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Python Training Overview
Python is a general-purpose interpreted, interactive, object-oriented, and high-level programming language. Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis
What are the Python Course Pre-requisites
There are no hard pre-requisites. Basic understanding of Computer Programming terminologies is sufficient. Also, basic concepts related to Programming and Database is beeficial but not mandatory.
Python Course Content
Core Python
Introduction to Languages
✔ What is Language?
✔ Types of languages
✔ Introduction to Translators
(1) Compiler
(2) Interpreter
✔ What is Scripting Language?
✔ Types of Script
✔ Programming Languages v/s Scripting Languages
✔ Difference between Scripting and Programming languages
✔ What is programming paradigm?
✔ Procedural programming paradigm
✔ Object Oriented Programming paradigm
Introduction to Python
✔ What is Python?
✔ WHY PYTHON?
✔ History
✔ Features – Dynamic, Interpreted, Object oriented, Embeddable, Extensible, Large standard libraries, Free and Open source
✔ Why Python is General Language?
✔ Limitations of Python
✔ What is PSF?
✔ Python implementations
✔ Python applications
✔ Python versions
✔ PYTHON IN REALTIME INDUSTRY
✔ Difference between Python 2.x and 3.x
✔ Difference between Python 3.7 and 3.8
✔ Software Development Architectures
Python Software’s
✔ Python Distributions
✔ Download &Python Installation Process in Windows, Unix, Linux and Mac
✔ Online Python IDLE
✔ Python Real-time IDEs like Spyder, Jupyter Note Book, PyCharm, Rodeo, Visual Studio Code, ATOM, PyDevetc
Python Language Fundamentals
✔ Python Implementation Alternatives/Flavors
✔ Keywords
✔ Identifiers
✔ Constants / Literals
✔ Data types
✔ Python VS JAVA
✔ Python Syntax
Different Modes of Python
✔ Interactive Mode
✔ Scripting Mode
✔ Programming Elements
✔ Structure of Python program
✔ First Python Application
✔ Comments in Python
✔ Python file extensions
✔ Setting Path in Windows
✔ Edit and Run python program without IDE
✔ Edit and Run python program using IDEs
✔ INSIDE PYTHON
✔ Programmers View of Interpreter
✔ Inside INTERPRETER
✔ What is Byte Code in PYTHON?
✔ Python Debugger
Python Variables
✔ bytes Data Type
✔ byte array
✔ String Formatting in Python
✔ Math, Random, Secrets Modules
✔ Introduction
✔ Initialization of variables
✔ Local variables
✔ Global variables
✔ ‘global’ keyword
✔ Input and Output operations
✔ Data conversion functions – int(), float(), complex(), str(), chr(), ord()
Operators
✔ Arithmetic Operators
✔ Comparison Operators
✔ Python Assignment Operators
✔ Logical Operators
✔ Bitwise Operators
✔ Shift operators
✔ Membership Operators
✔ Identity Operators
✔ Ternary Operator
✔ Operator precedence
✔ Difference between “is” vs “==”
Input & Output Operators
✔ Print
✔ Input
✔ Command-line arguments
Control Statements
✔ Conditional control statements
✔ If
✔ If-else
✔ If-elif-else
✔ Nested-if
✔ Loop control statements
✔ for
✔ while
✔ Nested loops
✔ Branching statements
✔ Break
✔ Continue
✔ Pass
✔ Return
✔ Case studies
Data Structures or Collections
✔ Introduction
✔ Importance of Data structures
✔ Applications of Data structures
✔ Types of Collections
✔ Sequence
✔ Strings, List, Tuple, range
✔ Non sequence
✔ Set, Frozen set, Dictionary
✔ Strings
✔ What is string
✔ Representation of Strings
✔ Processing elements using indexing
✔ Processing elements using Iterators
✔ Manipulation of String using Indexing and Slicing
✔ String operators
✔ Methods of String object
✔ String Formatting
✔ String functions
✔ String Immutability
✔ Case studies
List Collection
✔ What is List
✔ Need of List collection
✔ Different ways of creating List
✔ List comprehension
✔ List indices
✔ Processing elements of List through Indexing and Slicing
✔ List object methods
✔ List is Mutable
✔ Mutable and Immutable elements of List
✔ Nested Lists
✔ List_of_lists
✔ Hardcopy, shallowCopy and DeepCopy
✔ zip() in Python
✔ How to unzip?
✔ Python Arrays:
✔ Case studies
Tuple Collection
✔ What is tuple?
✔ Different ways of creating Tuple
✔ Method of Tuple object
✔ Tuple is Immutable
✔ Mutable and Immutable elements of Tuple
✔ Process tuple through Indexing and Slicing
✔ List v/s Tuple
✔ Case studies
Set Collection
✔ What is set?
✔ Different ways of creating set
✔ Difference between list and set
✔ Iteration Over Sets
✔ Accessing elements of set
✔ Python Set Methods
✔ Python Set Operations
✔ Union of sets
✔ functions and methods of set
✔ Python Frozen set
✔ Difference between set and frozenset ?
✔ Case study
Dictionary Collection
✔ What is dictionary?
✔ Difference between list, set and dictionary
✔ How to create a dictionary?
✔ PYTHON HASHING?
✔ Accessing values of dictionary
✔ Python Dictionary Methods
✔ Copying dictionary
✔ Updating Dictionary
✔ Reading keys from Dictionary
✔ Reading values from Dictionary
✔ Reading items from Dictionary
✔ Delete Keys from the dictionary
✔ Sorting the Dictionary
✔ Python Dictionary Functions and methods
✔ Dictionary comprehension
Functions
✔ What is Function?
✔ Advantages of functions
✔ Syntax and Writing function
✔ Calling or Invoking function
✔ Classification of Functions
i) No arguments and No return values
ii) With arguments and No return values
iii) With arguments and With return values
iv) No arguments and With return values
v) Recursion
✔ Python argument type functions :
i) Default argument functions
ii) Required(Positional) arguments function
iii) Keyword arguments function
iv) Variable arguments functions
‘✔ pass’ keyword in functions
✔ Lambda functions/Anonymous functions
i) map()
ii) filter()
iii) reduce()
✔ Nested functions
✔ Non local variables, global variables
✔ Closures
✔ Decorators
✔ Generators
✔ Iterators
✔ Monkey patching
Advanced Python
Python Modules
✔ Importance of modular programming
✔ What is module
✔ Types of Modules – Pre defined, User defined.
✔ User defined modules creation
✔ Functions based modules
✔ Class based modules
✔ Connecting modules
✔ Import module
✔ From … import
✔ Module alias / Renaming module
✔ Built In properties of module
Packages
✔ Organizing python project into packages
✔ Types of packages – pre defined, user defined.
✔ Package v/s Folder
✔ py file
✔ Importing package
✔ PIP
✔ Introduction to PIP
✔ Installing PIP
✔ Installing Python packages
✔ Un installing Python packages
OOPs
✔ Procedural v/s Object oriented programming
✔ Principles of OOP – Encapsulation , Abstraction (Data Hiding)
✔ Classes and Objects
✔ How to define class in python
✔ Types of variables – instance variables, class variables.
✔ Types of methods – instance methods, class method, static method
✔ Object initialization
✔ ‘self’ reference variable
✔ ‘cls’ reference variable
✔ Access modifiers – private(__) , protected(_), public
✔ AT property class
✔ Property() object
✔ Creating object properties using setaltr, getaltr functions
✔ Encapsulation(Data Binding)
✔ What is polymorphism?
✔ Overriding
i) Method overriding
ii) Constructor overriding
✔ Overloading
i) Method Overloading
ii) Constructor Overloading
iii) Operator Overloading
✔ Class re-usability
✔ Composition
✔ Aggregation
✔ Inheritance – single , multi level, multiple, hierarchical and hybrid inheritance and Diamond inheritance
✔ Constructors in inheritance
✔ Object class
✔ super()
✔ Runtime polymorphism
✔ Method overriding
✔ Method resolution order(MRO)
✔ Method overriding in Multiple inheritance and Hybrid Inheritance
✔ Duck typing
✔ Concrete Methods in Abstract Base Classes
✔ Difference between Abstraction & Encapsulation
✔ Inner classes
✔ Introduction
✔ Writing inner class
✔ Accessing class level members of inner class
✔ Accessing object level members of inner class
✔ Local inner classes
✔ Complex inner classes
✔ Case studies
Exception Handling & Types of Errors
✔ What is Exception?
✔ Why exception handling?
✔ Syntax error v/s Runtime error
✔ Exception codes – AttributeError, ValueError, IndexError, TypeError…
i) Handling exception – try except block
ii) Try with multi except
iii) Handling multiple exceptions with single except block
✔ Finally block
i) Try-except-finally
ii) Try with finally
iii) Case study of finally block
✔ Raise keyword
i) Custom exceptions / User defined exceptions
ii) Need to Custom exceptions
✔ Case studies
Regular expressions
✔ Understanding regular expressions
✔ String v/s Regular expression string
✔ “re” module functions
✔ Match()
✔ Search()
✔ Split()
✔ Findall()
✔ Compile()
✔ Sub()
✔ ✔ Subn()
✔ Expressions using operators and symbols
✔ Simple character matches
✔ Special characters
✔ Character classes
✔ Mobile number extraction
✔ Mail extraction
✔ Different Mail ID patterns
✔ Data extraction
✔ Password extraction
✔ URL extraction
✔ Vehicle number extraction
✔ Case study
File &Directory handling
✔ Introduction to files
✔ Opening file
✔ File modes
✔ Reading data from file
✔ Writing data into file
✔ Appending data into file
✔ Line count in File
✔ CSV module
✔ Creating CSV file
✔ Reading from CSV file
✔ Writing into CSV file
✔ Object serialization – pickle module
✔ XML parsing
✔ JSON parsing
Python Logging
✔ Logging Levels
✔ implement Logging
✔ Configure Log File in over writing Mode
✔ Timestamp in the Log Messages
✔ Python Program Exceptions to the Log File
✔ Requirement of Our Own Customized Logger
✔ Features of Customized Logger
Date & Time module
✔ How to use Date & Date Time class
✔ How to use Time Delta object
✔ Formatting Date and Time
✔ Calendar module
✔ Text calendar
✔ HTML calendar
OS module
✔ Shell script commands
✔ Various OS operations in Python
✔ Python file system shell methods
✔ Creating files and directories
✔ Removing files and directories
✔ Shutdown and Restart system
✔ Renaming files and directories
✔ Executing system commands
Multi-threading & Multi Processing
✔ Introduction
✔ Multi tasking v/s Multi threading
✔ Threading module
✔ Creating thread – inheriting Thread class , Using callable object
✔ Life cycle of thread
✔ Single threaded application
✔ Multi threaded application
✔ Can we call run() directly?
✔ Need to start() method
✔ Sleep()
✔ Join()
✔ Synchronization – Lock class – acquire(), release() functions
✔ Case studies
Garbage collection
✔ Introduction
✔ Importance of Manual garbage collection
✔ Self reference objects garbage collection
✔ ‘gc’ module
✔ Collect() method
✔ Threshold function
✔ Case studies
Python Data Base Communications(PDBC)
✔ Introduction to DBMS applications
✔ File system v/s DBMS
✔ Communicating with MySQL
✔ Python – MySQL connector
✔ connector module
✔ connect() method
✔ Oracle Database
✔ Install cx_Oracle
✔ Cursor Object methods
✔ execute() method
✔ executeMany() method
✔ fetchone()
✔ fetchmany()
✔ fetchall()
✔ Static queries v/s Dynamic queries
✔ Transaction management
✔ Case studies
Python – Network Programming
✔ What is Sockets?
✔ What is Socket Programming?
✔ The socket Module
✔ Server Socket Methods
✔ Connecting to a server
✔ A simple server-client program
✔ Server
✔ Client
Tkinter & Turtle
✔ Introduction to GUI programming
✔ Tkinter module
✔ Tk class
✔ Components / Widgets
✔ Label , Entry , Button , Combo, Radio
✔ Types of Layouts
✔ Handling events
✔ Widgets properties
✔ Case studies
Data analytics modules
✔ Numpy
✔ Introduction
✔ Scipy
✔ Introduction
✔ Arrays
✔ Datatypes
✔ Matrices
✔ N dimension arrays
✔ Indexing and Slicing
✔ Pandas
✔ Introduction
✔ Data Frames
✔ Merge , Join, Concat
✔ MatPlotLib introduction
✔ Drawing plots
✔ Introduction to Machine learning
✔ Types of Machine Learning?
✔ Introduction to Data science
DJANGO
✔ Introduction to PYTHON Django
✔ What is Web framework?
✔ Why Frameworks?
✔ Define MVT Design Pattern
✔ Difference between MVC and MVT
PANDAS
Pandas – Introduction
Pandas – Environment Setup
Pandas – Introduction to Data Structures
✔ Dimension & Description
✔ Series
✔ DataFrame
✔ Data Type of Columns
✔ Panel
Pandas — Series
✔ Series
✔ Create an Empty Series
✔ Create a Series f
✔ rom ndarray
✔ rom dict
✔ rom Scalar
✔ Accessing Data from Series with Position
✔ Retrieve Data Using Label (Index)
Pandas – DataFrame
✔ DataFrame
✔ Create DataFrame
✔ Create an Empty DataFrame
✔ Create a DataFrame from Lists
✔ Create a DataFrame from Dict of ndarrays / Lists
✔ Create a DataFrame from List of Dicts
✔ Create a DataFrame from Dict of Series
✔ Column Selection
✔ Column Addition
✔ Column Deletion
✔ Row Selection, Addition, and Deletion
Pandas – Panel
✔ Panel()
✔ Create Panel
✔ Selecting the Data from Panel
Pandas – Basic Functionality
✔ DataFrame Basic Functionality
Pandas – Descriptive Statistics
✔ Functions & Description
✔ Summarizing Data
Pandas – Function Application
✔ Table-wise Function Application
✔ Row or Column Wise Function Application
✔ Element Wise Function Application
Pandas – Reindexing
✔ Reindex to Align with Other Objects
✔ Filling while ReIndexing
✔ Limits on Filling while Reindexing
✔ Renaming
Pandas – Iteration
✔ Iterating a DataFrame
✔ iteritems()
✔ iterrows()
✔ itertuples()
Pandas – Sorting
✔ By Label
✔ Sorting Algorithm
Pandas – Working with Text Data
Pandas – Options and Customization
✔ get_option(param)
✔ set_option(param,value)
✔ reset_option(param)
✔ describe_option(param)
✔ option_context()
Pandas – Indexing and Selecting Data
✔ .loc()
✔ .iloc()
✔ .ix()
✔ Use of Notations
Pandas – Statistical Functions
✔ Percent_change
✔ Covariance
✔ Correlation
✔ Data Ranking
Pandas – Window Functions
✔ .rolling() Function
✔ .expanding() Function
✔ .ewm() Function
Pandas – Aggregations
✔ Applying Aggregations on DataFrame
Pandas – Missing Data
✔ Cleaning / Filling Missing Data
✔ Replace NaN with a Scalar Value
✔ Fill NA Forward and Backward
✔ Drop Missing Values
✔ Replace Missing (or) Generic Values
Pandas – GroupBy
✔ Split Data into Groups
✔ View Groups
✔ Iterating through Groups
✔ Select a Group
✔ Aggregations
✔ Transformations
✔ Filtration
Pandas – Merging/Joining
✔ Merge Using ‘how’ Argument
Pandas – Concatenation
✔ Concatenating Objects
✔ Time Series
Pandas – Date Functionality
Pandas – Timedelta
Pandas – Categorical Data
✔ Object Creation
Pandas – Visualization
✔ Bar Plot
✔ Histograms
✔ Box Plots
✔ Area Plot
✔ Scatter Plot
✔ Pie Chart
Pandas – IO Tools
✔ csv
Pandas – Sparse Data
Pandas – Caveats & Gotchas
Pandas – Comparison with SQL
NUMPY
NUMPY − INTRODUCTION
NUMPY − ENVIRONMENT
NUMPY − NDARRAY OBJECT
NUMPY − DATA TYPES
✔ Data Type Objects (dtype)
NUMPY − ARRAY ATTRIBUTES
✔ shape
✔ ndim
✔ itemsize
✔ flags
NUMPY − ARRAY CREATION ROUTINES
✔ empty
✔ zeros
✔ ones
NUMPY − ARRAY FROM EXISTING DATA
✔ asarray
✔ frombuffer
✔ fromiter
NUMPY − ARRAY FROM NUMERICAL RANGES
✔ arange
✔ linspace
✔ logspace
NUMPY − INDEXING & SLICING
NUMPY − ADVANCED INDEXING
✔ Integer Indexing
✔ Boolean Array Indexing
NUMPY − BROADCASTING
NUMPY − ITERATING OVER ARRAY
✔ Iteration
✔ Order
✔ Modifying Array Values
✔ External Loop
✔ Broadcasting Iteration
NUMPY – ARRAY MANIPULATION
✔ reshape
✔ ndarray.flat
✔ ndarray.flatten
✔ ravel
✔ transpose
✔ ndarray.T
✔ swapaxes
✔ rollaxis
✔ broadcast
✔ broadcast_to
✔ expand_dims
✔ squeeze
✔ concatenate
✔ stack
✔ hstack and numpy.vstack
✔ split
✔ hsplit and numpy.vsplit
✔ resize
✔ append
✔ insert
✔ delete
✔ unique
NUMPY – BINARY OPERATORS
✔ bitwise_and
✔ bitwise_or
✔ invert()
✔ left_shift
✔ right_shift
NUMPY − STRING FUNCTIONS
NUMPY − MATHEMATICAL FUNCTIONS
✔ Trigonometric Functions
✔ Functions for Rounding
NUMPY − ARITHMETIC OPERATIONS
✔ reciprocal()
✔ power()
✔ mod()
NUMPY − STATISTICAL FUNCTIONS
✔ amin() and numpy.amax()
✔ ptp()
✔ percentile()
✔ median()
✔ mean()
✔ average()
✔ Standard Deviation
✔ Variance
NUMPY − SORT, SEARCH & COUNTING FUNCTIONS
✔ sort()
✔ argsort()
✔ lexsort()
✔ argmax() and numpy.argmin()
✔ nonzero()
✔ where()
✔ extract()
NUMPY − BYTE SWAPPING
✔ ndarray.byteswap()
NUMPY − COPIES & VIEWS
✔ No Copy
✔ View or Shallow Copy
✔ Deep Copy
NUMPY − MATRIX LIBRARY
✔ empty()
✔ matlib.zeros()
✔ matlib.ones()
✔ matlib.eye()
✔ matlib.identity()
✔ matlib.rand()
NUMPY − LINEAR ALGEBRA
✔ dot()
✔ vdot()
✔ inner()
✔ matmul()
✔ Determinant
✔ linalg.solve()
NUMPY − MATPLOTLIB
✔ Sine Wave Plot
✔ subplot()
✔ bar()
NUMPY – HISTOGRAM USING MATPLOTLIB
✔ histogram()
✔ plt()
NUMPY − I/O WITH NUMPY
✔ save()
✔ savetxt()
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