๐๐๐ ๐๐๐ฌ๐ ๐๐ญ๐ฎ๐๐ข๐๐ฌ ๐๐จ๐ซ ๐๐ง๐ญ๐๐ซ๐ฏ๐ข๐๐ฐ:
Join for more: https://t.iss.one/sqlanalyst
1. Dannyโs Diner:
Restaurant analytics to understand the customer orders pattern.
Link: https://8weeksqlchallenge.com/case-study-1/
2. Pizza Runner
Pizza shop analytics to optimize the efficiency of the operation
Link: https://8weeksqlchallenge.com/case-study-2/
3. Foodie Fie
Subscription-based food content platform
Link: https://lnkd.in/gzB39qAT
4. Data Bank: Thatโs money
Analytics based on customer activities with the digital bank
Link: https://lnkd.in/gH8pKPyv
5. Data Mart: Fresh is Best
Analytics on Online supermarket
Link: https://lnkd.in/gC5bkcDf
6. Clique Bait: Attention capturing
Analytics on the seafood industry
Link: https://lnkd.in/ggP4JiYG
7. Balanced Tree: Clothing Company
Analytics on the sales performance of clothing store
Link: https://8weeksqlchallenge.com/case-study-7
8. Fresh segments: Extract maximum value
Analytics on online advertising
Link: https://8weeksqlchallenge.com/case-study-8
Join for more: https://t.iss.one/sqlanalyst
1. Dannyโs Diner:
Restaurant analytics to understand the customer orders pattern.
Link: https://8weeksqlchallenge.com/case-study-1/
2. Pizza Runner
Pizza shop analytics to optimize the efficiency of the operation
Link: https://8weeksqlchallenge.com/case-study-2/
3. Foodie Fie
Subscription-based food content platform
Link: https://lnkd.in/gzB39qAT
4. Data Bank: Thatโs money
Analytics based on customer activities with the digital bank
Link: https://lnkd.in/gH8pKPyv
5. Data Mart: Fresh is Best
Analytics on Online supermarket
Link: https://lnkd.in/gC5bkcDf
6. Clique Bait: Attention capturing
Analytics on the seafood industry
Link: https://lnkd.in/ggP4JiYG
7. Balanced Tree: Clothing Company
Analytics on the sales performance of clothing store
Link: https://8weeksqlchallenge.com/case-study-7
8. Fresh segments: Extract maximum value
Analytics on online advertising
Link: https://8weeksqlchallenge.com/case-study-8
โค2๐1
โ
If you're serious about learning Web Development โ follow this roadmap ๐๐ป
1. Learn HTML basics (structure, elements, attributes) ๐
2. Master CSS (selectors, box model, flexbox, grid) ๐จ
3. Understand responsive design: media queries, mobile-first approach ๐ฑ
4. Learn JavaScript fundamentals: variables, loops, functions, DOM manipulation ๐ฅ๏ธ
5. Get familiar with version control using Git (repositories, commits, branches) ๐๏ธ
6. Study JavaScript ES6+ features: arrow functions, promises, async/await ๐
7. Learn about the Document Object Model (DOM) and how to manipulate it ๐
8. Explore front-end frameworks: React, Vue.js, or Angular ๐ง
9. Understand state management concepts (Redux, Context API) ๐
10. Learn about RESTful APIs and how to make API requests (fetch, Axios) ๐
11. Dive into back-end development: choose Node.js with Express or Python with Flask/Django ๐ ๏ธ
12. Understand databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB) ๐พ
13. Learn about authentication and authorization (JWT, OAuth) ๐
14. Explore deployment options: Heroku, Vercel, Netlify ๐
15. Get familiar with web security basics: HTTPS, CORS, XSS, CSRF ๐ก๏ธ
16. Build full-stack projects (CRUD apps, e-commerce site) ๐๏ธ
17. Learn about testing frameworks: Jest for JavaScript or PyTest for Python ๐งช
18. Understand performance optimization techniques (lazy loading, minification) โก
19. Create a personal portfolio website to showcase your projects ๐
20. Stay updated with web technologies: follow blogs, podcasts, and communities ๐ฌ
21. Contribute to open-source projects to gain experience and visibility ๐
22. Network with other developers through meetups or online forums ๐ค
23. Apply for internships or junior developer positions to gain real-world experience ๐ฏ
Tip: Build projects that interest youโthis keeps motivation high!
๐ฌ Tap โค๏ธ for more!
1. Learn HTML basics (structure, elements, attributes) ๐
2. Master CSS (selectors, box model, flexbox, grid) ๐จ
3. Understand responsive design: media queries, mobile-first approach ๐ฑ
4. Learn JavaScript fundamentals: variables, loops, functions, DOM manipulation ๐ฅ๏ธ
5. Get familiar with version control using Git (repositories, commits, branches) ๐๏ธ
6. Study JavaScript ES6+ features: arrow functions, promises, async/await ๐
7. Learn about the Document Object Model (DOM) and how to manipulate it ๐
8. Explore front-end frameworks: React, Vue.js, or Angular ๐ง
9. Understand state management concepts (Redux, Context API) ๐
10. Learn about RESTful APIs and how to make API requests (fetch, Axios) ๐
11. Dive into back-end development: choose Node.js with Express or Python with Flask/Django ๐ ๏ธ
12. Understand databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB) ๐พ
13. Learn about authentication and authorization (JWT, OAuth) ๐
14. Explore deployment options: Heroku, Vercel, Netlify ๐
15. Get familiar with web security basics: HTTPS, CORS, XSS, CSRF ๐ก๏ธ
16. Build full-stack projects (CRUD apps, e-commerce site) ๐๏ธ
17. Learn about testing frameworks: Jest for JavaScript or PyTest for Python ๐งช
18. Understand performance optimization techniques (lazy loading, minification) โก
19. Create a personal portfolio website to showcase your projects ๐
20. Stay updated with web technologies: follow blogs, podcasts, and communities ๐ฌ
21. Contribute to open-source projects to gain experience and visibility ๐
22. Network with other developers through meetups or online forums ๐ค
23. Apply for internships or junior developer positions to gain real-world experience ๐ฏ
Tip: Build projects that interest youโthis keeps motivation high!
๐ฌ Tap โค๏ธ for more!
โค7๐1
Kandinsky 5.0 Video Lite and Kandinsky 5.0 Video Pro generative models on the global text-to-video landscape
๐Pro is currently the #1 open-source model worldwide
๐Lite (2B parameters) outperforms Sora v1.
๐Only Google (Veo 3.1, Veo 3), OpenAI (Sora 2), Alibaba (Wan 2.5), and KlingAI (Kling 2.5, 2.6) outperform Pro โ these are objectively the strongest video generation models in production today. We are on par with Luma AI (Ray 3) and MiniMax (Hailuo 2.3): the maximum ELO gap is 3 points, with a 95% CI of ยฑ21.
Useful links
๐Full leaderboard: LM Arena
๐Kandinsky 5.0 details: technical report
๐Open-source Kandinsky 5.0: GitHub and Hugging Face
๐Pro is currently the #1 open-source model worldwide
๐Lite (2B parameters) outperforms Sora v1.
๐Only Google (Veo 3.1, Veo 3), OpenAI (Sora 2), Alibaba (Wan 2.5), and KlingAI (Kling 2.5, 2.6) outperform Pro โ these are objectively the strongest video generation models in production today. We are on par with Luma AI (Ray 3) and MiniMax (Hailuo 2.3): the maximum ELO gap is 3 points, with a 95% CI of ยฑ21.
Useful links
๐Full leaderboard: LM Arena
๐Kandinsky 5.0 details: technical report
๐Open-source Kandinsky 5.0: GitHub and Hugging Face
โค5
Bookmark these sites FOREVER!!!
โฏ HTML โ learn-html
โฏ CSS โ css-tricks
โฏ JavaScript โ javascript .info
โฏ Python โ realpython
โฏ C โ learn-c
โฏ C++ โ fluentcpp
โฏ Java โ baeldung
โฏ SQL โ sqlbolt
โฏ Go โ learn-golang
โฏ Kotlin โ studytonight
โฏ Swift โ codewithchris
โฏ C# โ learncs
โฏ PHP โ learn-php
โฏ DSA โ techdevguide .withgoogle
โฏ HTML โ learn-html
โฏ CSS โ css-tricks
โฏ JavaScript โ javascript .info
โฏ Python โ realpython
โฏ C โ learn-c
โฏ C++ โ fluentcpp
โฏ Java โ baeldung
โฏ SQL โ sqlbolt
โฏ Go โ learn-golang
โฏ Kotlin โ studytonight
โฏ Swift โ codewithchris
โฏ C# โ learncs
โฏ PHP โ learn-php
โฏ DSA โ techdevguide .withgoogle
โค10
๐ Roadmap to Master DSA (Data Structures Algorithms) in 60 Days! ๐๐ป
๐ Week 1โ2: Foundations
๐น Day 1โ3: Time Space Complexity
๐น Day 4โ7: Recursion basics practice
๐น Day 8โ10: Arrays โ operations, sliding window
๐น Day 11โ14: Strings โ patterns, hashing, two pointers
๐ Week 3โ4: Core Data Structures
๐น Day 15โ17: Linked Lists โ single, double, reverse
๐น Day 18โ20: Stacks Queues โ using arrays linked lists
๐น Day 21โ24: Trees โ traversal, height, BST
๐น Day 25โ28: Binary Search Trees Heaps
๐ Week 5โ6: Algorithms Graphs
๐น Day 29โ31: Sorting โ bubble, merge, quick
๐น Day 32โ35: Binary Search โ on arrays answer
๐น Day 36โ40: Backtracking โ N-Queens, Sudoku
๐น Day 41โ44: Graphs โ BFS, DFS, adjacency list/matrix
๐น Day 45โ48: Dijkstra, Topological Sort, Union-Find
๐ Week 7โ8: Advanced Concepts
๐น Day 49โ52: Dynamic Programming โ Fibonacci, LCS, LIS
๐น Day 53โ55: Greedy โ activity selection, coin change
๐น Day 56โ58: Tries, Segment Trees (basic)
๐น Day 59โ60: Practice full mock tests revise
๐ฌ Tap โค๏ธ for more!
๐ Week 1โ2: Foundations
๐น Day 1โ3: Time Space Complexity
๐น Day 4โ7: Recursion basics practice
๐น Day 8โ10: Arrays โ operations, sliding window
๐น Day 11โ14: Strings โ patterns, hashing, two pointers
๐ Week 3โ4: Core Data Structures
๐น Day 15โ17: Linked Lists โ single, double, reverse
๐น Day 18โ20: Stacks Queues โ using arrays linked lists
๐น Day 21โ24: Trees โ traversal, height, BST
๐น Day 25โ28: Binary Search Trees Heaps
๐ Week 5โ6: Algorithms Graphs
๐น Day 29โ31: Sorting โ bubble, merge, quick
๐น Day 32โ35: Binary Search โ on arrays answer
๐น Day 36โ40: Backtracking โ N-Queens, Sudoku
๐น Day 41โ44: Graphs โ BFS, DFS, adjacency list/matrix
๐น Day 45โ48: Dijkstra, Topological Sort, Union-Find
๐ Week 7โ8: Advanced Concepts
๐น Day 49โ52: Dynamic Programming โ Fibonacci, LCS, LIS
๐น Day 53โ55: Greedy โ activity selection, coin change
๐น Day 56โ58: Tries, Segment Trees (basic)
๐น Day 59โ60: Practice full mock tests revise
๐ฌ Tap โค๏ธ for more!
โค9
๐๐ฅ๐๐ ๐ข๐ป๐น๐ถ๐ป๐ฒ ๐ ๐ฎ๐๐๐ฒ๐ฟ๐ฐ๐น๐ฎ๐๐ ๐๐ ๐๐ป๐ฑ๐๐๐๐ฟ๐ ๐๐
๐ฝ๐ฒ๐ฟ๐๐ ๐
Roadmap to land your dream job in top product-based companies
๐๐ถ๐ด๐ต๐น๐ถ๐ด๐ต๐๐ฒ๐:-
- 90-Day Placement Plan
- Tech & Non-Tech Career Path
- Interview Preparation Tips
- Live Q&A
๐ฅ๐ฒ๐ด๐ถ๐๐๐ฒ๐ฟ ๐๐ผ๐ฟ ๐๐ฅ๐๐๐:-
https://pdlink.in/3Ltb3CE
Date & Time:- 06th January 2026 , 7PM
Roadmap to land your dream job in top product-based companies
๐๐ถ๐ด๐ต๐น๐ถ๐ด๐ต๐๐ฒ๐:-
- 90-Day Placement Plan
- Tech & Non-Tech Career Path
- Interview Preparation Tips
- Live Q&A
๐ฅ๐ฒ๐ด๐ถ๐๐๐ฒ๐ฟ ๐๐ผ๐ฟ ๐๐ฅ๐๐๐:-
https://pdlink.in/3Ltb3CE
Date & Time:- 06th January 2026 , 7PM
โค2
Artificial Intelligence (AI) Roadmap
|
|-- Fundamentals
| |-- Mathematics
| | |-- Linear Algebra
| | |-- Calculus
| | |-- Probability and Statistics
| |
| |-- Programming
| | |-- Python (Focus on Libraries like NumPy, Pandas)
| | |-- Java or C++ (optional but useful)
| |
| |-- Algorithms and Data Structures
| | |-- Graphs and Trees
| | |-- Dynamic Programming
| | |-- Search Algorithms (e.g., A*, Minimax)
|
|-- Core AI Concepts
| |-- Knowledge Representation
| |-- Search Methods (DFS, BFS)
| |-- Constraint Satisfaction Problems
| |-- Logical Reasoning
|
|-- Machine Learning (ML)
| |-- Supervised Learning (Regression, Classification)
| |-- Unsupervised Learning (Clustering, Dimensionality Reduction)
| |-- Reinforcement Learning (Q-Learning, Policy Gradient Methods)
| |-- Ensemble Methods (Random Forest, Gradient Boosting)
|
|-- Deep Learning (DL)
| |-- Neural Networks
| |-- Convolutional Neural Networks (CNNs)
| |-- Recurrent Neural Networks (RNNs)
| |-- Transformers (BERT, GPT)
| |-- Frameworks (TensorFlow, PyTorch)
|
|-- Natural Language Processing (NLP)
| |-- Text Preprocessing (Tokenization, Lemmatization)
| |-- NLP Models (Word2Vec, BERT)
| |-- Applications (Chatbots, Sentiment Analysis, NER)
|
|-- Computer Vision
| |-- Image Processing
| |-- Object Detection (YOLO, SSD)
| |-- Image Segmentation
| |-- Applications (Facial Recognition, OCR)
|
|-- Ethical AI
| |-- Fairness and Bias
| |-- Privacy and Security
| |-- Explainability (SHAP, LIME)
|
|-- Applications of AI
| |-- Healthcare (Diagnostics, Personalized Medicine)
| |-- Finance (Fraud Detection, Algorithmic Trading)
| |-- Retail (Recommendation Systems, Inventory Management)
| |-- Autonomous Vehicles (Perception, Control Systems)
|
|-- AI Deployment
| |-- Model Serving (Flask, FastAPI)
| |-- Cloud Platforms (AWS SageMaker, Google AI)
| |-- Edge AI (TensorFlow Lite, ONNX)
|
|-- Advanced Topics
| |-- Multi-Agent Systems
| |-- Generative Models (GANs, VAEs)
| |-- Knowledge Graphs
| |-- AI in Quantum Computing
Best Resources to learn ML & AI ๐
Learn Python for Free
Prompt Engineering Course
Prompt Engineering Guide
Data Science Course
Google Cloud Generative AI Path
Machine Learning with Python Free Course
Machine Learning Free Book
Artificial Intelligence WhatsApp channel
Hands-on Machine Learning
Deep Learning Nanodegree Program with Real-world Projects
AI, Machine Learning and Deep Learning
Like this post for more roadmaps โค๏ธ
Follow & share the channel link with your friends: t.iss.one/free4unow_backup
ENJOY LEARNING๐๐
|
|-- Fundamentals
| |-- Mathematics
| | |-- Linear Algebra
| | |-- Calculus
| | |-- Probability and Statistics
| |
| |-- Programming
| | |-- Python (Focus on Libraries like NumPy, Pandas)
| | |-- Java or C++ (optional but useful)
| |
| |-- Algorithms and Data Structures
| | |-- Graphs and Trees
| | |-- Dynamic Programming
| | |-- Search Algorithms (e.g., A*, Minimax)
|
|-- Core AI Concepts
| |-- Knowledge Representation
| |-- Search Methods (DFS, BFS)
| |-- Constraint Satisfaction Problems
| |-- Logical Reasoning
|
|-- Machine Learning (ML)
| |-- Supervised Learning (Regression, Classification)
| |-- Unsupervised Learning (Clustering, Dimensionality Reduction)
| |-- Reinforcement Learning (Q-Learning, Policy Gradient Methods)
| |-- Ensemble Methods (Random Forest, Gradient Boosting)
|
|-- Deep Learning (DL)
| |-- Neural Networks
| |-- Convolutional Neural Networks (CNNs)
| |-- Recurrent Neural Networks (RNNs)
| |-- Transformers (BERT, GPT)
| |-- Frameworks (TensorFlow, PyTorch)
|
|-- Natural Language Processing (NLP)
| |-- Text Preprocessing (Tokenization, Lemmatization)
| |-- NLP Models (Word2Vec, BERT)
| |-- Applications (Chatbots, Sentiment Analysis, NER)
|
|-- Computer Vision
| |-- Image Processing
| |-- Object Detection (YOLO, SSD)
| |-- Image Segmentation
| |-- Applications (Facial Recognition, OCR)
|
|-- Ethical AI
| |-- Fairness and Bias
| |-- Privacy and Security
| |-- Explainability (SHAP, LIME)
|
|-- Applications of AI
| |-- Healthcare (Diagnostics, Personalized Medicine)
| |-- Finance (Fraud Detection, Algorithmic Trading)
| |-- Retail (Recommendation Systems, Inventory Management)
| |-- Autonomous Vehicles (Perception, Control Systems)
|
|-- AI Deployment
| |-- Model Serving (Flask, FastAPI)
| |-- Cloud Platforms (AWS SageMaker, Google AI)
| |-- Edge AI (TensorFlow Lite, ONNX)
|
|-- Advanced Topics
| |-- Multi-Agent Systems
| |-- Generative Models (GANs, VAEs)
| |-- Knowledge Graphs
| |-- AI in Quantum Computing
Best Resources to learn ML & AI ๐
Learn Python for Free
Prompt Engineering Course
Prompt Engineering Guide
Data Science Course
Google Cloud Generative AI Path
Machine Learning with Python Free Course
Machine Learning Free Book
Artificial Intelligence WhatsApp channel
Hands-on Machine Learning
Deep Learning Nanodegree Program with Real-world Projects
AI, Machine Learning and Deep Learning
Like this post for more roadmaps โค๏ธ
Follow & share the channel link with your friends: t.iss.one/free4unow_backup
ENJOY LEARNING๐๐
โค3
๐ง๐ผ๐ฝ ๐ฑ ๐๐ป-๐๐ฒ๐บ๐ฎ๐ป๐ฑ ๐ฆ๐ธ๐ถ๐น๐น๐ ๐๐ผ ๐๐ผ๐ฐ๐๐ ๐ผ๐ป ๐ถ๐ป ๐ฎ๐ฌ๐ฎ๐ฒ๐
Start learning industry-relevant data skills today at zero cost!
๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐:- https://pdlink.in/497MMLw
๐๐ & ๐ ๐ :- https://pdlink.in/4bhetTu
๐๐น๐ผ๐๐ฑ ๐๐ผ๐บ๐ฝ๐๐๐ถ๐ป๐ด:- https://pdlink.in/3LoutZd
๐๐๐ฏ๐ฒ๐ฟ ๐ฆ๐ฒ๐ฐ๐๐ฟ๐ถ๐๐:- https://pdlink.in/3N9VOyW
๐ข๐๐ต๐ฒ๐ฟ ๐ง๐ฒ๐ฐ๐ต ๐๐ผ๐๐ฟ๐๐ฒ๐:- https://pdlink.in/4qgtrxU
๐ Enroll Now & Get Certified
Start learning industry-relevant data skills today at zero cost!
๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐:- https://pdlink.in/497MMLw
๐๐ & ๐ ๐ :- https://pdlink.in/4bhetTu
๐๐น๐ผ๐๐ฑ ๐๐ผ๐บ๐ฝ๐๐๐ถ๐ป๐ด:- https://pdlink.in/3LoutZd
๐๐๐ฏ๐ฒ๐ฟ ๐ฆ๐ฒ๐ฐ๐๐ฟ๐ถ๐๐:- https://pdlink.in/3N9VOyW
๐ข๐๐ต๐ฒ๐ฟ ๐ง๐ฒ๐ฐ๐ต ๐๐ผ๐๐ฟ๐๐ฒ๐:- https://pdlink.in/4qgtrxU
๐ Enroll Now & Get Certified
โ
Top Python Interview Questions ๐๐ก
1๏ธโฃ What is a string in Python?
Answer: A string is a sequence of characters enclosed in quotes (single, double, or triple).
Example: "Hello", 'World', '''Multi-line'''
2๏ธโฃ How do you reverse a string in Python?
Answer:
3๏ธโฃ Whatโs the difference between is and ==?
Answer:
โข == checks if values are equal
โข is checks if they are the same object in memory
4๏ธโฃ How do for and while loops differ?
Answer:
โข for loop is used for iterating over a sequence (list, string, etc.)
โข while loop runs as long as a condition is True
5๏ธโฃ What is the use of break, continue, and pass?
Answer:
โข break: exits the loop
โข continue: skips current iteration
โข pass: does nothing (placeholder)
6๏ธโฃ How to check if a substring exists in a string?
Answer:
7๏ธโฃ How do you use if-else conditions?
Answer:
8๏ธโฃ What are f-strings in Python?
Answer: Introduced in Python 3.6 for cleaner string formatting:
9๏ธโฃ How do you count characters or words in a string?
Answer:
๐ What is a nested loop?
Answer: A loop inside another loop:
๐ฌ Tap โค๏ธ for more!
1๏ธโฃ What is a string in Python?
Answer: A string is a sequence of characters enclosed in quotes (single, double, or triple).
Example: "Hello", 'World', '''Multi-line'''
2๏ธโฃ How do you reverse a string in Python?
Answer:
text = "hello"
reversed_text = text[::-1]
3๏ธโฃ Whatโs the difference between is and ==?
Answer:
โข == checks if values are equal
โข is checks if they are the same object in memory
4๏ธโฃ How do for and while loops differ?
Answer:
โข for loop is used for iterating over a sequence (list, string, etc.)
โข while loop runs as long as a condition is True
5๏ธโฃ What is the use of break, continue, and pass?
Answer:
โข break: exits the loop
โข continue: skips current iteration
โข pass: does nothing (placeholder)
6๏ธโฃ How to check if a substring exists in a string?
Answer:
"data" in "data science" # Returns True
7๏ธโฃ How do you use if-else conditions?
Answer:
x = 10
if x > 0:
print("Positive")
else:
print("Non-positive")
8๏ธโฃ What are f-strings in Python?
Answer: Introduced in Python 3.6 for cleaner string formatting:
name = "Riya"
print(f"Hello, {name}")
9๏ธโฃ How do you count characters or words in a string?
Answer:
text.count('a') # Count 'a'
len(text.split()) # Count words
๐ What is a nested loop?
Answer: A loop inside another loop:
for i in range(2):
for j in range(3):
print(i, j)
๐ฌ Tap โค๏ธ for more!
โค4
โ
OOP Interview Questions with Answers Part-2 ๐ก๐ป
11. What is Method Overriding?
It allows a subclass to provide a specific implementation of a method already defined in its superclass.
Example (Java):
12. What is a Constructor?
A constructor is a special method used to initialize objects. It has the same name as the class and no return type.
Runs automatically when an object is created.
13. Types of Constructors:
โข Default Constructor: Takes no parameters.
โข Parameterized Constructor: Takes arguments to set properties.
โข Copy Constructor (C++): Copies data from another object.
14. What is a Destructor?
Used in C++ to clean up memory/resources when an object is destroyed.
In Java,
15. Difference: Abstract Class vs Interface
| Feature | Abstract Class | Interface |
|---------------|----------------------|------------------------|
| Methods | Can have implemented | Only declarations (till Java 8) |
| Inheritance | One abstract class | Multiple interfaces |
| Use case | Partial abstraction | Full abstraction |
16. Can a Class Inherit Multiple Interfaces?
Yes. Java allows a class to implement multiple interfaces, enabling multiple inheritance of type, without ambiguity.
17. What is the super keyword?
Used to refer to the parent class:
โข Access parentโs constructor:
โข Call parent method:
18. What is the this keyword?
Refers to the current class instance. Useful when local and instance variables have the same name.
19. Difference: == vs .equals() in Java
โข
โข
Use
20. What are Static Members?
Static members belong to the class, not individual objects.
โข static variable: shared across all instances
โข static method: can be called without an object
๐ฌ Double Tap โฅ๏ธ for Part-3
11. What is Method Overriding?
It allows a subclass to provide a specific implementation of a method already defined in its superclass.
Example (Java):
class Animal {
void sound() { System.out.println("Animal sound"); }
}
class Dog extends Animal {
void sound() { System.out.println("Bark"); }
}
12. What is a Constructor?
A constructor is a special method used to initialize objects. It has the same name as the class and no return type.
Runs automatically when an object is created.
13. Types of Constructors:
โข Default Constructor: Takes no parameters.
โข Parameterized Constructor: Takes arguments to set properties.
โข Copy Constructor (C++): Copies data from another object.
14. What is a Destructor?
Used in C++ to clean up memory/resources when an object is destroyed.
In Java,
finalize() was used (deprecated now). Java uses garbage collection instead.15. Difference: Abstract Class vs Interface
| Feature | Abstract Class | Interface |
|---------------|----------------------|------------------------|
| Methods | Can have implemented | Only declarations (till Java 8) |
| Inheritance | One abstract class | Multiple interfaces |
| Use case | Partial abstraction | Full abstraction |
16. Can a Class Inherit Multiple Interfaces?
Yes. Java allows a class to implement multiple interfaces, enabling multiple inheritance of type, without ambiguity.
17. What is the super keyword?
Used to refer to the parent class:
โข Access parentโs constructor:
super()โข Call parent method:
super.methodName()18. What is the this keyword?
Refers to the current class instance. Useful when local and instance variables have the same name.
this.name = name;
19. Difference: == vs .equals() in Java
โข
== compares object references (memory address).โข
.equals() compares the content/values.Use
.equals() to compare strings or objects meaningfully.20. What are Static Members?
Static members belong to the class, not individual objects.
โข static variable: shared across all instances
โข static method: can be called without an object
๐ฌ Double Tap โฅ๏ธ for Part-3
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Deadline: 11th January 2026
Eligibility: Open to everyone
Duration: 6 Months
Program Mode: Online
Taught By: IIT Roorkee Professors
Companies majorly hire candidates having Data Science and Artificial Intelligence knowledge these days.
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OOP Interview Questions with Answers Part-3 ๐ก๐ป
21. What is a final class or method?
โข A final class can't be extended.
โข A final method can't be overridden.
Useful for security, immutability (e.g., String class in Java is final).
22. What is object cloning?
โข Creating an exact copy of an object.
โข In Java: use .clone() method from Cloneable interface.
โข Shallow vs Deep cloning:
โ Shallow copies references.
โ Deep copies full object graph.
23. What is a singleton class?
โข A class that allows only one instance.
โข Ensures shared resource (like a config manager or DB connection).
โข Common in design patterns.
24. What are access specifiers?
Control visibility of class members:
โข public โ accessible everywhere
โข private โ only inside the class
โข protected โ inside class subclasses
โข (default) โ same package
25. What is cohesion in OOP?
โข Degree to which class elements belong together.
โข High cohesion = focused responsibility โ better design.
26. What is coupling?
โข Dependency between classes.
โข Low coupling = better modularity, easier maintenance.
27. Difference between tight and loose coupling?
โข Tight coupling: classes are strongly dependent โ harder to modify/test.
โข Loose coupling: minimal dependency โ promotes reusability, flexibility.
28. What is composition vs aggregation?
โข Composition: "part-of" strong relationship โ child can't exist without parent.
Example: Engine in a Car
โข Aggregation: weak association โ child can exist independently.
Example: Student in a University
29. Difference between association, aggregation, and composition?
โข Association: General relationship
โข Aggregation: Whole-part, but loose
โข Composition: Whole-part, tightly bound
30. What is the open/closed principle?
โข From SOLID:
โSoftware entities should be open for extension, but closed for modification.โ
โข Means add new code via inheritance, not by changing existing logic.
๐ฌ Double Tap โฅ๏ธ for Part-3
21. What is a final class or method?
โข A final class can't be extended.
โข A final method can't be overridden.
Useful for security, immutability (e.g., String class in Java is final).
22. What is object cloning?
โข Creating an exact copy of an object.
โข In Java: use .clone() method from Cloneable interface.
โข Shallow vs Deep cloning:
โ Shallow copies references.
โ Deep copies full object graph.
23. What is a singleton class?
โข A class that allows only one instance.
โข Ensures shared resource (like a config manager or DB connection).
โข Common in design patterns.
public class Singleton {
private static Singleton instance = new Singleton();
private Singleton() {}
public static Singleton getInstance() {
return instance;
}
}
24. What are access specifiers?
Control visibility of class members:
โข public โ accessible everywhere
โข private โ only inside the class
โข protected โ inside class subclasses
โข (default) โ same package
25. What is cohesion in OOP?
โข Degree to which class elements belong together.
โข High cohesion = focused responsibility โ better design.
26. What is coupling?
โข Dependency between classes.
โข Low coupling = better modularity, easier maintenance.
27. Difference between tight and loose coupling?
โข Tight coupling: classes are strongly dependent โ harder to modify/test.
โข Loose coupling: minimal dependency โ promotes reusability, flexibility.
28. What is composition vs aggregation?
โข Composition: "part-of" strong relationship โ child can't exist without parent.
Example: Engine in a Car
โข Aggregation: weak association โ child can exist independently.
Example: Student in a University
29. Difference between association, aggregation, and composition?
โข Association: General relationship
โข Aggregation: Whole-part, but loose
โข Composition: Whole-part, tightly bound
30. What is the open/closed principle?
โข From SOLID:
โSoftware entities should be open for extension, but closed for modification.โ
โข Means add new code via inheritance, not by changing existing logic.
๐ฌ Double Tap โฅ๏ธ for Part-3
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