Python Training

Python is a versatile, high-level programming language that is interpreted, interactive, and object-oriented. Renowned for its flexibility and power, this open-source language is celebrated for its ease of learning and use, offering robust libraries particularly beneficial for data manipulation and analysis.

10 Modules
with Certifications

English
Language

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Module-1: Introduction to Languages

What is Language?
Types of languages,Introduction to Translators-Compiler,Interpreter
What is Scripting Language? and 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

Module-2: Introduction to Python

What is Python?,WHY PYTHON? and 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 IN REALTIME INDUSTRY
Difference between Python 2.x and 3.x
Difference between Python 3.7 and 3.8
Software Development Architectures

Module-3: Python

Python Language Fundamentals
Different Modes of Python
Python Variables
Operators
Input & Output Operators
Control Statements
Data Structures or Collections
List Collection
Tuple Collection
Set Collection
Dictionary Collection
Functions

Module-4: Advanced Python

Python Modules
Packages
OOPs
Exception Handling & Types of Errors
Regular expressions
File &Directory handling
Python Logging
Date & Time module
OS module
Multi-threading & Multi Processing
Garbage collection
Python Data Base Communications(PDBC)
Python – Network Programming
Tkinter & Turtle
Data analytics modules

Module-5: DJango

Introduction to PYTHON Django
What is Web framework?
Why Frameworks?
Define MVT Design Pattern
Difference between MVC and MVT

Module-6: PANDAS

Pandas – Introduction
Pandas – Environment Setup
Pandas – Introduction to Data Structures
Pandas — Series
Pandas – DataFrame
Pandas – Panel
Pandas – Basic Functionality
Pandas – Descriptive Statistics
Pandas – Function Application
Pandas – Reindexing
Pandas – Iteration
Pandas – Sorting
Pandas – Working with Text Data
Pandas – Options and Customization
Pandas – Indexing and Selecting Data
Pandas – Statistical Functions
Pandas – Window Functions
Pandas – Aggregations
Pandas – Missing Data
Pandas – GroupBy
Pandas – Merging/Joining
Pandas – Concatenation
Pandas – Date Functionality
Pandas – Timedelta
Pandas – Categorical Data
Pandas – Visualization
Pandas – IO Tools
Pandas – Sparse Data
Pandas – Caveats & Gotchas
Pandas – Comparison with SQL

Module-7: Numpy

NUMPY − INTRODUCTION
NUMPY − ENVIRONMENT
NUMPY − NDARRAY OBJECT
NUMPY − DATA TYPES
NUMPY − ARRAY ATTRIBUTES
NUMPY − ARRAY CREATION ROUTINES
NUMPY − ARRAY FROM EXISTING DATA
NUMPY − ARRAY FROM NUMERICAL RANGES
NUMPY − INDEXING & SLICING
NUMPY − ADVANCED INDEXING
NUMPY − BROADCASTING
NUMPY − ITERATING OVER ARRAY
NUMPY – ARRAY MANIPULATION
NUMPY – BINARY OPERATORS
NUMPY − STRING FUNCTIONS
NUMPY − MATHEMATICAL FUNCTIONS
NUMPY − ARITHMETIC OPERATIONS
NUMPY − STATISTICAL FUNCTIONS
NUMPY − SORT, SEARCH & COUNTING FUNCTIONS
NUMPY − BYTE SWAPPING
NUMPY − COPIES & VIEWS
NUMPY − MATRIX LIBRARY
NUMPY − LINEAR ALGEBRA
NUMPY − MATPLOTLIB
NUMPY – HISTOGRAM USING MATPLOTLIB
NUMPY − I/O WITH NUMPY

Module-8: IDE’S

Module-9: Interview Guidance

Module-10: Placement Assistance