Python to handle their huge amounts of data in a well-defined manner.

Topics Covered in this module are:

• Introduction to Data Analytics
• Importance of Python Programming in Data Analysis
• Introduction to Data Science
• Handling huge amount of Data Sets

Learning Outcome: How Python builds better data insights, How Python correlates huge data sets and the Advantages of using Python in Data Science.