Certified Python Full Stack Developer Course

BY
Henry Harvin

Mode

Online

Duration

120 Hours

Fees

₹ 178650 198500

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study, Virtual Classroom
Mode of Delivery Video and Text Based
Frequency of Classes Weekends

Course and certificate fees

Fees information
₹ 178,650  ₹198,500
certificate availability

Yes

certificate providing authority

Henry Harvin

The syllabus

Module 1: Python Basics

  • Introduction, and why python in the industry lot
  • Software required and their installation
  • python( or any language ) basics
  • reference variables
  • where,how,how much memory get allocated during coding? (related to python.exe)
  • what is IDE, different IDE’s available in the market - different flavors/ implementations of python

Module 2: Python

  • Python comments
  • Python identifiers
  • Python data type-both simple and complex
  • Data structure
  • Array, linked list ( singly and doubly ), hashtable
  • Python type casting
  • Need of virtual environment and everything related to it, pip
  • Python type casting
  • Integer catching in python
  • Concept of importing anything
  • Python built-in functions overview
  • Python string class methods overview
  • Python operators
  • Python looping
  • Selective
  • If else
  • If elif elif.............else
  • Nested if else
  • Iterative
  • Transfer looping statements

Module 3: Flask Introduction

  • Introduction and Overview
  • Environment
  • Application
  • Routing
  • Variables rules
  • URL building
  • HTTP methods
  • Templates
  • Static files
  • Request object
  • Sending form data to the template
  • Cookies
  • Sessions
  • Redirect and errors
  • Message flashing
  • File uploading
  • Extensions
  • Mail
  • WTF
  • SQLite
  • SQL Alchemy
  • Sijax
  • Deployment
  • CGI

Module 4: Django Language

  • Covering basics and overview
  • Environment
  • Creating a project
  • The life cycle of Apps
  • Admin interface
  • Creating views
  • Url mapping
  • Template system
  • Models
  • Page redirection
  • Sending Emails
  • Generic Views
  • Form processing
  • File uploading
  • Apache Setup
  • Cookies Handling
  • Sessions
  • Caching
  • Comments
  • RSS
  • AJAX

Module 5: RESTful API

  • Introduction
  • Environment Setup
  • Resources
  • Messages
  • Addressing
  • Methods
  • Statelessness
  • Caching
  • Security
  • Java ( JAX- RS)

Module 6: Full Stack GIT

  • Introduction
  • Basic concepts and key points in GIT
  • Setting up Environment
  • Create operation
  • Clone operation
  • Making changes
  • Review
  • Commit
  • Push
  • Update
  • Stash
  • Move
  • Renaming operation
  • Delete
  • Fixing up mistakes
  • Tagging
  • Patch
  • Managing Branches
  • Solving issues out of Conflicts

Module 7: Logger Overview

  • Introduction
  • Installation
  • Architecture
  • Configuration
  • Various Logging Methods
  • Various Logging Levels
  • Log Formatting
  • Logging in Files
  • Logging in Database

Module 8: Jira Ticketing Tools

  • Introduction and why we require this?
  • Issues related to Tasks
  • Tracking the lifecycle of an Issue
  • Installation 
  • Login
  • Dashboard
  • View Screen
  • Creating an Issue
  • Cloning of an Issue
  • Creating a SubTask
  • Converting Issue to SubTask and Vice-Versa
  • CSV for creating Issue
  • Labeling, Moving, Editing, Mailing, Linking of an Issue
  • View/ Change History
  • Watch and Vote on Issue
  • Advanced Search
  • Reports
  • Pie chart of Workload
  • Created vs Resolved Issues

Module 9: Agile Methodology

  • Introduction
  • Useful terms
  • Charactersitics of Agile Methodology
  • Daily Standup
  • Product Backlog
  • Release Planning
  • Iteration Planning

Module 10: Numpy Library

  • Introduction
  • Creating, Slicing, Indexing of Array
  • Numpy Data types
  • Copy and View
  • Shaping, Reshaping, Iteration of Numpy Array
  • Search, Sort, Filter, Join, Split of Numpy Array
  • Numpy Random Introduction
  • Seaborn module
  • Random permutation
  • Various types of Distributions
  • Numpy fun: - various operations like Creating functions, Simple Arithmetic, Rounding decimals, Logs, Summation, Products, Differences, Finding LCM, GCD, Trigonometric, Hyperbolic, Set operations.

Module 11: Pandas Library

  • Introduction
  • Pandas Series and Dataframes
  • Reading Pandas CSV and JSON
  • Pandas Analyzing Data
  • Removing Duplicates
  • Cleaning Data, Empty cells, Wrong Format, Wrong Data
  • Pandas Correlations

Complimentary Module 1: Soft Skills Development

  • Business Communication 
  • Preparation for the Interview
  • Presentation Skills

Complimentary Module2: Resume Writing

  • Resume Writing Skills

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