Python Full Stack Developer

Python Full Stack Developer Course Syllabus

This Full Stack Python Developer program will help you master both front-end and backend Java technologies and accelerate your career as a full stack python developer.This course will expose you to basic and advanced concepts of web development. You will also learn complete python core concept, data science machine learning , Django and much more.This course will help advance your career as a fullstack developer and help you learn some of the most high demand skills in the industry

Duration

1 Month 10 Day's

navratri special discount offer

50%

Available Seats

30

Schedule


Weekly:- 5.00 pm - 7.00 pm

WeekEnd:- Saturday - Sunday : 11:00 am - 2:00 pm

1 HTML

Introduction to HTML
Basic Structure of HTML
HTML Editors
HTML Tags
Paragraphs, Headings and Text
Formatting Tags
HTML Lists
HTML Images
HTML Tables
HTML Forms
HTML Media

2 CSS

• Introduction to CSS
• Types of CSS
• CSS Properties, Selectors and Values
• Applying CSS to HTML
• CSS colors
• CSS Box Model, Margins, Padding,
• Borders
• CSS Text & Font Formats
• CSS Advanced Topics (Effects, Animations,
• Shadows, Etc.,)

3 BOOTSTRAP

• ntroduction to Bootstrap
• Bootstrap Setup
• Bootstrap Containers
• Bootstrap Grids
• Bootstrap Tables
• Bootstrap Buttons, Navbars, Alerts
• Bootstrap Carousel
• Bootstrap Forms

4 JAVASCRIPT

• Introduction to JavaScript
• How to Apply JavaScript
• Displaying Output in JavaScript
• Understanding JavaScript Syntax
• Variables & Datatypes
• Operators
• Math and String Manipulations
• Conditional and looping Statements
• Functions
• Validations
• Events

5 ANGULARJS

• Introduction to Angular
• Environment Setup
• Installing Angular CLI
• Directory Structure of Angular
• Angular Fundamentals
• Angular Building Blocks
• Angular Data Binding
• String Interpolation
• Directives and Pipes
• Forms
• Approaches (Driven & Reactive)
• Validators
• Routing

6 INTRODUCTION TO PYTHON

• What is Python and history of Python
• Unique features of Python
• Python-2 and Python-3 differences
• Install Python and Environment Setup
• First Python Program
• Python Identifiers, Keywords and Indentation
• Comments and document interlude in Python
• Command-line arguments
• Getting User Input
• Python Data Types
• What are variables?
• Python Core objects and Functions
• Number and Maths
• Assignments

7 CONTROL STATEMENTS and algorithms

• if-else
• if-elseif-else
• while loop
• for loop
• break
• continue
• assert
• pass
• return

8 LIST, RANGES & TUPLES IN PYTHON of models

• Introduction
• Lists in Python
• More about Lists
• Understanding Iterators
• Generators, Comprehensions and Lambda
• Expressions
• Generators and Yield
• Next and Ranges
• Understanding and using Ranges
• More About Ranges
• Ordered Sets with tuples

9 PYTHON DICTIONARIES AND SETS

• Introduction to the section
• Python Dictionaries
• MORE ON DICTIONARIES
• SETS
• Python Sets Examples
• Input and Output in Python
• Reading and writing text files
• writing Text Files
• Appending to Files and Challenge
• Writing Binary Files Manually
• Using Pickle to Write Binary Files

10 PYTHON REGULAR EXPRESSIONS

• What are regular expressions?
• The match Function
• The search Function
• Matching vs searching
• Search and Replace
• Extended Regular Expressions
• Wildcard

11 PYTHON MULTITHREADED PROGRAMMING

• What is multithreading?
• Difference between a Process and Thread
• Concurrent Programming and GIL
• Uses of Thread
• Starting a New Thread
• The Threading Module
• Thread Synchronization
• Locks
• Semaphore
• Deadlock of Threads
• Avoiding Deadlocks
• Daemon Threads
• Using Databases in Python
• Python MySQL Database Access
• Install the MySQLdb and other Packages
• Create Database Connection
• CREATE, INSERT, READ Operation
• DML and DDL Oepration with Databases
• Web Scraping in Python

12 PYTHON BUILT IN FUNCTION

• Python user defined functions
• Python packages functions
• Defining and calling FunctionThe anonymous • Functions
• Loops and statement in Python
• Python Modules & Packages

13 PYTHON OBJECT ORIENTED

• Overview of OOP
• The self variable
• Constructor
• Types Of Variables
• Namespaces
• Creating Classes and Objects
• Inheritance
• Types of Methods
• Instance Methods
• Static Methods
• Class Methods
• Accessing attributes
• Built-In Class Attributes
• Destroying Objects
• Abstract classes and Interfaces
• Abstract Methods and Abstract class
• Interface in Python
• Abstract classes and Interfaces

14 EXCEPTIONS

• Errors in Python
• Compile-Time Errors
• Runtime Errors
• Logical Errors
• What is Exception?
• Handling an exceptiontry….except…elsetry-finally • clause.
• Argument of an Exception
• Python Standard Exceptions
• Raising an exceptions
• User-Defined Exceptions

15 GRAPHICAL USER INTERFACE

• HTML, CSS, Jquery, Bootstrap
• GUI in Python
• Button Widget
• Label Widget
• Text Widget
• Rest Api

16 DJANGO WEB FRAMEWORK IN PYTHON

• Django overview
• Creating a project
• Apps life cycle
• Admin interface
• Creating views
• URL Mapping
• Template system
• Models
• Form details
• Testing
• Page redirection
• Sending Emails
• Deploying Django framework
• Form processing
• File uploading
• Cookie handling
• Sessions, caching and comments
• RSS,AJAX
• Sending Emails
• GitHub,Bigbucket
• Flask Framework & TkInter GUI Framework
• Overview of Flask Framework
• Installation of Flask and
• Demo Application

17 Database

• DATABASE HANDLING WITH MYSQL
• PYTHON MYSQL DATABASE ACCESS
• CREATE DATABASE CONNECTION
• DML AND DDL OPERATIONS WITH DATABASES
• PERFORMING TRANSACTIONS
• HANDLING DATABASE ERRORS
• DISCONNECTING DATABASE
• DATABASE HANDLING WITH MONGODB
• SQL VS NOSQL
• MONGODB
• PYMONGO
• ESTABLISHING A CONNECTION
• ACCESSING DATABASE
• DML AND DDL OPERATIONS

TensorFlow

• Linking TensorFlow with Keras
• Application of Word Embedding with Word2vec
• Presentation of the Recurent Neurals Networks (GRU, LSTM…)
• Presentation of the Generative adversialNetwork

Introduction to Reinforcement Learning

• Development of mathematics for Reinforcement Learning
• Application of the Monte-Carlo method
• Discovery of the Temporal Difference
• Comparison of learnings: SARSA and Q-Learning

Deep Reinforcement Learning

• Presentation of Deep Q Learning
• Introduction to the Policy Gradient method