Introduction to Artificial Intelligence – Definitions, Evolution, and Scope

 

What is Artificial Intelligence?

Artificial Intelligence (AI) is a branch of computer science that aims to create machines that can perform tasks typically requiring human intelligence. These tasks include learning, reasoning, problem-solving, perception, and language understanding.

Classic Definition:

"AI is the science and engineering of making intelligent machines." – John McCarthy (Father of AI).

Evolution of AI: A Quick Timeline

Era	Highlights
1950s	Turing Test proposed by Alan Turing to check machine intelligence
1956	Term “Artificial Intelligence” coined at Dartmouth Conference
1970s	Expert Systems emerged
1980s	Rise of Machine Learning
2000s	Big Data & faster computation boosted AI growth
2012-Present	Deep Learning, Neural Networks, Generative AI (like ChatGPT) revolutionized AI capabilities

AI vs ML vs DL – Clearing the Confusion

Feature	Artificial Intelligence	Machine Learning	Deep Learning
Goal	Mimic human intelligence	Learn from data	Learn complex patterns
Input	Rules + Data	Data	Big data
Example	Expert Systems	Email Spam Filter	Self-driving Cars (Vision)

Branches of AI

1. Machine Learning (ML) – Systems that learn from data

2. Natural Language Processing (NLP) – Language understanding (ChatGPT, Alexa)

3. Computer Vision (CV) – Image & video analysis (Face Recognition, OCR)

4. Robotics – Physical machines that interact with the world

5. Expert Systems – Rule-based decision systems

6. Speech Recognition – Voice-based interaction (Siri, Google Assistant)

1. 🧠 Machine Learning (ML)

📌 What it is:

Machine Learning is a branch of AI that allows machines to learn from data and improve their performance over time without being explicitly programmed.

🔍 Types of ML:

• Supervised Learning – Learns from labeled data
  Example: Predicting house prices based on size, location, etc.

• Unsupervised Learning – Finds hidden patterns in unlabeled data
  Example: Customer segmentation for marketing

• Reinforcement Learning – Learns through trial and error
  Example: AI playing chess or controlling a robot arm

✅ Applications:

• Spam filters in Gmail

• Fraud detection in banks

• Product recommendations on Amazon

---

2. 💬 Natural Language Processing (NLP)

📌 What it is:

NLP helps machines understand, interpret, and generate human language — both written and spoken.

🔍 Key Tasks:

• Text Classification – Detecting spam, sentiment

• Language Translation – Google Translate

• Text Generation – ChatGPT, content generators

• Speech Recognition – Converting voice to text (e.g., Alexa)

✅ Applications:

• Chatbots & virtual assistants (Siri, ChatGPT)

• Language translation apps

• Sentiment analysis in social media

---

3. 👁️‍🗨️ Computer Vision (CV)

📌 What it is:

Computer Vision enables machines to see, process, and understand images or videos — similar to human vision.

🔍 Core Techniques:

• Image Classification – Identifying objects in images

• Object Detection – Locating multiple objects

• Facial Recognition – Matching faces in security systems

• Optical Character Recognition (OCR) – Reading text from images

✅ Applications:

• Self-driving cars (detecting pedestrians and signals)

• Face unlock in smartphones

• Medical image analysis (X-ray, MRI)

---

4. 🤖 Robotics

📌 What it is:

Robotics is the intersection of AI and mechanical engineering to build intelligent physical machines (robots) that can interact with the real world.

🔍 Capabilities:

• Perception (sensing environment)

• Planning (decision-making)

• Movement (motor control)

✅ Applications:

• Industrial robots for assembly lines

• Delivery robots & drones

• Surgical robots in healthcare

---

5. 🎓 Expert Systems

📌 What it is:

Expert Systems are AI programs that simulate the decision-making ability of a human expert using a rule-based system.

🔍 Components:

• Knowledge Base – Stores facts and rules

• Inference Engine – Applies rules to known facts to infer new information

✅ Applications:

• Medical diagnosis systems

• Loan approval systems in banking

• Legal advice and compliance tools

---

6. 🗣️ Speech Recognition

📌 What it is:

This branch allows machines to convert spoken language into text and understand the context of voice commands.

🔍 Techniques:

• Acoustic modeling

• Language modeling

• Voice activity detection

✅ Applications:

• Voice assistants (Google Assistant, Siri)

• Transcription tools

• Voice commands in smart homes

---

7. 🧩 Planning and Reasoning

📌 What it is:

This area deals with machines that can think logically, plan actions, and solve problems to reach specific goals — similar to human decision-making.

🔍 Tasks:

• Path planning (e.g., GPS routing)

• Strategic game playing (e.g., chess)

• Scheduling problems (e.g., airline crew scheduling)

✅ Applications:

• AI in games (Chess, Go)

• Route optimization in logistics

• Business process automation

---

🧠 Summary Table:

Branch	Focus	Real-World Examples
Machine Learning	Learning from data	Email filters, recommendations
NLP	Understanding language	Chatbots, translation
Computer Vision	Visual understanding	Face ID, object detection
Robotics	Physical interaction	Assembly robots, drones
Expert Systems	Decision-making	Medical diagnosis
Speech Recognition	Voice to text	Alexa, dictation
Planning & Reasoning	Goal-oriented actions	GPS, game AI

Why Should You Learn AI?

• Career: AI engineers, data scientists, ML engineers are in high demand

• Innovation: AI fuels smart apps, self-driving cars, recommendation engines

• Research: AI plays a major role in future research in healthcare, automation, etc.

Real-World Examples of AI

• Netflix recommending you shows based on your watch history.

• Google Maps calculating the fastest route using real-time traffic.

• Tesla Autopilot using CV & sensors to drive semi-autonomously.

• ChatGPT answering your questions using language understanding.

Summary

• AI is about creating machines with human-like intelligence.

• It has evolved from rule-based systems to data-driven learning models.

• Understanding AI is foundational to grasping Generative AI, which we'll explore next.

 

🌩️ What is the Cloud? Cloud Computing Models & Deployment Types

Cloud computing is everywhere — from Netflix and YouTube to banking and gaming apps. But what exactly is the cloud, and why is it so important for businesses and individuals?

In this blog, we’ll simplify:

• What cloud computing means

• Core cloud service models (IaaS, PaaS, SaaS)

• Major deployment models (Public, Private, Hybrid, and more)

---

🌐 What is Cloud Computing?

Cloud computing is the delivery of computing services — like servers, storage, databases, networking, software — over the internet (“the cloud”).

Instead of buying and maintaining physical infrastructure, you can rent these resources from cloud providers like AWS (Amazon Web Services), Microsoft Azure, or Google Cloud.

🧠 Example:

Instead of buying a USB drive, imagine you upload files to Google Drive or Dropbox — that’s cloud storage!

---

🎯 Benefits of Cloud Computing

Benefit	Description
Cost-Efficiency	No upfront hardware costs. Pay-as-you-go model.
Scalability	Instantly scale up or down based on demand.
High Availability	Resources are distributed across multiple regions for fault tolerance.
Speed & Agility	Quickly deploy apps or services with minimal setup.
Security	Providers offer encryption, IAM, and compliance tools out-of-the-box.

☁️ Cloud Computing Service Models (IaaS, PaaS, SaaS)

These define how much control vs convenience you get.

1. IaaS – Infrastructure as a Service

You get virtual servers, storage, and networking.

➡️ You manage the OS, apps, etc.

🔹 Examples: AWS EC2, Azure Virtual Machines, Google Compute Engine

2. PaaS – Platform as a Service

The provider manages infrastructure and OS.

➡️ You deploy and manage your app.

🔹 Examples: AWS Elastic Beanstalk, Google App Engine, Heroku

3. SaaS – Software as a Service

Ready-to-use software delivered via the cloud.

➡️ You just use it.

🔹 Examples: Gmail, Zoom, Salesforce, Microsoft 365

---

🏗️ Cloud Deployment Models

Deployment models define where your cloud services run — and who controls them.

1. Public Cloud

• Services are delivered over the internet.

• Shared by multiple customers.

• Managed by a third-party like AWS.

✅ Cost-effective

✅ Scalable

⚠️ Less customization

🔹 Example: Hosting a blog on AWS using S3 + CloudFront

---

2. Private Cloud

• Services are used exclusively by a single organization.

• Hosted on-premise or via third-party vendors.

✅ More control & security

⚠️ Higher cost

🔹 Example: Bank hosting customer data on its own private servers

---

3. Hybrid Cloud

• Combines public and private cloud environments.

• Data and applications can move between them.

✅ Flexible

✅ Business continuity

⚠️ Complexity

🔹 Example: Hospital storing patient data privately but using public cloud for analytics

---

4. Multi-Cloud

• Uses multiple cloud providers (e.g., AWS + Azure) for different tasks.

✅ Avoid vendor lock-in

✅ Redundancy

⚠️ Complex to manage

---

📘 AWS Cloud Practitioner Exam Tips

• Understand the differences between IaaS, PaaS, SaaS

• Know real-world examples of each deployment model

• Focus on benefits of cloud computing from a business point of view

---

🧠 Quick Recap

Term	Meaning	Example
IaaS	Rent hardware resources	AWS EC2, Azure VMs
PaaS	Build apps without managing hardware	AWS Elastic Beanstalk
SaaS	Use ready-made software	Gmail, Microsoft 365
Public Cloud	Shared infrastructure, over the internet	AWS, GCP
Private Cloud	Dedicated environment	On-premise data centers
Hybrid Cloud	Mix of public and private	AWS Outposts + On-premise
Multi-Cloud	Uses multiple cloud providers	AWS + Azure combo

Ultimate Roadmap to Crack Any Tech Interview in 2025

 

🚀 Introduction

Are you preparing for placements or job interviews in 2025? Whether you are a college student or a working professional switching domains, cracking a technical interview demands structured preparation, practice, and smart strategy.

This blog is your ultimate guide, covering every essential topic, step-by-step roadmap, and daily practice plan to make you interview-ready!

---

🧭 Why a Roadmap Matters?

Without a plan, you waste time jumping between random topics. This roadmap ensures you:

• Cover all core CS subjects

• Practice DSA regularly

• Prepare for aptitude + HR rounds

• Focus on resume, projects, and mock interviews

• Get domain-specific prep (AI/ML, Cloud, etc.)

---

🛣️ 4-Month Tech Interview Roadmap

---

✅ Month 1: Core Computer Science Concepts

Focus on Theory Subjects asked in 90% interviews

• DBMS: ER Model, Normalization, SQL Queries

• Operating System (OS): Process, Deadlock, Scheduling

• Computer Networks (CN): OSI Model, TCP/IP, Routing

• OOPs: Concepts, Inheritance, Polymorphism (C++/Java)

• Compiler & COA (Basics)

📌 Daily Goal: 2 topics + 10 MCQs

📌 Bonus: Make short handwritten notes for revision

---

✅ Month 2: DSA (Data Structures & Algorithms)

Every tech company expects solid DSA skills

• Must-Do Topics:

  • Arrays, Strings

  • Linked Lists, Stacks, Queues

  • Trees, Graphs

  • Sorting, Searching

  • Dynamic Programming

• Practice Platform: LeetCode, GFG, InterviewBit

📌 Daily Goal: 2 questions easy → medium → hard

📌 Weekly Practice: 1 mock test

---

✅ Month 3: Aptitude + HR Round + Resume

Non-tech rounds matter equally

• Aptitude: Percentages, Time & Work, Probability

• Reasoning: Blood Relations, Puzzles, Coding-Decoding

• HR Prep:

  • Tell me about yourself

  • Why should we hire you?

  • Strengths, Weaknesses, Project explanation

• Resume:

  • Project highlights

  • 1-page clean format

  • No grammar errors

📌 Daily Goal: 10 Aptitude + 1 HR answer

📌 Bonus: Practice interview with a friend or mock tool

---

✅ Month 4: Specialization Focus + Mock Interviews

Domain-specific practice for your role

• AI/ML Roles:

  • Python, Numpy, Pandas, Sklearn

  • ML Models (LogReg, SVM, Clustering, etc.)

• Cloud Roles (AWS/GCP/Azure):

  • EC2, S3, IAM, VPC, Load Balancers

• Web Dev:

  • HTML, CSS, JS

  • React/Node + DB + APIs

📌 Daily Goal: 1 project/code explanation

📌 Weekly Goal: 1 mock interview

---

🔁 Final Checklist (Before Interview)

✅ All core subjects revised

✅ 100+ DSA questions solved

✅ Resume ready

✅ 3+ mock interviews done

✅ HR answers practiced

✅ At least 1 project solidly explained

📩 Bookmark this blog, follow daily, and crack your dream job!

What is a Flowchart? Properties and Flowchart to Check Buzz Number in C Programming

What is a Flowchart?

A flowchart is a graphical representation of an algorithm or process using different symbols such as rectangles, diamonds, ovals, and arrows to show the flow of control step by step.

Flowcharts are widely used in programming, system design, and process documentation because they help visualize logic clearly and intuitively.

Standard Flowchart Symbols

Symbol	Shape	Use
Start/End	Oval	Denotes the beginning or end of the flowchart.
Process	Rectangle	Represents an action, process, or instruction.
Decision	Diamond	Used for branching based on yes/no or true/false conditions.
Input/Output	Parallelogram	Indicates data input or output operations.
Flow Lines	Arrows	Show the direction of control flow between symbols.
Connector	Small Circle	Connects different parts of flowchart, especially when diagram continues on another page.

Properties of a Good Flowchart

1. Clarity: It should be easily understandable with well-defined symbols and logical flow.

2. Logical Sequence: The process should proceed in proper sequence from start to end.

3. Standard Symbols: Use standard symbols (rectangle for process, diamond for decision, etc.) accepted in flowchart conventions.

4. Flow Lines: Use arrows to clearly show the direction of flow from one step to another.

5. Simplicity: Keep it simple and avoid unnecessary details.

6. Modularity: Break complex processes into sub-processes or separate flowcharts if needed.

Buzz Number Definition

A number is called a Buzz Number if:

• It ends with digit 7, or

• It is divisible by 7.

Flowchart to Check Buzz Number

Sample C Program

#include <stdio.h>

int main() {

    int num;

    printf("Enter a number: ");

    scanf("%d", &num);

    if (num % 10 == 7 || num % 7 == 0)

        printf("%d is a Buzz number.\n", num);

    else

        printf("%d is not a Buzz number.\n", num);

    return 0;

}

Summary

• Flowchart: Visual tool using standard symbols to describe an algorithm.

• Properties: Clear, logical, uses proper symbols, and arrows.

• Buzz Number: Ends with 7 or divisible by 7.

• Symbols: Oval (start/end), rectangle (process), diamond (decision), parallelogram (I/O), arrows (flow).

If you found this post helpful, share and explore our other blogs for detailed solutions on PPS with C exam questions!

BCS201 PROGRAMMING FOR PROBLEM SOLVING THEORY EXAMINATION 2023-24 Solution

 Section A

 attempt all questions in brief.

a. 1Nibble =………..Bytes. 

Answer:
1 Nibble = 0.5 Bytes

Explanation: 1 Nibble = 4 bits; 1 Byte = 8 bits → 4/8 = 0.5 Bytes

b. Find the value of variable max in the following code: -

 int a=10, b=20; int max= (a>b)? a: b;  

Answer:
max = 20

Explanation: Since a = 10 and b = 20, the condition (a > b) is false. So the ternary operator returns b.




c. Define Explicit type conversion with suitable example. 

Answer:
Explicit type conversion, also known as type casting, is when a programmer manually converts one data type into another.

Example:

float x = 5.75;

int y = (int)x;  // Explicitly converting float to int

Here, (int)x converts 5.75 to 5 by truncating the decimal part.

d. Write a C program to print all natural numbers from 10 to 100. 

Answer: 

#include <stdio.h>

int main() {

    int i;

    for(i = 10; i <= 100; i++) {

        printf("%d ", i);

    }

    return 0;

}

This program uses a for loop to print natural numbers from 10 to 100.

e. Define Pointer to Pointer.  

Answer:
A Pointer to Pointer is a variable that stores the address of another pointer.

Syntax Example:

int a = 5;

int *p = &a;

int **pp = &p;

Here, pp is a pointer to the pointer p, which in turn points to variable a.

f. Find the output of following code: - 

#include<stdio.h>

 #defien a 2*2+2 

void main () { 

int b,c; b=2/a; 

c=b+4;

printf(“Value of variable b and c are %d%d respectively ”, b,c); 

} 

Answer:
There are two issues:

1. Typo: #defien should be #define.

2. Macro expansion issue due to missing parentheses.

Corrected Code:

#include<stdio.h>
#define a (2*2+2)  // a becomes (2*2+2) = 6

void main() {
    int b, c;
    b = 2 / a;  // 2 / 6 = 0
    c = b + 4;  // 0 + 4 = 4
    printf("Value of variable b and c are %d%d respectively", b, c);
}

Output:Value of variable b and c are 04 respectively.

g. Draw block diagram to represent doubly linked list.

Answer:

Each node in a doubly linked list contains:

• A pointer to the previous node

• The data

• A pointer to the next node

Explanation:

• The first node’s prev points to NULL.

• The last node’s next points to NULL.

• Every node is bidirectionally linked.

-------------------------------------------------------------------------------------------------------------------

Mastering Spring Core – IoC & Dependency Injection (DI)

 

🌟 1. What is Spring Framework?

Spring Framework is a powerful, lightweight Java platform for building enterprise-grade applications. It provides a comprehensive infrastructure support for developing Java applications.

✅ Main Goals:

• Loose Coupling

• Easy Testing

• Better Code Maintainability

• Integration with Web, Security, AOP, ORM, and Microservices (via Spring Boot)

🌀 2. What is Inversion of Control (IoC)?

📌 Definition:

Inversion of Control means transferring the control of object creation and dependency management to the Spring container, instead of manually creating objects using new keyword.

#BCS403,#Object Oriented Programming with Java

---

📦 Real-Life Analogy:

• Without IoC: You go to a restaurant, go to the kitchen, cook food, serve yourself.

• With IoC: You sit at a table and order. Chef (Spring container) serves you everything — you just consume.

---

🔧 Before Spring (Tightly Coupled Code):

public class Car {

    Engine engine = new Engine(); // tightly coupled

}

🌱 With Spring IoC (Loose Coupling):

public class Car {

    private Engine engine;

    public Car(Engine engine) { // injected via constructor

        this.engine = engine;

    }

}

And Spring container injects it for you.

🔗 3. What is Dependency Injection (DI)?

📌 Definition:

Dependency Injection is a design pattern used to achieve IoC. The object’s dependencies are injected by the container, not created manually.

✅ Types of Dependency Injection in Spring:

Type	Description	Use Case
Constructor DI	Dependencies are passed via constructor	Immutable objects
Setter DI	Dependencies injected via setter method	Optional dependencies
Field DI	Using annotations (@Autowired)	Quick setup

1️⃣ Constructor Injection (Constructor DI)

📌 Best for: Immutable dependencies (dependencies that shouldn’t change after object creation).

 Code Example:

🧩 Engine.java

 package com.example;

public class Engine {

    public void start() {

        System.out.println("🚀 Engine started via Constructor DI");

    }

}

🚗 Car.java

package com.example;

public class Car {

    private Engine engine;

    // Constructor DI

    public Car(Engine engine) {

        this.engine = engine;

    }

    public void drive() {

        engine.start();

        System.out.println("🏎️ Car is moving...");

    }

}

⚙️ applicationContext.xml

<bean id="engine" class="com.example.Engine"/>
<bean id="car" class="com.example.Car">
    <constructor-arg ref="engine"/>
</bean>

▶️ Output:
🚀 Engine started via Constructor DI  
🏎️ Car is moving...

2️⃣ Setter Injection (Setter DI)
📌 Best for: Optional or changeable dependencies
 Code Example:

🧩 Engine.java
package com.example;
public class Engine {
    public void start() {
        System.out.println("🚀 Engine started via Setter DI");
    }
}
🚗 Car.java
package com.example;

public class Car {
    private Engine engine;

    // Setter Method for Injection
    public void setEngine(Engine engine) {
        this.engine = engine;
    }

    public void drive() {
        engine.start();
        System.out.println("🏎️ Car is moving...");
    }
}

⚙️ applicationContext.xml
<bean id="engine" class="com.example.Engine"/>
<bean id="car" class="com.example.Car">
    <property name="engine" ref="engine"/>
</bean>

▶️ Output:
🚀 Engine started via Setter DI  
🏎️ Car is moving...

3️⃣ Field Injection (Annotation-Based @Autowired)
📌 Best for: Quick setup; not best for testing or immutability
Code Example:
🧩 Engine.java
package com.example;

import org.springframework.stereotype.Component;
@Component
public class Engine {
    public void start() {
        System.out.println("🚀 Engine started via Field DI");
    }
}

🚗 Car.java

package com.example;

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Component;
@Component
public class Car {
    @Autowired
    private Engine engine;  // Field Injection
    public void drive() {
        engine.start();
        System.out.println("🏎️ Car is moving...");
    }
}

📄 Java Config – AppConfig.java
package com.example;

import org.springframework.context.annotation.ComponentScan;
import org.springframework.context.annotation.Configuration;
@Configuration
@ComponentScan("com.example")
public class AppConfig {}

▶️ Main Class – App.java
package com.example;

import org.springframework.context.ApplicationContext;
import org.springframework.context.annotation.AnnotationConfigApplicationContext;
public class App {
    public static void main(String[] args) {
        ApplicationContext context = new AnnotationConfigApplicationContext(AppConfig.class);
        Car car = context.getBean(Car.class);
        car.drive();
    }
}

▶️ Output:
🚀 Engine started via Field DI  
🏎️ Car is moving...
🔍 Summary Table




DI Type
Config Style
Benefits  
     Drawbacks




Constructor DI
XML / Java Config
Immutable, recommended for required deps   
   More verbose if too many         dependencies




Setter DI
XML / Java Config
Good for optional properties
   Allows mutation (not ideal for all cases)




Field DI
Annotation-based
Short and clean
 Difficult to test, not           recommended for large apps



📘 4. How Spring Manages IoC and DI?
🔧 Spring provides a container called ApplicationContext, which:
Manages Beans
Injects Dependencies
Controls Bean Lifecycle
⚙️ 5. Let's Build a Simple Spring Core Project (Step-by-Step)
✅ Project Goal: Inject Engine object into Car using Spring
🛠 Step-by-Step (XML + Annotation Based DI)
🔶 STEP 1: Open Spring Initializr
Go to: 👉 https://start.spring.io
This is an official tool by Spring to generate a ready-to-use Spring Boot project.

🔶 STEP 2: Fill in Project Metadata
Fill the following fields:

Field
  What to Fill
Project
  Maven
Language
  Java
Spring Boot
  Keep latest version (e.g., 3.2.x)
Group
  com.example
Artifact
  spring-di-example
Name
  spring-di-example
Description
  Spring Boot project to demonstrate DI
Packaging
  Jar
Java Version
  17 or 21 (based on your system/IDE)
🔶 STEP 3: Add Dependencies
Click on the “ADD DEPENDENCIES” button and add:

✅ Spring Web
✅ Spring Context
✅ Spring Boot DevTools (for hot reload in development)
🔶 STEP 4: Generate Project
Click the “GENERATE” button.
A .zip file will be downloaded → Unzip it on your computer.
🔶 STEP 5: Open Project in IDE
Open IntelliJ IDEA, VS Code, or Eclipse.
Select: File → Open → Navigate to unzipped folder → Open the folder
Wait for the project to load and Maven to finish downloading dependencies.
🔶 STEP 6: Create Your Java Classes
Inside src/main/java/com/example/springdiexample/, create these files:
📁 Project Structure:
spring-core-example/
 ├── pom.xml
 └── src/
     └── main/
         ├── java/com/example/
         │     ├── Engine.java
         │     ├── Car.java
         │     └── App.java
         └── resources/
               └── applicationContext.xml
📄 pom.xml

🔶 STEP 6: Create Your Java Classes
Inside src/main/java/com/example/springdiexample/, create these files:
📄 Engine.java
package com.example.springdiexample;

import org.springframework.stereotype.Component;
@Component
public class Engine {
    public void start() {
        System.out.println("🚀 Engine started via Constructor DI");
    }
}

📄 Car.java
package com.example.springdiexample;

import org.springframework.stereotype.Component;

@Component
public class Car {
    private final Engine engine;
    // Constructor-based DI
    public Car(Engine engine) {
        this.engine = engine;
    }
    public void drive() {
        engine.start();
        System.out.println("🏎️ Car is moving via Spring Boot DI...");
    }
}

🔶 STEP 7: Modify the Main Class
Open the auto-generated main class:
📄 SpringDiExampleApplication.java
package com.example.springdiexample;

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.CommandLineRunner;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
@SpringBootApplication
public class SpringDiExampleApplication implements CommandLineRunner {
    @Autowired
    private Car car;
    public static void main(String[] args) {
        SpringApplication.run(SpringDiExampleApplication.class, args);
    }
    @Override
    public void run(String... args) {
        car.drive();  // This method runs after the app starts
    }
}

🔶 STEP 8: Run Your Application
Right-click on SpringDiExampleApplication.java
Select Run
✅ Output You’ll See in Console

🚀 Engine started via Constructor DI  
🏎️ Car is moving via Spring Boot DI...

🎯 You Just Built a Spring Boot App!

And you used:
Spring Initializr to generate boilerplate code
@Component to register beans
Constructor Dependency Injection
@Autowired and CommandLineRunner to run code on startup




🔄 Quick Recap

Step
Task
1
Go to Spring Initializr
2
Fill metadata and dependencies
3
Generate and unzip project
4
Open in IDE
5
Create Engine, Car class
6
Modify main class with DI
7
Run and see output

🎯 Benefits of This Flow

Feature
Why it helps?
Spring Initializr     
      No manual setup, production-ready base
@Component  
      Bean auto-registration
Constructor DI
      Clean and testable
CommandLineRunner
      Code runs at startup – great for testing

📚 Important Interview/Exam Questions
What is Inversion of Control in Spring? Explain with example.
What are the types of Dependency Injection? Which is preferred and why?
Difference between BeanFactory and ApplicationContext?
What is the role of @Autowired?
How is Spring loosely coupled?
What is the difference between XML vs Annotation based configuration?
What is the life cycle of a Spring bean?