Master Full Stack Python: Online Training for Web Development

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Dur: 4 months
Course fee : 12000 /-

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Full Stack Python

Course Overview

The Online Training course in Full Stack Python Development offers an immersive learning experience that delves into both the front-end and back-end facets of Python-driven web development. It is meticulously designed to equip participants with a thorough understanding of essential concepts, tools, and frameworks crucial for crafting contemporary, scalable web applications. Through a blend of interactive modules and hands-on exercises, learners will acquire practical expertise in every stage of the development cycle, from conceptualizing and designing to coding, deploying, and sustaining full-stack Python applications. Whether opting for Online Training or Classroom Training, this comprehensive program ensures that individuals gain the necessary skills and knowledge to thrive in the dynamic realm of web development.

Description

This course delves into the complete stack of technologies involved in Python web development, including frontend frameworks like Flask or Django, backend databases like MySQL or MongoDB, and client-side technologies such as HTML, CSS, and JavaScript. Through a combination of lectures, hands-on coding exercises, and projects, participants will learn how to integrate various components to create fully functional web applications. Additionally, the course covers topics such as API development, authentication, security best practices, and deployment strategies.

Course Objectives

Understand the architecture of full-stack web applications.
Gain proficiency in Python programming language.
Learn to develop dynamic web interfaces using frontend frameworks like Flask or Django.
Master backend development with Python and popular databases like MySQL or MongoDB.
Acquire knowledge of RESTful API development and integration.
Implement user authentication and authorization mechanisms.
Explore best practices for security and performance optimization.
Learn deployment strategies for deploying Python applications to production environments.

Prerequisites

- Basic understanding of programming concepts (preferably Python).
- Familiarity with web technologies such as HTML, CSS, and JavaScript.
- Knowledge of database concepts is beneficial but not mandatory.

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Course Curriculum

Introduction to Programming Languages
Introduction to Python
Working with Python Software
Python Language Fundamentals
Different Modes of working with Python
Basic I/O operations in Python
Operators and Expressions in Python
Data Types in Python
Flow Control Statements (or) Control Structures
String Handling Operations
Bytes, ByteArray and Range Data Types
List Data Structure and Operations
Tuple Data Structure and Operations
Set and Frozenset Data Structures or Collection
Dictionary Data Structures or collection
Comprehensions (List/Dictionary/Set)
NoneType Category
Functions in Python
Modules in Python
Packages in python
Exception Handling in Python
Regular Expressions (Re Module)
File or Stream Handling
Collections module for building applications

Object Oriented Programming Principles
OS Module
Multi Threading
Python Logging
Date and Time module
Garbage Collection
Python Data Base Communications (PDBC)
Network / Socket Programming (socket module)
Tkinter and Turtle

Basic Introduction to the Numpy
Creation of Numpy Arrays
Array attributes & Numpy Data Types
View vs Copy
Indexing, Slicing and Advanced Indexing
How to Iterate Elements of the ndarray.
Arithmetic Operators
Broadcasting
Array Manipulation Functions
Joining Of Multiple Arrays Into a Single Array
Splitting of Arrays
Sorting Elements of ndarrays
Searching elemenets of ndarray
How to insert elements into ndarray?
How to delete elements from ndarray
Matric multiplication by using dot() function
Importance of matrix class in numpy library
Linear algebra functions from linalg module
I/0 operations with Numpy
Basic statistics with Numpy
Numpy mathematical functions
How to find unique items and count

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

Introduction to Matplotlib
Line Plot- Basics
Line Plots-Advanced
How to add grid lines to plot
Adding Legend
Customization of Tick Location and Labels
How to set limit range of values on x-axis and y-axis by using xlim() and ylim() functions
How to set scale of x-axis and y-axis?
Plotting Styles
Functional/Procedural Oriented Vs Object Oriented Approached of plotting
Bar Chart / Bar Graph / Bar Plot
Pie Chart
Histogram
Scatter Plots
Subplots
Plotting Geographic Data with Basemap
Three-Dimensional(3-D) Plotting in Matplotlib
Animations

Web Introduction
Introduction to HTML
Introduction to HTML Structure
Presentational & Formatting Tags
Title and Html entities
Attributes
HTML Images & Anchor Tag
Working with Lists
Working with Div tag
HTML Tables
HTML Forms
HTML Form Controls
Additional from controls
HTML5 New Semantic / Structural Elements

Introduction to CSS
CSS Selectors
CSS Box model
Styling Elements
Advanced Cascading Style Sheets

Introduction JavaScript
JavaScript implementations
Java Script Variables & datatypes
JavaScript Operators
Java Script Control Controls
Arrays
Functions
Functional Expressions
Arrow Functions
JavaScript Strings
Working with JS Objects
JS Constructors
DOM-Document object
DOM-Element object
DOM-Event Handling
BOM-Window object
Javascript validations and Regular Expressions
Bootstrap

Introduction to Django
Django & Atom Installation and Development of First Web Application
Templates and Static Files
Views and URLs
Models and Databases
Forms and Validation
Advanced Template Features
Session Management
User Authentication and Authorization
Class Based Views and CRUD Operations by using both CBVs and FBVs
Django ORM
Working with Advanced Model Concepts
Django Rest Framework
Testing and Debugging
Caching and Performance Optimization
Django Forms Advanced Topics
Django Security
Django Signals and Asynchronous Tasks
Django Deployment and Production
WebSockets and Real-Time Communication
Project Development and Refinement

Introduction to Flask
Building Web Applications with Flask
Web Forms and User Input
Databases and Data Storage
User Authentication and Authorization
RESTful APIs
Deployment and Scaling
Advanced Topics

MySQL
MongoDB

AWS Basics
Version Control-GIT
Docker
Kubernetes

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Who can learn this course

Aspiring web developers seeking to specialize in Python-based full-stack development.
Software engineers looking to expand their skills into web development.
Entrepreneurs or startup founders interested in building their own web applications.
Professionals interested in transitioning into a career in web development.
Students or enthusiasts passionate about learning modern web development technologies.

Average package of course (Full Stack Python )

50% Avg
salary hike

50L Avg
Package

Upcoming Batches

Course Name	Faculty	Date	Time	Mode of Training	Batch Type
Full Stack Python	Mr. Satish Gupta	2 May	7:15 AM (IST)	online	Online Training
Full Stack Python	Mr. Satish Gupta	2 May	7:15 AM (IST)	offline	Classroom Training
Full Stack Python	Dr. Venkat Raju	21 Apr	7:00 PM (IST)	offline	KPHB