𝐒𝐐𝐋 𝐂𝐚𝐬𝐞 𝐒𝐭𝐮𝐝𝐢𝐞𝐬 𝐟𝐨𝐫 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰:

Join for more: https://news.1rj.ru/str/sqlanalyst

1. Danny’s 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
Subnoscription-based food content platform
Link: https://lnkd.in/gzB39qAT

4. Data Bank: That’s 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

✅ If you're serious about learning Web Development — follow this roadmap 🌐💻

1. Learn HTML basics (structure, elements, attributes) 📄
2. Master CSS (selectors, box model, flexbox, grid) 🎨
3. Understand responsive design: media queries, mobile-first approach 📱
4. Learn JavaScript fundamentals: variables, loops, functions, DOM manipulation 🖥️
5. Get familiar with version control using Git (repositories, commits, branches) 🗂️
6. Study JavaScript ES6+ features: arrow functions, promises, async/await 🚀
7. Learn about the Document Object Model (DOM) and how to manipulate it 📜
8. Explore front-end frameworks: React, Vue.js, or Angular 🔧
9. Understand state management concepts (Redux, Context API) 📊
10. Learn about RESTful APIs and how to make API requests (fetch, Axios) 🌐
11. Dive into back-end development: choose Node.js with Express or Python with Flask/Django 🛠️
12. Understand databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB) 💾
13. Learn about authentication and authorization (JWT, OAuth) 🔑
14. Explore deployment options: Heroku, Vercel, Netlify 🚀
15. Get familiar with web security basics: HTTPS, CORS, XSS, CSRF 🛡️
16. Build full-stack projects (CRUD apps, e-commerce site) 🏗️
17. Learn about testing frameworks: Jest for JavaScript or PyTest for Python 🧪
18. Understand performance optimization techniques (lazy loading, minification) ⚡
19. Create a personal portfolio website to showcase your projects 🌟
20. Stay updated with web technologies: follow blogs, podcasts, and communities 💬
21. Contribute to open-source projects to gain experience and visibility 🌍
22. Network with other developers through meetups or online forums 🤝
23. Apply for internships or junior developer positions to gain real-world experience 🎯

Tip: Build projects that interest you—this keeps motivation high!

💬 Tap ❤️ for more!

Kandinsky 5.0 Video Lite and Kandinsky 5.0 Video Pro generative models on the global text-to-video landscape

🔘Pro is currently the #1 open-source model worldwide
🔘Lite (2B parameters) outperforms Sora v1.
🔘Only Google (Veo 3.1, Veo 3), OpenAI (Sora 2), Alibaba (Wan 2.5), and KlingAI (Kling 2.5, 2.6) outperform Pro — 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 ±21.

Useful links
🔘Full leaderboard: LM Arena
🔘Kandinsky 5.0 details: technical report
🔘Open-source Kandinsky 5.0: GitHub and Hugging Face

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❯ HTML ➟ learn-html
❯ CSS ➟ css-tricks
❯ JavaScript ➟ javanoscript .info
❯ Python ➟ realpython
❯ C ➟ learn-c
❯ C++ ➟ fluentcpp
❯ Java ➟ baeldung
❯ SQL ➟ sqlbolt
❯ Go ➟ learn-golang
❯ Kotlin ➟ studytonight
❯ Swift ➟ codewithchris
❯ C# ➟ learncs
❯ PHP ➟ learn-php
❯ DSA ➟ techdevguide .withgoogle

🚀 Roadmap to Master DSA (Data Structures  Algorithms) in 60 Days! 📚💻

📅 Week 1–2: Foundations 
🔹 Day 1–3: Time  Space Complexity 
🔹 Day 4–7: Recursion basics  practice 
🔹 Day 8–10: Arrays – operations, sliding window 
🔹 Day 11–14: Strings – patterns, hashing, two pointers

📅 Week 3–4: Core Data Structures 
🔹 Day 15–17: Linked Lists – single, double, reverse 
🔹 Day 18–20: Stacks  Queues – using arrays  linked lists 
🔹 Day 21–24: Trees – traversal, height, BST 
🔹 Day 25–28: Binary Search Trees  Heaps

📅 Week 5–6: Algorithms  Graphs 
🔹 Day 29–31: Sorting – bubble, merge, quick 
🔹 Day 32–35: Binary Search – on arrays  answer 
🔹 Day 36–40: Backtracking – N-Queens, Sudoku 
🔹 Day 41–44: Graphs – BFS, DFS, adjacency list/matrix 
🔹 Day 45–48: Dijkstra, Topological Sort, Union-Find

📅 Week 7–8: Advanced Concepts 
🔹 Day 49–52: Dynamic Programming – Fibonacci, LCS, LIS 
🔹 Day 53–55: Greedy – activity selection, coin change 
🔹 Day 56–58: Tries, Segment Trees (basic) 
🔹 Day 59–60: Practice full mock tests  revise

💬 Tap ❤️ for more!

Useful Git Commands📝👨🏻‍💻

React ❤️ for more like this

𝗙𝗥𝗘𝗘 𝗢𝗻𝗹𝗶𝗻𝗲 𝗠𝗮𝘀𝘁𝗲𝗿𝗰𝗹𝗮𝘀𝘀 𝗕𝘆 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗘𝘅𝗽𝗲𝗿𝘁𝘀 😍

Roadmap to land your dream job in top product-based companies

𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝗲𝘀:-
- 90-Day Placement Plan
- Tech & Non-Tech Career Path
- Interview Preparation Tips
- Live Q&A

𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:- 

https://pdlink.in/3Ltb3CE

Date & Time:- 06th January 2026 , 7PM

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

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✅ Top Python Interview Questions 🐍💡

1️⃣ 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'''

2️⃣ How do you reverse a string in Python?
Answer:

text = "hello"
reversed_text = text[::-1]

3️⃣ What’s the difference between is and ==?
Answer:
• == checks if values are equal
• is checks if they are the same object in memory

4️⃣ How do for and while loops differ?
Answer:
• for loop is used for iterating over a sequence (list, string, etc.)
• while loop runs as long as a condition is True

5️⃣ What is the use of break, continue, and pass?
Answer:
• break: exits the loop
• continue: skips current iteration
• pass: does nothing (placeholder)

6️⃣ How to check if a substring exists in a string?
Answer:

"data" in "data science"  # Returns True

7️⃣ How do you use if-else conditions?
Answer:

x = 10  
if x > 0:  
    print("Positive")  
else:  
    print("Non-positive")

8️⃣ What are f-strings in Python?
Answer: Introduced in Python 3.6 for cleaner string formatting:

name = "Riya"
print(f"Hello, {name}")

9️⃣ How do you count characters or words in a string?
Answer:

text.count('a')      # Count 'a'  
len(text.split())    # Count words

🔟 What is a nested loop?
Answer: A loop inside another loop:

for i in range(2):  
    for j in range(3):  
        print(i, j)

💬 Tap ❤️ for more!

✅ OOP Interview Questions with Answers Part-2 💡💻

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:
• Default Constructor: Takes no parameters.
• Parameterized Constructor: Takes arguments to set properties.
• 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:
• Access parent’s constructor: super()
• 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
• == compares object references (memory address).
• .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.
• static variable: shared across all instances
• static method: can be called without an object

💬 Double Tap ♥️ for Part-3

✅ OOP Interview Questions with Answers Part-3 💡💻

21. What is a final class or method?
• A final class can't be extended.
• A final method can't be overridden.
Useful for security, immutability (e.g., String class in Java is final).

22. What is object cloning?
• Creating an exact copy of an object.
• In Java: use .clone() method from Cloneable interface.
• Shallow vs Deep cloning:
– Shallow copies references.
– Deep copies full object graph.

23. What is a singleton class?
• A class that allows only one instance.
• Ensures shared resource (like a config manager or DB connection).
• 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:
• public – accessible everywhere
• private – only inside the class
• protected – inside class subclasses
• (default) – same package

25. What is cohesion in OOP?
• Degree to which class elements belong together.
• High cohesion = focused responsibility → better design.

26. What is coupling?
• Dependency between classes.
• Low coupling = better modularity, easier maintenance.

27. Difference between tight and loose coupling?
• Tight coupling: classes are strongly dependent → harder to modify/test.
• Loose coupling: minimal dependency → promotes reusability, flexibility.

28. What is composition vs aggregation?
• Composition: "part-of" strong relationship → child can't exist without parent.
Example: Engine in a Car
• Aggregation: weak association → child can exist independently.
Example: Student in a University

29. Difference between association, aggregation, and composition?
• Association: General relationship
• Aggregation: Whole-part, but loose
• Composition: Whole-part, tightly bound

30. What is the open/closed principle?
• From SOLID:
“Software entities should be open for extension, but closed for modification.”
• Means add new code via inheritance, not by changing existing logic.

💬 Double Tap ♥️ for Part-3

𝗙𝗥𝗘𝗘 𝗢𝗻𝗹𝗶𝗻𝗲 𝗠𝗮𝘀𝘁𝗲𝗿𝗰𝗹𝗮𝘀𝘀 𝗢𝗻 𝗟𝗮𝘁𝗲𝘀𝘁 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀😍

- Data Science 
- AI/ML
- Data Analytics
- UI/UX
- Full-stack Development 

Get Job-Ready Guidance in Your Tech Journey

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https://pdlink.in/4sw5Ev8

Date :- 11th January 2026

✅ OOP Interview Questions with Answers Part-4 🧠💻

31. What is SOLID in OOP?
SOLID is a set of 5 design principles for writing maintainable, scalable OOP code. It stands for:
S – Single Responsibility
O – Open/Closed
L – Liskov Substitution
I – Interface Segregation
D – Dependency Inversion

32. Explain each SOLID principle briefly:
• Single Responsibility – A class should do one thing only.
• Open/Closed – Classes should be open for extension, but closed for modification.
• Liskov Substitution – Subclasses should replace their parent classes without breaking functionality.
• Interface Segregation – Prefer small, specific interfaces over large ones.
• Dependency Inversion – Depend on abstractions, not concrete classes.

33. What is Liskov Substitution Principle?
If a class S is a subclass of class T, objects of type T should be replaceable with objects of type S without affecting the program.
Example: A Bird base class with a fly() method may break if Penguin inherits it (Penguins can't fly). So, design must respect capabilities.

34. What is Dependency Inversion Principle?
High-level modules should not depend on low-level modules. Both should depend on abstractions.
Example: A service class should depend on an interface, not a specific implementation.

35. What is object slicing?
Occurs when an object of a derived class is assigned to a base class variable — the extra properties of the derived class are "sliced off."
Example: C++ object slicing when passing by value.

36. What are getters and setters?
Special methods used to get and set values of private variables in a class.
They support encapsulation and validation.

def get_name(self): return self._name  
def set_name(self, name): self._name = name

37. What is a virtual function?
A function declared in the base class and overridden in the derived class, using the virtual keyword (in C++). Enables run-time polymorphism.

38. What is early binding vs late binding?
• Early Binding (Static): Method call is resolved at compile time (e.g., method overloading).
• Late Binding (Dynamic): Method call is resolved at run-time (e.g., method overriding).

39. What is dynamic dispatch?
It’s the process where the method to be invoked is determined at runtime based on the object’s actual type — used in method overriding (late binding).

40. What is a pure virtual function?
A virtual function with no implementation in the base class — makes the class abstract.
Syntax (C++):

virtual void draw() = 0;

💬 Double Tap ♥️ for Part-5

𝗛𝗶𝗴𝗵 𝗗𝗲𝗺𝗮𝗻𝗱𝗶𝗻𝗴 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗪𝗶𝘁𝗵 𝗣𝗹𝗮𝗰𝗲𝗺𝗲𝗻𝘁 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝗰𝗲😍

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✅ OOP Interview Questions with Answers Part-5 🧠💻

41. What is multiple inheritance?
It means a class can inherit from more than one parent class.
✔ Supported in C++
✖ Not directly supported in Java (handled via interfaces)

42. What are mixins?
Mixins are a way to add reusable behavior to classes without using inheritance.
✔ Used in Python and JavaScript
✔ Promotes code reuse

43. What is the diamond problem in inheritance?
Occurs when two parent classes inherit from a common grandparent, and a child class inherits both.
❌ Creates ambiguity about which method to inherit.

44. How is the diamond problem solved in C++ or Java?
• C++: Uses virtual inheritance
• Java: Avoids it entirely using interfaces (no multiple class inheritance)

45. What are abstract data types in OOP?
ADTs define what operations can be done, not how.
Examples: Stack, Queue, List
✔ Implementation is hidden
✔ Promotes abstraction

46. What is a design pattern in OOP?
Reusable solution to a common software design problem.
✔ Templates for writing clean, maintainable code

47. What are some common OOP design patterns?
• Singleton – one instance
• Factory – object creation logic
• Observer – event-based updates
• Strategy – interchangeable behavior
• Adapter – interface compatibility

48. Interface vs Abstract Class (Real-world use)
• Interface – Contract; use when you want to define capability (e.g., Drivable)
• Abstract Class – Shared structure + behavior; base class for similar types (e.g., Vehicle)

49. What is garbage collection?
Automatic memory management – reclaims memory from unused objects.
✔ Java has a built-in GC
✔ Prevents memory leaks

50. Real-world use of OOP?
• Games – Objects for players, enemies
• Banking – Classes for accounts, transactions
• UI – Buttons, forms as objects
• E-commerce – Products, carts, users as objects

💬 Double Tap ❤️ For More!

📊 SQL Interview Queries – Intermediate Level

━━━━━━━━━━━━━━

❓ Query 01: Find employees earning more than the average salary

SELECT *
FROM employees
WHERE salary > (SELECT AVG(salary) FROM employees);

❓ Query 02: Find department-wise employee count

SELECT department, COUNT(*) AS emp_count
FROM employees
GROUP BY department;

❓ Query 03: Find departments with average salary greater than 60,000

SELECT department
FROM employees
GROUP BY department
HAVING AVG(salary) > 60000;

❓ Query 04: Fetch employees who do not belong to any department

SELECT e.*
FROM employees e
LEFT JOIN departments d
ON e.department_id = d.department_id
WHERE d.department_id IS NULL;

❓ Query 05: Find second highest salary

SELECT MAX(salary)
FROM employees
WHERE salary < (SELECT MAX(salary) FROM employees);

❓ Query 06: Get highest salary in each department

SELECT department, MAX(salary)
FROM employees
GROUP BY department;

❓ Query 07: Fetch employees hired in the last 6 months

SELECT *
FROM employees
WHERE hire_date >= DATE_SUB(CURDATE(), INTERVAL 6 MONTH);

❓ Query 08: Find duplicate email IDs

SELECT email, COUNT(*)
FROM employees
GROUP BY email
HAVING COUNT(*) > 1;

❓ Query 09: Rank employees by salary within each department

SELECT *,
RANK() OVER (PARTITION BY department ORDER BY salary DESC) AS rank
FROM employees;

❓ Query 10: Fetch top 2 highest paid employees from each department

SELECT *
FROM (
SELECT *,
DENSE_RANK() OVER (PARTITION BY department ORDER BY salary DESC) AS rnk
FROM employees
) t
WHERE rnk <= 2;

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