🚀 CODING SEEKHO — ZERO TO SUPERSTAR
COMPLETE COURSE SYLLABUS
👨‍🏫 Tutor: Prof. Vikas Singh

Zero to Hero का पूरा syllabus + Advanced Modules
+ Full Stack Development + Data Analytics
+ Data Science + 4 Major Projects

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 01: CORE PYTHON
━━━━━━━━━━━━━━━━━━━━━━

✅ Python Setup
• History and features
• Installation and IDE setup
• Syntax, indentation and comments
• Program execution flow

✅ Data Types
• Variables
• input() and print()
• Type casting
• Numbers, strings and Boolean
• ASCII and Unicode

✅ Operators
• Arithmetic and comparison
• Logical and assignment
• Bitwise, identity and membership

✅ Control Flow
• if, elif, else and nested conditions
• for and while loops
• range(), break and continue
• Loop-else

✅ Collections
• Strings, indexing and slicing
• Lists, tuples, sets and dictionaries
• Built-in methods

✅ Functions
• def, return and arguments
• *args and **kwargs
• Recursion and lambda
• Variable scope

✅ Coding Practice
• Prime numbers
• Fibonacci and factorial
• Armstrong and palindrome
• Digit sums and patterns
• Mini programs

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 02: C PROGRAMMING
━━━━━━━━━━━━━━━━━━━━━━

✅ C Fundamentals
• Compiler and source code
• Tokens and keywords
• Constants and identifiers
• Primitive data types

✅ Input/Output & Operators
• printf() and scanf()
• Format specifiers
• Expressions and type conversion

✅ Decision Making
• if/else and nested if
• switch and conditional operators
• Practical logic problems

✅ Loops
• for, while and do-while
• Nested loops
• break and continue
• Number-pattern problems

✅ Functions
• Function prototypes and parameters
• Recursion and header files
• Variable scope

✅ Arrays & Strings
• 1D and 2D arrays
• Matrices and character arrays
• Standard string functions

✅ Memory & Practice
• Pointers
• Structures and unions
• Dynamic memory allocation basics
• Menu-driven programs

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 03: DSA
DATA STRUCTURES & ALGORITHMS
━━━━━━━━━━━━━━━━━━━━━━

✅ Algorithm Basics
• Pseudocode and flowcharts
• Time and space complexity
• Big-O fundamentals

✅ Core Techniques
• Arrays and strings
• Recursion and basic pointers
• Problem decomposition

✅ Linear Data Structures
• Singly and doubly linked lists
• Stacks and queues
• Circular queue
• Applications

✅ Searching
• Linear search
• Binary search
• Practical searching problems

✅ Sorting
• Bubble sort
• Selection sort
• Insertion sort
• Merge sort
• Quick sort
• Complexity comparison

✅ Non-Linear Data Structures
• Trees and binary search trees
• Tree traversals
• Heaps and graphs
• BFS and DFS basics

✅ Problem Practice
• Introduction to hashing
• Two-pointer technique
• Sliding-window technique
• Coding assignments

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 04: C++ PROGRAMMING
━━━━━━━━━━━━━━━━━━━━━━

✅ C++ Basics
• Syntax and namespaces
• Input/output streams
• Functions and references
• Function overloading
• Default parameters

✅ Classes & Objects
• Class design
• Constructors and destructors
• Access modifiers
• this pointer
• Static members

✅ OOP Principles
• Encapsulation
• Inheritance
• Polymorphism
• Virtual functions
• Abstraction

✅ Advanced C++
• Operator overloading
• Templates
• Exception handling
• Overview of file streams

✅ Standard Template Library
• vector and pair
• stack and queue
• map and set
• Iterators and string
• Standard algorithms

✅ Practice
• OOP exercises
• Data structure implementations
• Problem-solving tasks

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 05: CORE JAVA
━━━━━━━━━━━━━━━━━━━━━━

✅ Java Environment
• JDK, JRE and JVM
• Setup and class structure
• First Java program

✅ Language Fundamentals
• Variables and casting
• Operators
• Control statements
• Loops and switch

✅ Methods & Data
• Methods and overloading
• Arrays and strings
• StringBuilder
• Recursion

✅ Object-Oriented Java
• Classes and constructors
• this and super
• Inheritance
• Encapsulation
• Polymorphism

✅ Java Essentials
• Interfaces and abstract classes
• Packages and access levels
• static and final
• Enums🚀 CODING SEEKHO — ZERO TO SUPERSTAR
COMPLETE COURSE SYLLABUS
👨‍🏫 Tutor: Prof. Vikas Singh

Zero to Hero का पूरा syllabus + Advanced Modules
+ Full Stack Development + Data Analytics
+ Data Science + 4 Major Projects

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 01: CORE PYTHON
━━━━━━━━━━━━━━━━━━━━━━

✅ Python Setup
• History and features
• Installation and IDE setup
• Syntax, indentation and comments
• Program execution flow

✅ Data Types
• Variables
• input() and print()
• Type casting
• Numbers, strings and Boolean
• ASCII and Unicode

✅ Operators
• Arithmetic and comparison
• Logical and assignment
• Bitwise, identity and membership

✅ Control Flow
• if, elif, else and nested conditions
• for and while loops
• range(), break and continue
• Loop-else

✅ Collections
• Strings, indexing and slicing
• Lists, tuples, sets and dictionaries
• Built-in methods

✅ Functions
• def, return and arguments
• *args and **kwargs
• Recursion and lambda
• Variable scope

✅ Coding Practice
• Prime numbers
• Fibonacci and factorial
• Armstrong and palindrome
• Digit sums and patterns
• Mini programs

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 02: C PROGRAMMING
━━━━━━━━━━━━━━━━━━━━━━

✅ C Fundamentals
• Compiler and source code
• Tokens and keywords
• Constants and identifiers
• Primitive data types

✅ Input/Output & Operators
• printf() and scanf()
• Format specifiers
• Expressions and type conversion

✅ Decision Making
• if/else and nested if
• switch and conditional operators
• Practical logic problems

✅ Loops
• for, while and do-while
• Nested loops
• break and continue
• Number-pattern problems

✅ Functions
• Function prototypes and parameters
• Recursion and header files
• Variable scope

✅ Arrays & Strings
• 1D and 2D arrays
• Matrices and character arrays
• Standard string functions

✅ Memory & Practice
• Pointers
• Structures and unions
• Dynamic memory allocation basics
• Menu-driven programs

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 03: DSA
DATA STRUCTURES & ALGORITHMS
━━━━━━━━━━━━━━━━━━━━━━

✅ Algorithm Basics
• Pseudocode and flowcharts
• Time and space complexity
• Big-O fundamentals

✅ Core Techniques
• Arrays and strings
• Recursion and basic pointers
• Problem decomposition

✅ Linear Data Structures
• Singly and doubly linked lists
• Stacks and queues
• Circular queue
• Applications

✅ Searching
• Linear search
• Binary search
• Practical searching problems

✅ Sorting
• Bubble sort
• Selection sort
• Insertion sort
• Merge sort
• Quick sort
• Complexity comparison

✅ Non-Linear Data Structures
• Trees and binary search trees
• Tree traversals
• Heaps and graphs
• BFS and DFS basics

✅ Problem Practice
• Introduction to hashing
• Two-pointer technique
• Sliding-window technique
• Coding assignments

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 04: C++ PROGRAMMING
━━━━━━━━━━━━━━━━━━━━━━

✅ C++ Basics
• Syntax and namespaces
• Input/output streams
• Functions and references
• Function overloading
• Default parameters

✅ Classes & Objects
• Class design
• Constructors and destructors
• Access modifiers
• this pointer
• Static members

✅ OOP Principles
• Encapsulation
• Inheritance
• Polymorphism
• Virtual functions
• Abstraction

✅ Advanced C++
• Operator overloading
• Templates
• Exception handling
• Overview of file streams

✅ Standard Template Library
• vector and pair
• stack and queue
• map and set
• Iterators and string
• Standard algorithms

✅ Practice
• OOP exercises
• Data structure implementations
• Problem-solving tasks

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 05: CORE JAVA
━━━━━━━━━━━━━━━━━━━━━━

✅ Java Environment
• JDK, JRE and JVM
• Setup and class structure
• First Java program

✅ Language Fundamentals
• Variables and casting
• Operators
• Control statements
• Loops and switch

✅ Methods & Data
• Methods and overloading
• Arrays and strings
• StringBuilder
• Recursion

✅ Object-Oriented Java
• Classes and constructors
• this and super
• Inheritance
• Encapsulation
• Polymorphism

✅ Java Essentials
• Interfaces and abstract classes
• Packages and access levels
• static and final
• Enums

✅ Collections & Tools
• Collections and generics
• Exception handling
• Thread basics
• Overview of file input/output

✅ Practice
• Console-based Student/Course Record Application
• Reusable classes

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 06: ADVANCED JAVA
━━━━━━━━━━━━━━━━━━━━━━

✅ JDBC
• Drivers and database connections
• PreparedStatement and ResultSet
• CRUD operations

✅ HTTP & Web
• Request-response fundamentals
• Web project structure
• Servlet life cycle

✅ Servlets
• GET and POST
• Request parameters
• Forwarding and redirects
• Introduction to web filters

✅ JSP
• JavaServer Pages
• Expression Language
• JSTL awareness

✅ Sessions & MVC
• Cookies and sessions
• Form validation
• DAO pattern
• MVC design pattern

✅ Integration
• JSP + Servlet + JDBC + SQL workflow
• Introduction to deployment

✅ Mini Project
• Student Registration/Login Web Application
• Database integration

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 07: ADVANCED PYTHON
━━━━━━━━━━━━━━━━━━━━━━

✅ Python OOP
• Classes and objects
• Constructors
• Inheritance
• Polymorphism
• Abstraction
• Encapsulation

✅ Exception Handling
• try, except, else and finally
• raise
• Custom exceptions
• Error-handling patterns

✅ File Handling
• Text, CSV and JSON files
• Read, write and append
• with statement
• File paths

✅ Functional Python
• Closures and decorators
• map() and filter()
• Comprehensions
• Iterators and generators

✅ Professional Tools
• Modules and packages
• Virtual environments and pip
• Regular expressions
• Logging
• Testing basics

✅ APIs & Automation
• requests library
• API consumption
• JSON responses
• Useful automation scripts

✅ Snake Game
• pygame graphics
• Controls, food and score
• Collision detection
• Restart functionality

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 08: PYTHON DATA LIBRARIES
━━━━━━━━━━━━━━━━━━━━━━

✅ NumPy
• ndarray and data types
• Shapes, indexing and slicing
• Broadcasting
• Vectorization

✅ Pandas
• Series and DataFrames
• Filtering and cleaning
• CSV/Excel data handling
• Joins, groupby and pivots

✅ Matplotlib
• Line and bar charts
• Scatter and pie charts
• Histograms
• Labels and customization

✅ Seaborn
• Heatmaps and distributions
• Correlations
• Statistical chart examples

✅ Plotly Introduction
• Interactive charts
• Visual exploration overview

✅ Notebooks & EDA
• Jupyter notebooks
• Statistics
• Exploratory Data Analysis
• Reporting

✅ Practice
• Clean a messy dataset
• Produce a short analysis notebook

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 09: HTML, CSS & JAVASCRIPT
━━━━━━━━━━━━━━━━━━━━━━

✅ HTML
• Semantic tags
• Links and images
• Tables and forms
• Accessibility basics

✅ CSS
• Selectors and box model
• Positioning and typography
• Flexbox and Grid
• Responsive design

✅ JavaScript Core
• Variables and data types
• Operators and conditions
• Loops and functions
• Objects

✅ DOM & Events
• Selectors and DOM manipulation
• Event handling
• Client-side form validation

✅ Asynchronous JavaScript
• Promises
• async/await
• fetch API
• JSON
• Browser storage

✅ Frontend Practice
• Responsive portfolio page
• Dynamic user interface
• Small API-based webpage

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 10: SQL + DATA ANALYTICS
+ POWER BI
━━━━━━━━━━━━━━━━━━━━━━

✅ Relational SQL
• Tables and keys
• Database design
• SELECT and WHERE
• GROUP BY and HAVING

✅ Advanced Queries
• JOINs and ORDER BY
• Subqueries
• Aggregate functions
• Introduction to window functions

✅ Data Preparation
• Excel basics
• Missing values and duplicates
• Data quality
• KPI definition

✅ Python Analytics
• Data cleaning using Pandas
• Descriptive statistics
• Exploratory analysis

✅ Power BI
• Power Query
• Relationships and data modeling
• DAX measures
• Visuals and slicers

✅ Visualization & Reporting
• Dashboard layout
• Metrics and reporting
• Communicating data insights

✅ Practice
• Sales and revenue analysis
• SQL + Pandas + Power BI

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 11: DATA SCIENCE
+ MACHINE LEARNING
━━━━━━━━━━━━━━━━━━━━━━

✅ Data Science Foundations
• Data science life cycle
• Problem framing
• Probability and statistics basics✅ Collections & Tools
• Collections and generics
• Exception handling
• Thread basics
• Overview of file input/output

✅ Practice
• Console-based Student/Course Record Application
• Reusable classes

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 06: ADVANCED JAVA
━━━━━━━━━━━━━━━━━━━━━━

✅ JDBC
• Drivers and database connections
• PreparedStatement and ResultSet
• CRUD operations

✅ HTTP & Web
• Request-response fundamentals
• Web project structure
• Servlet life cycle

✅ Servlets
• GET and POST
• Request parameters
• Forwarding and redirects
• Introduction to web filters

✅ JSP
• JavaServer Pages
• Expression Language
• JSTL awareness

✅ Sessions & MVC
• Cookies and sessions
• Form validation
• DAO pattern
• MVC design pattern

✅ Integration
• JSP + Servlet + JDBC + SQL workflow
• Introduction to deployment

✅ Mini Project
• Student Registration/Login Web Application
• Database integration

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 07: ADVANCED PYTHON
━━━━━━━━━━━━━━━━━━━━━━

✅ Python OOP
• Classes and objects
• Constructors
• Inheritance
• Polymorphism
• Abstraction
• Encapsulation

✅ Exception Handling
• try, except, else and finally
• raise
• Custom exceptions
• Error-handling patterns

✅ File Handling
• Text, CSV and JSON files
• Read, write and append
• with statement
• File paths

✅ Functional Python
• Closures and decorators
• map() and filter()
• Comprehensions
• Iterators and generators

✅ Professional Tools
• Modules and packages
• Virtual environments and pip
• Regular expressions
• Logging
• Testing basics

✅ APIs & Automation
• requests library
• API consumption
• JSON responses
• Useful automation scripts

✅ Snake Game
• pygame graphics
• Controls, food and score
• Collision detection
• Restart functionality

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 08: PYTHON DATA LIBRARIES
━━━━━━━━━━━━━━━━━━━━━━

✅ NumPy
• ndarray and data types
• Shapes, indexing and slicing
• Broadcasting
• Vectorization

✅ Pandas
• Series and DataFrames
• Filtering and cleaning
• CSV/Excel data handling
• Joins, groupby and pivots

✅ Matplotlib
• Line and bar charts
• Scatter and pie charts
• Histograms
• Labels and customization

✅ Seaborn
• Heatmaps and distributions
• Correlations
• Statistical chart examples

✅ Plotly Introduction
• Interactive charts
• Visual exploration overview

✅ Notebooks & EDA
• Jupyter notebooks
• Statistics
• Exploratory Data Analysis
• Reporting

✅ Practice
• Clean a messy dataset
• Produce a short analysis notebook

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 09: HTML, CSS & JAVASCRIPT
━━━━━━━━━━━━━━━━━━━━━━

✅ HTML
• Semantic tags
• Links and images
• Tables and forms
• Accessibility basics

✅ CSS
• Selectors and box model
• Positioning and typography
• Flexbox and Grid
• Responsive design

✅ JavaScript Core
• Variables and data types
• Operators and conditions
• Loops and functions
• Objects

✅ DOM & Events
• Selectors and DOM manipulation
• Event handling
• Client-side form validation

✅ Asynchronous JavaScript
• Promises
• async/await
• fetch API
• JSON
• Browser storage

✅ Frontend Practice
• Responsive portfolio page
• Dynamic user interface
• Small API-based webpage

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 10: SQL + DATA ANALYTICS
+ POWER BI
━━━━━━━━━━━━━━━━━━━━━━

✅ Relational SQL
• Tables and keys
• Database design
• SELECT and WHERE
• GROUP BY and HAVING

✅ Advanced Queries
• JOINs and ORDER BY
• Subqueries
• Aggregate functions
• Introduction to window functions

✅ Data Preparation
• Excel basics
• Missing values and duplicates
• Data quality
• KPI definition

✅ Python Analytics
• Data cleaning using Pandas
• Descriptive statistics
• Exploratory analysis

✅ Power BI
• Power Query
• Relationships and data modeling
• DAX measures
• Visuals and slicers

✅ Visualization & Reporting
• Dashboard layout
• Metrics and reporting
• Communicating data insights

✅ Practice
• Sales and revenue analysis
• SQL + Pandas + Power BI

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 11: DATA SCIENCE
+ MACHINE LEARNING
━━━━━━━━━━━━━━━━━━━━━━

✅ Data Science Foundations
• Data science life cycle
• Problem framing
• Probability and statistics basics

✅ Data Preparation
• Exploratory Data Analysis
• Data cleaning and preprocessing
• Encoding and scaling
• Train/test split

✅ Supervised Machine Learning
• Linear regression
• Logistic regression
• Decision trees
• Random forests
• Implementation using scikit-learn

✅ Model Evaluation
• MAE and RMSE
• Accuracy
• Precision and recall
• F1 score
• Cross-validation

✅ Unsupervised Machine Learning
• K-means clustering
• Introduction to model interpretation

✅ Real Project
• House Price Prediction
OR Student Placement Prediction
• Project report

✅ Communicating Results
• Model limitations
• Evaluation insights
• Clear presentation of results

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 12: SPRING BOOT
+ JAVA REST APIs
━━━━━━━━━━━━━━━━━━━━━━

✅ Spring Foundation
• Spring Core
• IoC and Dependency Injection
• Beans and Maven
• Spring Boot project setup

✅ MVC & Application Layers
• Controllers and services
• Repositories and DTOs
• Clean project structure

✅ REST APIs
• GET, POST, PUT and DELETE
• HTTP status codes
• JSON
• Validation and exceptions

✅ Database Layer
• Spring Data JPA
• Hibernate mappings
• MySQL integration
• Transactions

✅ Testing & Security
• Postman
• API testing basics
• Authentication concepts
• Logging

✅ Packaging & Deployment
• Properties and profiles
• Build process
• Deployment concepts

✅ Project
• Course Management REST API
• CRUD operations
• Validation and database integration

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 13: MERN FULL STACK
━━━━━━━━━━━━━━━━━━━━━━

MongoDB + Express.js + React.js + Node.js

✅ MongoDB
• Documents and collections
• CRUD operations and queries
• Indexes
• Mongoose schemas

✅ Node.js
• Runtime and npm
• Modules
• Asynchronous code
• Environment variables
• Error handling

✅ Express.js
• Routers and middleware
• REST endpoints
• Validation
• Error handling

✅ React.js
• JSX and components
• Props and state
• Hooks
• Forms and routing
• API integration

✅ Full Stack Workflow
• React-to-Node API calls
• JWT/authentication overview
• Roles
• CRUD workflows

✅ Deployment & Collaboration
• Git and GitHub
• Introduction to app hosting/deployment

✅ Project
• Full Stack Job Portal
OR Learning Platform
• Login and responsive user interface

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 14: APIs
+ DEVELOPER WORKFLOW
━━━━━━━━━━━━━━━━━━━━━━

✅ REST Fundamentals
• HTTP methods
• URL routing
• JSON and status codes
• Stateless APIs

✅ API Tools
• Postman requests
• Headers and parameters
• Tokens
• Basic automated tests

✅ Git & GitHub
• Repositories and commits
• Branches
• Pull requests
• Project README files

✅ Integration
• Frontend/backend communication
• Database-backed CRUD operations

✅ Deployment Basics
• Configuration
• Environment variables
• Build output
• Hosting overview

✅ Code Quality
• Readable naming
• Validation and debugging
• Project documentation

━━━━━━━━━━━━━━━━━━━━━━
💻 FOUR MAJOR PROJECTS
━━━━━━━━━━━━━━━━━━━━━━

1️⃣ DATA ANALYTICS PROJECT
Sales Performance Dashboard

Technologies:
SQL + Pandas + Power BI

• Clean customer and order datasets
• Prepare meaningful KPIs
• Write SQL queries for sales, revenue
and category performance
• Build interactive Power BI charts,
slicers and a summary dashboard
• Present insights and suggested
business improvements

2️⃣ DATA SCIENCE PROJECT
Prediction Model

Technologies:
Python + Pandas + scikit-learn

• Choose House Price Prediction
OR Student Placement Prediction
• Perform EDA and feature preprocessing
• Create train/test splits
• Train regression/classification models
• Evaluate model results
• Submit notebook, predictions, charts
and an explanatory report

3️⃣ SPRING BOOT PROJECT
Course Management REST API

Technologies:
Java + Spring Boot + JPA + MySQL

• Design controllers, services,
repositories and database tables
• Implement CRUD endpoints
• Add validation and status codes
• Test APIs in Postman
• Connect APIs to persistent data
• Document setup, endpoints
and demonstration examples

4️⃣ MERN FULL STACK PROJECT
Job Portal / Learning Platform

Technologies:
MongoDB + Express.js + React.js + Node.js✅ Data Preparation
• Exploratory Data Analysis
• Data cleaning and preprocessing
• Encoding and scaling
• Train/test split

✅ Supervised Machine Learning
• Linear regression
• Logistic regression
• Decision trees
• Random forests
• Implementation using scikit-learn

✅ Model Evaluation
• MAE and RMSE
• Accuracy
• Precision and recall
• F1 score
• Cross-validation

✅ Unsupervised Machine Learning
• K-means clustering
• Introduction to model interpretation

✅ Real Project
• House Price Prediction
OR Student Placement Prediction
• Project report

✅ Communicating Results
• Model limitations
• Evaluation insights
• Clear presentation of results

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 12: SPRING BOOT
+ JAVA REST APIs
━━━━━━━━━━━━━━━━━━━━━━

✅ Spring Foundation
• Spring Core
• IoC and Dependency Injection
• Beans and Maven
• Spring Boot project setup

✅ MVC & Application Layers
• Controllers and services
• Repositories and DTOs
• Clean project structure

✅ REST APIs
• GET, POST, PUT and DELETE
• HTTP status codes
• JSON
• Validation and exceptions

✅ Database Layer
• Spring Data JPA
• Hibernate mappings
• MySQL integration
• Transactions

✅ Testing & Security
• Postman
• API testing basics
• Authentication concepts
• Logging

✅ Packaging & Deployment
• Properties and profiles
• Build process
• Deployment concepts

✅ Project
• Course Management REST API
• CRUD operations
• Validation and database integration

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 13: MERN FULL STACK
━━━━━━━━━━━━━━━━━━━━━━

MongoDB + Express.js + React.js + Node.js

✅ MongoDB
• Documents and collections
• CRUD operations and queries
• Indexes
• Mongoose schemas

✅ Node.js
• Runtime and npm
• Modules
• Asynchronous code
• Environment variables
• Error handling

✅ Express.js
• Routers and middleware
• REST endpoints
• Validation
• Error handling

✅ React.js
• JSX and components
• Props and state
• Hooks
• Forms and routing
• API integration

✅ Full Stack Workflow
• React-to-Node API calls
• JWT/authentication overview
• Roles
• CRUD workflows

✅ Deployment & Collaboration
• Git and GitHub
• Introduction to app hosting/deployment

✅ Project
• Full Stack Job Portal
OR Learning Platform
• Login and responsive user interface

━━━━━━━━━━━━━━━━━━━━━━
📘 MODULE 14: APIs
+ DEVELOPER WORKFLOW
━━━━━━━━━━━━━━━━━━━━━━

✅ REST Fundamentals
• HTTP methods
• URL routing
• JSON and status codes
• Stateless APIs

✅ API Tools
• Postman requests
• Headers and parameters
• Tokens
• Basic automated tests

✅ Git & GitHub
• Repositories and commits
• Branches
• Pull requests
• Project README files

✅ Integration
• Frontend/backend communication
• Database-backed CRUD operations

✅ Deployment Basics
• Configuration
• Environment variables
• Build output
• Hosting overview

✅ Code Quality
• Readable naming
• Validation and debugging
• Project documentation

━━━━━━━━━━━━━━━━━━━━━━
💻 FOUR MAJOR PROJECTS
━━━━━━━━━━━━━━━━━━━━━━

1️⃣ DATA ANALYTICS PROJECT
Sales Performance Dashboard

Technologies:
SQL + Pandas + Power BI

• Clean customer and order datasets
• Prepare meaningful KPIs
• Write SQL queries for sales, revenue
and category performance
• Build interactive Power BI charts,
slicers and a summary dashboard
• Present insights and suggested
business improvements

2️⃣ DATA SCIENCE PROJECT
Prediction Model

Technologies:
Python + Pandas + scikit-learn

• Choose House Price Prediction
OR Student Placement Prediction
• Perform EDA and feature preprocessing
• Create train/test splits
• Train regression/classification models
• Evaluate model results
• Submit notebook, predictions, charts
and an explanatory report

3️⃣ SPRING BOOT PROJECT
Course Management REST API

Technologies:
Java + Spring Boot + JPA + MySQL

• Design controllers, services,
repositories and database tables
• Implement CRUD endpoints
• Add validation and status codes
• Test APIs in Postman
• Connect APIs to persistent data
• Document setup, endpoints
and demonstration examples

4️⃣ MERN FULL STACK PROJECT
Job Portal / Learning Platform

Technologies:
MongoDB + Express.js + React.js + Node.js

• Build responsive React screens
for real application workflows
• Create Express/Node REST APIs
• Build MongoDB data models
• Add user login and role concepts
• Implement CRUD and API integration
• Prepare GitHub repository,
README and project demo

━━━━━━━━━━━━━━━━━━━━━━
📌 THIS BATCH INCLUDES BOTH LEVELS
━━━━━━━━━━━━━━━━━━━━━━

✅ Complete Zero to Hero Foundation
Core Python + C + C++ + DSA
+ Core Java + Advanced Java

✅ Advanced Learning
Advanced Python + Data Libraries
+ HTML + CSS + JavaScript
+ SQL + Data Analytics + Power BI
+ Data Science + Machine Learning
+ Spring Boot + MERN Full Stack
+ REST APIs + GitHub
+ 4 Major Projects• Build responsive React screens
for real application workflows
• Create Express/Node REST APIs
• Build MongoDB data models
• Add user login and role concepts
• Implement CRUD and API integration
• Prepare GitHub repository,
README and project demo

━━━━━━━━━━━━━━━━━━━━━━
📌 THIS BATCH INCLUDES BOTH LEVELS
━━━━━━━━━━━━━━━━━━━━━━

✅ Complete Zero to Hero Foundation
Core Python + C + C++ + DSA
+ Core Java + Advanced Java

✅ Advanced Learning
Advanced Python + Data Libraries
+ HTML + CSS + JavaScript
+ SQL + Data Analytics + Power BI
+ Data Science + Machine Learning
+ Spring Boot + MERN Full Stack
+ REST APIs + GitHub
+ 4 Major Projects