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 beneficial but not mandatory.
To understand the concepts and constructs of Python to create own Python programs, know the machine learning algorithms in Python and work on a real-time project running on Python.
Big Data Professionals
IT Developers
Those who are showing interest to build their career in Python
Python Training Course Duration
35 Days, Daily 1
Python Course Content
Core Python
Introduction to Languages
What is Language?
Types of languages
Introduction to Translators
Compiler
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
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
No arguments and No return values
With arguments and No return values
With arguments and With return values
No arguments and With return values
Recursion
Python argument type functions :
Default argument functions
Required(Positional) arguments function
Keyword arguments function
Variable arguments functions
‘pass’ keyword in functions
Lambda functions/Anonymous functions
map()
filter()
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…
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
Raise keyword
Custom exceptions / User defined exceptions
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()