#Mern Full Stack

✅ Backend APIs using Express.js
✅ Server Logic with Node.js
✅ Data Storage in MongoDB
✅ Full JavaScript Development
✅ Routing & Middleware Integration
✅ RESTful API Development
✅ Frontend & Backend Connection
✅ Real-Time Functionality with Socket.io
✅ Deployment with Git & Cloud Platforms

#MERN Full Stack Road Map

Python Training Course Contents:

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Ch 1. Python Introduction

Need for Data Analytics
Python in Data Analysis
History of Python
Python Versions
Python Implementations
Python Installations
Python IDE & Usage
Jupyter Notebooks

Ch 2. Python Basics, Architecture

Python Scripting Options
Basic Operations in Python
Python Scripts, Print()
Single, Multiline Statements
Adding Cells, Saving Notebook
Single, Multi Line Comments
Python : Internal Architecture
Compiler Versus Interpreter

Ch 3. Data Types & Variables

Integer / Int Data Types
Float & String Data Types
Boolean, Binary Types
Sequence Types: List, Tuple
Range, Complex & memview
Retrieving Data Type: type()
Multi Assignments & Casting
Unpack Collection, Outputs

Ch 4. Python Operators

Arithmetic, Assignment Ops
Comparison Operators
Logical, Identity Operators
Member, Bitwise Operators
Operator Precedence
If … Else Statement, Pass
Short Hand If, OR, AND
ELIF and ELSE IF Statements
Expressions, Ternary OPs

Ch 5: Python Loops, Iterations

Python Loop & Realtime Use
Python While Loop Statement
Break and Continue Statement
Using Print with While()
Iterations & Conditions
Exit Conditions & For Loops
Break, Continue & Range
__iter__() and __next__()
iter() and Looping Options

Ch 6: Python Collections

Python Collections (Arrays)
list() Constructor, print()
Python Tuples, Tuple Items
tuple() Constructor, Usage
Python Sets : Syntax Rules
Duplicates, Types, Ordered
Python Dictionaries: Usage
Changeable, Ordered Data
Dictionary Construct, type()

Ch 7: Python Functions

Python Functions & Usage
Function Parameters
Arguments, **kwargs
Default & List Parameters
Python Lambda Functions
Anonymous Functions
Recursive Functions, Usage
Return & Print @ Lamdba

Ch 8: Python Classes & Arrays

Python Classes & Objects
__init__() Function
__str__() Function
Self Parameters & Objects
Python Inheritance & Classes
Parent & Child Classes
__init__() & super() Function
Polymorphism in Python

Ch 9: Python Modules

import Python Modules
Variables in Modules
Built In Modules & dir
datetime module in Python
Date Objections Creation
strftime Method & Usage
imports & datetime.now()
Using Python Constructors

Ch 10: : Python JSON & RegEx

JSON Concepts, Usage
Dictionary & import json
Python Objects into JSON
Formatting & Ordering
json.dumps, print options
Python Regular Expressions
RegEx Module & Function
search() & span() , Strings
Using RegEx with JSON

Ch 11: Python User Inputs & TRY

Try Except, Exception Handling
NameError Resolution
Python Finally Block, Usage
Raise an exception method
TypeError, Scripting in Python
Python User Inputs
Python Index Numbers
Named Indexes, Usage
input() & raw_input()

Ch 12: Python File Handling

File Handling, Activities
r, a, w, x modes
t, b Operations
Read Only Parts
Loop, Write, Close Files
Appending, Overwriting
import os, path.exists
f.open, f.write
f.read, f.close

Ch 13: Data Analytics – Pandas

Python Modules & Pandas
Pandas Codebase & Usage
Installation of Pandas
import pandas.DataFrame
Checking Pandas Version
Pandas Series, arrays
Labels : Creation, Use
series(), print()

Ch 14: Data Analytics – DataFrames

Indexes & Named Options
Locate Row and Load Rows
Row Index & Index Lists
Load Files Into a DataFrame
pd.read_csv() Function
pd.options.display.max_rows
df.to_string() Function
tail() & null() Function

Ch 15: Pandas Transformations

Pandas – Cleaning Data
Replace, Transform Columns
Data Discovery & Column Fill
Identify & Remove Duplicates
dropna(), fillna() Functions
Pandas – Data Correlations
Good & Bad Correlation
Data Plotting & matlib Lib

Ch 16: : SQL DB & Python – 1

SQL & Databases
Azure Data Studio Tool
sp_execute_external_script
Input Data & Result Sets
DDL & DML with Python
SQL_out, SQL_in
Variables & Parameters
Versions, Package List
WITH RESULT SETS Options

Ch 17: SQL & Python – 2

pandas.Series with SQL DBs
Indexing Methods in Realtime
Convert series to data frame
Output values into data.frame
pymssql package in SQL Server
pip list & Package Manager
Python runtime, Py Package
pymssql.connect & Usage
Cursor Variables & Usage

Ch 18: Realtime Case Study

Ch 1. Python Dictionary

Dictionary Creation, Use
Hashing, Copy, Update
Deletion, Sorting
Len(), Inbuilt Functions
Variable Types – python List
Cmp() List Method
Python Dictionary Str(dict)
Programming Concepts
Loops and Sets
Realtime Usage

Ch 2. Python Packages

Package in Python
Creating a package
Package Imports, Modules
Sub Packages Creation
Sub Package Imports
Popular Packages in Python
NumPy & SciPy
Libraries in Python
Python Seaborn
Python framework

Ch 3. Exception Handling

Shell Script Commands
OS operations in Python
File System Shell Methods
os – math – cmd -csv – random
Numpy ( numerical python )
Pandas – sys – Matplotlib;
Common RunTime Errors
Python Custom Exception;
Exception Handling
Try…Except…else,Try…finally

Ch 4: Python Class & Objects

Class variables, Instances
Built in Class Attributes
Objects – Constructors
Modifiers – Self Variable
Python Garbage Collections
Hierarchical Inheritance
Multilevel, Multiple, Hybrid
Overloading & OverRiding
Polymorphism – Abstraction

Ch 5: Regular Expressions

Regular Expression
Regular Expression Patterns
Literals – Repetition Cases
Groups andGrouping
w+ and ^ , s Expressions
re.split function
Regular expression methods
re.match() in Regular Expr
re.search(), re.findall for Text

Ch 6: Multi-Threading

Python Multi-Threading
Thread Synchronization
Multiprocessing
Python Gil & Programming
Thread Control Block (TCB)
Stack Pointers & App Usage
Program Counters in Realtim
Thread State Concept
Python Exception Handling

Ch 7: Python TKinter

Tkinter GUI Program
Components & Events
Adding Controls inTkinter
Entry, Text Widgets
Radio & Check Buttons
Tkinter Forms in Realtime
List Boxes, Menu, ComboBox
Mainloop () & Functions

Ch 8: Python Web & IoT Intro

Python Web Frameworks
Django : Advantages
Web Framework
MVC and MVT – Django
Web Pages using python
HTML5, CSS3 usage
PYTHON Bottle & Pyramid
Falcon ; smart_open in python

SQL SCHOOL

24x7 LIVE Online Server (Lab) with Real-time Databases.
Course includes ONE Real-time Project.

MERN Full Stack Training FAQs

A MERN Full Stack Developer builds complete web applications using the MERN stack — MongoDB, Express.js, React, and Node.js. They handle both the frontend (React) and backend (Node + Express), along with database operations (MongoDB).

Key Tasks:

Design and develop user interfaces (UI) using React
Build server-side APIs and business logic with Node.js and Express
Manage and query data with MongoDB
Ensure app performance, security, and scalability
Integrate frontend and backend seamlessly

What are the Job Roles of an MERN Full Stack?

💼 Top Job Roles:

Job Roles of a MERN Full Stack

- Frontend Development – Build dynamic UIs using React.js
- Backend Development – Create APIs and server logic with Node.js & Express.js
- Database Management – Design and manage data with MongoDB
- Full-stack Integration – Connect frontend, backend, and database
- App Deployment & Maintenance – Deploy, test, and maintain web apps and more..!

What does our MERN Full Stack Training course contains?

The course is carefully curated with below module:
👉🏻Module 1: Full Stack Basics
👉🏻Module 2: REACT.JS
👉🏻Module 3: MongoDB and Node.js

Who can join this course?

Freshers aiming for a career in web development
Students and graduates interested in full-stack programming
Developers wanting to upskill in React, Node.js, and MongoDB
IT professionals looking to become full-stack developers
Anyone with basic programming or web knowledge

No prior experience in full-stack is required — the course starts from basics.

What training modes are available?

Option 1: LIVE Online Training (100% Interactive, step by step, assignments)

Option 2: Self Paced Videos (100% practical, step by step with concept wise assignments)

You may choose any one of these options, same curriculum!

I (Trainer) shall be available for doubts and clarifications, assignment check and review.

Why should I choose SQL School for MERN Full Stack training?

👉🏻 Every session is Practical, Step by Step with Concept wise FAQs !!

👉🏻 100% results with on-time practice. Daily Tasks for every session.

👉🏻 Concept wise tasks be submitted before next class for Job Waiters / Starters.

👉🏻 Concept wise tasks due for submission by Weekends for Working Professionals.

Why Choose SQL School

100% Real-Time and Practical
ISO 9001:2008 Certified
Weekly Mock Interviews
24/7 LIVE Server Access
Realtime Project FAQs
Course Completion Certificate
Placement Assistance
Job Support