Here are 40 most asked DSA questions to ace your next interview -
๐๐๐ป๐ฎ๐บ๐ถ๐ฐ ๐ฃ๐ฟ๐ผ๐ด๐ฟ๐ฎ๐บ๐บ๐ถ๐ป๐ด (๐๐ฃ):
1. How do you find the nth Fibonacci number using dynamic programming?
2. Write a dynamic programming solution for the 0/1 knapsack problem.
3. Memoization to optimize recursive solutions in dynamic programming?
4. Implement a dynamic programming algorithm to find the longest common subsequence of two strings.
5. The coin change problem.
6. Tabulation approach in dynamic programming.
๐๐ฎ๐ฐ๐ธ๐๐ฟ๐ฎ๐ฐ๐ธ๐ถ๐ป๐ด:
7. Backtracking algorithm to solve the N-Queens problem.
8. Generate all permutations of a given set using backtracking?
9. Implement backtracking to solve the Sudoku puzzle.
10. Subset sum problem.
11. Graph coloring problem using backtracking.
12. Write a backtracking algorithm to find the Hamiltonian cycle in a graph.
๐๐ฎ๐๐ต๐ถ๐ป๐ด:
13. Implement a hash table using separate chaining.
14. First non-repeating character in a string using hashing.
15. Collision resolution techniques in hashing.
16. Write a function to solve the two-sum problem using hashing.
17. How can you implement a hash set data structure?
18. Count the frequency of elements in an array using hashing.
๐๐ฒ๐ฎ๐ฝ:
19. Implement a priority queue using a min-heap.
20. How do you merge K sorted arrays using a min-heap?
21. Write a function to perform heap sort algorithm.
22. Find the kth largest element in an array using a min-heap.
23. Implement a priority queue using a min-heap.
24. How do you build a max heap from an array?
๐ง๐ฟ๐ถ๐ฒ๐:
25. Implement a trie data structure.
26. Write a function to search for a word in a trie.
27. How can you implement autocomplete feature using a trie?
28. Deleting a word from a trie.
30. Write a function to find all words matching a pattern in a trie.
๐๐ฟ๐ฒ๐ฒ๐ฑ๐ ๐๐น๐ด๐ผ๐ฟ๐ถ๐๐ต๐บ๐:
31. Solve the activity selection problem using a greedy algorithm.
32. Implement Huffman coding using a greedy algorithm.
33. Write a function to find the minimum spanning tree using Prim's algorithm.
34. Coin change problem.
35. Dijkstra's algorithm using a greedy approach.
36. Implement the job sequencing problem using a greedy algorithm.
37. Stack Vs queue.
38. breadth-first search (BFS) and depth-first search (DFS) traversal
39. Concept of big O notation.
40. What is an AVL tree? Explain its properties and how it maintains balance during insertion and deletion operations.
React โค๏ธ for more
๐๐๐ป๐ฎ๐บ๐ถ๐ฐ ๐ฃ๐ฟ๐ผ๐ด๐ฟ๐ฎ๐บ๐บ๐ถ๐ป๐ด (๐๐ฃ):
1. How do you find the nth Fibonacci number using dynamic programming?
2. Write a dynamic programming solution for the 0/1 knapsack problem.
3. Memoization to optimize recursive solutions in dynamic programming?
4. Implement a dynamic programming algorithm to find the longest common subsequence of two strings.
5. The coin change problem.
6. Tabulation approach in dynamic programming.
๐๐ฎ๐ฐ๐ธ๐๐ฟ๐ฎ๐ฐ๐ธ๐ถ๐ป๐ด:
7. Backtracking algorithm to solve the N-Queens problem.
8. Generate all permutations of a given set using backtracking?
9. Implement backtracking to solve the Sudoku puzzle.
10. Subset sum problem.
11. Graph coloring problem using backtracking.
12. Write a backtracking algorithm to find the Hamiltonian cycle in a graph.
๐๐ฎ๐๐ต๐ถ๐ป๐ด:
13. Implement a hash table using separate chaining.
14. First non-repeating character in a string using hashing.
15. Collision resolution techniques in hashing.
16. Write a function to solve the two-sum problem using hashing.
17. How can you implement a hash set data structure?
18. Count the frequency of elements in an array using hashing.
๐๐ฒ๐ฎ๐ฝ:
19. Implement a priority queue using a min-heap.
20. How do you merge K sorted arrays using a min-heap?
21. Write a function to perform heap sort algorithm.
22. Find the kth largest element in an array using a min-heap.
23. Implement a priority queue using a min-heap.
24. How do you build a max heap from an array?
๐ง๐ฟ๐ถ๐ฒ๐:
25. Implement a trie data structure.
26. Write a function to search for a word in a trie.
27. How can you implement autocomplete feature using a trie?
28. Deleting a word from a trie.
30. Write a function to find all words matching a pattern in a trie.
๐๐ฟ๐ฒ๐ฒ๐ฑ๐ ๐๐น๐ด๐ผ๐ฟ๐ถ๐๐ต๐บ๐:
31. Solve the activity selection problem using a greedy algorithm.
32. Implement Huffman coding using a greedy algorithm.
33. Write a function to find the minimum spanning tree using Prim's algorithm.
34. Coin change problem.
35. Dijkstra's algorithm using a greedy approach.
36. Implement the job sequencing problem using a greedy algorithm.
37. Stack Vs queue.
38. breadth-first search (BFS) and depth-first search (DFS) traversal
39. Concept of big O notation.
40. What is an AVL tree? Explain its properties and how it maintains balance during insertion and deletion operations.
React โค๏ธ for more
โค6
You will not learn system design in a month.
You will not master DSA in a month.
You will not suddenly understand how to solve problems at scale in a month.
You wonโt grasp scalability, databases, and caching overnight.
And you most definitely wonโt internalize every distributed system pattern just by reading a few blogs.
Because software engineering is an ocean: deep, vast, and ever-expanding.
And you canโt cross an ocean in a single leap.
In a month, youโll realize youโre only scratching the surface.
Youโll see more gaps than answers.
Youโll feel like thereโs too much to learn and too little time.
But thatโs where most people give up.
Thatโs where frustration makes them quit.
Donโt be one of them.
Take it one step at a time.
Real expertise doesnโt come from rushing. It comes from consistent, deliberate learning over years.
It comes from revisiting the same concepts and seeing them from new perspectives each time.
So trust your own pace.
Stay in the game long enough to connect the dots.
And one day, the same concepts that once seemed impossible will feel like second nature.
Just keep collecting buckets.
You will not master DSA in a month.
You will not suddenly understand how to solve problems at scale in a month.
You wonโt grasp scalability, databases, and caching overnight.
And you most definitely wonโt internalize every distributed system pattern just by reading a few blogs.
Because software engineering is an ocean: deep, vast, and ever-expanding.
And you canโt cross an ocean in a single leap.
In a month, youโll realize youโre only scratching the surface.
Youโll see more gaps than answers.
Youโll feel like thereโs too much to learn and too little time.
But thatโs where most people give up.
Thatโs where frustration makes them quit.
Donโt be one of them.
Take it one step at a time.
Real expertise doesnโt come from rushing. It comes from consistent, deliberate learning over years.
It comes from revisiting the same concepts and seeing them from new perspectives each time.
So trust your own pace.
Stay in the game long enough to connect the dots.
And one day, the same concepts that once seemed impossible will feel like second nature.
Just keep collecting buckets.
โค4๐1
SQL Essentials for Quick Revision
๐ SELECT
Retrieve data from one or more tables.
๐ฏ WHERE Clause
Filter records based on specific conditions.
๐ ORDER BY
Sort query results in ascending (ASC) or descending (DESC) order.
๐ Aggregation Functions
MIN, MAX, AVG, COUNT: Summarize data.
Window Functions: Perform calculations across a dataset without grouping rows.
๐ GROUP BY
Group data based on one or more columns and apply aggregate functions.
๐ JOINS
INNER JOIN: Fetch matching rows from both tables.
LEFT JOIN: All rows from the left table and matching rows from the right.
RIGHT JOIN: All rows from the right table and matching rows from the left.
FULL JOIN: Combine rows when there is a match in either table.
SELF JOIN: Join a table with itself.
๐งฉ Common Table Expressions (CTE)
Simplify complex queries with temporary result sets.
Quick SQL Revision Notes ๐
Master these concepts for interviews and projects!
#SQL #DataAnalytics #QuickNotes
๐ SELECT
Retrieve data from one or more tables.
๐ฏ WHERE Clause
Filter records based on specific conditions.
๐ ORDER BY
Sort query results in ascending (ASC) or descending (DESC) order.
๐ Aggregation Functions
MIN, MAX, AVG, COUNT: Summarize data.
Window Functions: Perform calculations across a dataset without grouping rows.
๐ GROUP BY
Group data based on one or more columns and apply aggregate functions.
๐ JOINS
INNER JOIN: Fetch matching rows from both tables.
LEFT JOIN: All rows from the left table and matching rows from the right.
RIGHT JOIN: All rows from the right table and matching rows from the left.
FULL JOIN: Combine rows when there is a match in either table.
SELF JOIN: Join a table with itself.
๐งฉ Common Table Expressions (CTE)
Simplify complex queries with temporary result sets.
Quick SQL Revision Notes ๐
Master these concepts for interviews and projects!
#SQL #DataAnalytics #QuickNotes
โค2
Typical C++ interview questions sorted by experience
Junior:
- What are the key features of object-oriented programming in C++?
- Explain the differences between public, private, and protected access specifiers in C++.
- Distinguish between function overloading and overriding in C++.
- Compare and contrast abstract classes and interfaces in C++.
- Can an interface inherit from another interface in C++?
- Define the static keyword in C++ and its significance.
- Is it possible to override a static method in C++?
- Explain the concepts of polymorphism and inheritance in C++.
- Can constructors be inherited in C++?
- Discuss pass-by-reference and pass-by-value for objects in C++.
- Compare == and .equals for string comparison in C++.
- Explain the purposes of the hashCode() and equals() functions.
- What does the Serializable interface do? How is it related to Parcelable in Android?
- Differentiate between Array and ArrayList in C++. When would you use each?
- Explain the distinction between Integer and int in C++.
- Define ThreadPool and discuss its advantages over using simple threads.
- Differentiate between local, instance, and class variables in C++.
Mid:
- What is reflection in C++?
- Define dependency injection and name a few libraries. Have you used any?
- Explain strong, soft, and weak references in C++.
- Interpret the meaning of the synchronized keyword.
- Can memory leaks occur in C++?
- Is it necessary to set references to null in C++?
- Why is a String considered immutable?
- Discuss transient and volatile modifiers in C++.
- What is the purpose of the finalize() method?
- How does the try{} finally{} block work in C++?
- Explain the difference between object instantiation and initialization.
- Under what conditions is a static block executed in C++?
- Why are generics used in C++?
- Mention some design patterns you are familiar with. Which do you typically use?
- Name some types of testing methodologies in C++.
Senior:
- Explain how
- What is the "double-check locking" problem, and how can it be solved in C++?
- Differentiate between StringBuffer and StringBuilder in C++.
- How is StringBuilder implemented to avoid the immutable string allocation problem?
- Explain the purpose of the
- Define Autoboxing and Unboxing in C++.
- What's the difference between Enumeration and Iterator in C++?
- Explain the difference between fail-fast and fail-safe in C++.
- What is PermGen in C++?
- Describe a Java priority queue.
- How is performance influenced by using the same number in different types: Int, Double, and Float?
- Explain the concept of the Java Heap.
- What is a daemon thread?
- Can a dead thread be restarted in C++?
โ Best Telegram channels to get free coding & data science resources
-> https://t.me/addlist/4q2PYC0pH_VjZDk5
ENJOY LEARNING ๐๐
Junior:
- What are the key features of object-oriented programming in C++?
- Explain the differences between public, private, and protected access specifiers in C++.
- Distinguish between function overloading and overriding in C++.
- Compare and contrast abstract classes and interfaces in C++.
- Can an interface inherit from another interface in C++?
- Define the static keyword in C++ and its significance.
- Is it possible to override a static method in C++?
- Explain the concepts of polymorphism and inheritance in C++.
- Can constructors be inherited in C++?
- Discuss pass-by-reference and pass-by-value for objects in C++.
- Compare == and .equals for string comparison in C++.
- Explain the purposes of the hashCode() and equals() functions.
- What does the Serializable interface do? How is it related to Parcelable in Android?
- Differentiate between Array and ArrayList in C++. When would you use each?
- Explain the distinction between Integer and int in C++.
- Define ThreadPool and discuss its advantages over using simple threads.
- Differentiate between local, instance, and class variables in C++.
Mid:
- What is reflection in C++?
- Define dependency injection and name a few libraries. Have you used any?
- Explain strong, soft, and weak references in C++.
- Interpret the meaning of the synchronized keyword.
- Can memory leaks occur in C++?
- Is it necessary to set references to null in C++?
- Why is a String considered immutable?
- Discuss transient and volatile modifiers in C++.
- What is the purpose of the finalize() method?
- How does the try{} finally{} block work in C++?
- Explain the difference between object instantiation and initialization.
- Under what conditions is a static block executed in C++?
- Why are generics used in C++?
- Mention some design patterns you are familiar with. Which do you typically use?
- Name some types of testing methodologies in C++.
Senior:
- Explain how
std::stoi (string to integer) works in C++.- What is the "double-check locking" problem, and how can it be solved in C++?
- Differentiate between StringBuffer and StringBuilder in C++.
- How is StringBuilder implemented to avoid the immutable string allocation problem?
- Explain the purpose of the
Class.forName method in C++.- Define Autoboxing and Unboxing in C++.
- What's the difference between Enumeration and Iterator in C++?
- Explain the difference between fail-fast and fail-safe in C++.
- What is PermGen in C++?
- Describe a Java priority queue.
- How is performance influenced by using the same number in different types: Int, Double, and Float?
- Explain the concept of the Java Heap.
- What is a daemon thread?
- Can a dead thread be restarted in C++?
โ Best Telegram channels to get free coding & data science resources
-> https://t.me/addlist/4q2PYC0pH_VjZDk5
ENJOY LEARNING ๐๐
โค1
Learning CSS in 30 days๐
Day 1-5: Introduction to CSSโก
Learn the basics of HTML (if you don't know already)
Understand what CSS is and how it is used to style web pages
Learn how to add CSS to an HTML page
Understand the different ways to add CSS to an HTML page (inline, internal, external)
Learn about selectors and how they are used to target HTML elements
Day 6-10: Box model and layout๐
Understand the box model and how it affects the layout of HTML elements
Learn how to manipulate the box model using padding, margin, and border
Learn how to position elements using CSS (relative, absolute, fixed, static, sticky)
Understand the different display properties (block, inline, inline-block) and how they affect layout
Learn how to create responsive layouts using media queries
Day 11-15: Typography and colors โค๏ธโ๐ฅ
Understand the CSS font properties (font-family, font-size, font-weight, etc.)
Learn how to style text using CSS (color, text-decoration, text-align, etc.)
Understand the CSS color property and how to use it to set colors
Learn about gradients, transparency, and opacity
Understand how to use CSS to create hover and active effects
Day 16-20: Advanced CSS concepts๐ฉโ๐ป
Learn about CSS preprocessors like Sass and Less
Understand how to use CSS frameworks like Bootstrap and Foundation
Learn about CSS animations and transitions
Understand how to use flexbox for layout
Learn how to use CSS grid for layout
Day 21-25: CSS best practices and optimization๐ฅ
Learn about CSS code organization and best practices
Understand how to optimize CSS for performance
Learn how to use CSS vendor prefixes for cross-browser compatibility
Understand how to debug CSS using browser developer tools
Learn how to use CSS linting tools to catch errors
Day 26-30: Practice and projects๐ฉโ๐ซ
Create simple projects to practice what you've learned
Work on more complex projects to challenge yourself
Join CSS communities to learn from others and get feedback on your work
Read articles and tutorials to stay up-to-date with the latest CSS trends and techniques
Reflect on what you've learned and identify areas for improvement
Remember, this is just a roadmap, and you can adjust it based on your learning style and pace.
The most important thing is to stay consistent and practice regularly. Good luck!
Web Development Best Resources: https://topmate.io/coding/930165
ENJOY LEARNING ๐๐
Day 1-5: Introduction to CSSโก
Learn the basics of HTML (if you don't know already)
Understand what CSS is and how it is used to style web pages
Learn how to add CSS to an HTML page
Understand the different ways to add CSS to an HTML page (inline, internal, external)
Learn about selectors and how they are used to target HTML elements
Day 6-10: Box model and layout๐
Understand the box model and how it affects the layout of HTML elements
Learn how to manipulate the box model using padding, margin, and border
Learn how to position elements using CSS (relative, absolute, fixed, static, sticky)
Understand the different display properties (block, inline, inline-block) and how they affect layout
Learn how to create responsive layouts using media queries
Day 11-15: Typography and colors โค๏ธโ๐ฅ
Understand the CSS font properties (font-family, font-size, font-weight, etc.)
Learn how to style text using CSS (color, text-decoration, text-align, etc.)
Understand the CSS color property and how to use it to set colors
Learn about gradients, transparency, and opacity
Understand how to use CSS to create hover and active effects
Day 16-20: Advanced CSS concepts๐ฉโ๐ป
Learn about CSS preprocessors like Sass and Less
Understand how to use CSS frameworks like Bootstrap and Foundation
Learn about CSS animations and transitions
Understand how to use flexbox for layout
Learn how to use CSS grid for layout
Day 21-25: CSS best practices and optimization๐ฅ
Learn about CSS code organization and best practices
Understand how to optimize CSS for performance
Learn how to use CSS vendor prefixes for cross-browser compatibility
Understand how to debug CSS using browser developer tools
Learn how to use CSS linting tools to catch errors
Day 26-30: Practice and projects๐ฉโ๐ซ
Create simple projects to practice what you've learned
Work on more complex projects to challenge yourself
Join CSS communities to learn from others and get feedback on your work
Read articles and tutorials to stay up-to-date with the latest CSS trends and techniques
Reflect on what you've learned and identify areas for improvement
Remember, this is just a roadmap, and you can adjust it based on your learning style and pace.
The most important thing is to stay consistent and practice regularly. Good luck!
Web Development Best Resources: https://topmate.io/coding/930165
ENJOY LEARNING ๐๐
โค2
If you want to get a job as a machine learning engineer, donโt start by diving into the hottest libraries like PyTorch,TensorFlow, Langchain, etc.
Yes, you might hear a lot about them or some other trending technology of the year...but guess what!
Technologies evolve rapidly, especially in the age of AI, but core concepts are always seen as more valuable than expertise in any particular tool. Stop trying to perform a brain surgery without knowing anything about human anatomy.
Instead, here are basic skills that will get you further than mastering any framework:
๐๐๐ญ๐ก๐๐ฆ๐๐ญ๐ข๐๐ฌ ๐๐ง๐ ๐๐ญ๐๐ญ๐ข๐ฌ๐ญ๐ข๐๐ฌ - My first exposure to probability and statistics was in college, and it felt abstract at the time, but these concepts are the backbone of ML.
You can start here: Khan Academy Statistics and Probability - https://www.khanacademy.org/math/statistics-probability
๐๐ข๐ง๐๐๐ซ ๐๐ฅ๐ ๐๐๐ซ๐ ๐๐ง๐ ๐๐๐ฅ๐๐ฎ๐ฅ๐ฎ๐ฌ - Concepts like matrices, vectors, eigenvalues, and derivatives are fundamental to understanding how ml algorithms work. These are used in everything from simple regression to deep learning.
๐๐ซ๐จ๐ ๐ซ๐๐ฆ๐ฆ๐ข๐ง๐ - Should you learn Python, Rust, R, Julia, JavaScript, etc.? The best advice is to pick the language that is most frequently used for the type of work you want to do. I started with Python due to its simplicity and extensive library support, and it remains my go-to language for machine learning tasks.
You can start here: Automate the Boring Stuff with Python - https://automatetheboringstuff.com/
๐๐ฅ๐ ๐จ๐ซ๐ข๐ญ๐ก๐ฆ ๐๐ง๐๐๐ซ๐ฌ๐ญ๐๐ง๐๐ข๐ง๐ - Understand the fundamental algorithms before jumping to deep learning. This includes linear regression, decision trees, SVMs, and clustering algorithms.
๐๐๐ฉ๐ฅ๐จ๐ฒ๐ฆ๐๐ง๐ญ ๐๐ง๐ ๐๐ซ๐จ๐๐ฎ๐๐ญ๐ข๐จ๐ง:
Knowing how to take a model from development to production is invaluable. This includes understanding APIs, model optimization, and monitoring. Tools like Docker and Flask are often used in this process.
๐๐ฅ๐จ๐ฎ๐ ๐๐จ๐ฆ๐ฉ๐ฎ๐ญ๐ข๐ง๐ ๐๐ง๐ ๐๐ข๐ ๐๐๐ญ๐:
Familiarity with cloud platforms (AWS, Google Cloud, Azure) and big data tools (Spark) is increasingly important as datasets grow larger. These skills help you manage and process large-scale data efficiently.
You can start here: Google Cloud Machine Learning - https://cloud.google.com/learn/training/machinelearning-ai
I love frameworks and libraries, and they can make anyone's job easier.
But the more solid your foundation, the easier it will be to pick up any new technologies and actually validate whether they solve your problems.
Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624
All the best ๐๐
Yes, you might hear a lot about them or some other trending technology of the year...but guess what!
Technologies evolve rapidly, especially in the age of AI, but core concepts are always seen as more valuable than expertise in any particular tool. Stop trying to perform a brain surgery without knowing anything about human anatomy.
Instead, here are basic skills that will get you further than mastering any framework:
๐๐๐ญ๐ก๐๐ฆ๐๐ญ๐ข๐๐ฌ ๐๐ง๐ ๐๐ญ๐๐ญ๐ข๐ฌ๐ญ๐ข๐๐ฌ - My first exposure to probability and statistics was in college, and it felt abstract at the time, but these concepts are the backbone of ML.
You can start here: Khan Academy Statistics and Probability - https://www.khanacademy.org/math/statistics-probability
๐๐ข๐ง๐๐๐ซ ๐๐ฅ๐ ๐๐๐ซ๐ ๐๐ง๐ ๐๐๐ฅ๐๐ฎ๐ฅ๐ฎ๐ฌ - Concepts like matrices, vectors, eigenvalues, and derivatives are fundamental to understanding how ml algorithms work. These are used in everything from simple regression to deep learning.
๐๐ซ๐จ๐ ๐ซ๐๐ฆ๐ฆ๐ข๐ง๐ - Should you learn Python, Rust, R, Julia, JavaScript, etc.? The best advice is to pick the language that is most frequently used for the type of work you want to do. I started with Python due to its simplicity and extensive library support, and it remains my go-to language for machine learning tasks.
You can start here: Automate the Boring Stuff with Python - https://automatetheboringstuff.com/
๐๐ฅ๐ ๐จ๐ซ๐ข๐ญ๐ก๐ฆ ๐๐ง๐๐๐ซ๐ฌ๐ญ๐๐ง๐๐ข๐ง๐ - Understand the fundamental algorithms before jumping to deep learning. This includes linear regression, decision trees, SVMs, and clustering algorithms.
๐๐๐ฉ๐ฅ๐จ๐ฒ๐ฆ๐๐ง๐ญ ๐๐ง๐ ๐๐ซ๐จ๐๐ฎ๐๐ญ๐ข๐จ๐ง:
Knowing how to take a model from development to production is invaluable. This includes understanding APIs, model optimization, and monitoring. Tools like Docker and Flask are often used in this process.
๐๐ฅ๐จ๐ฎ๐ ๐๐จ๐ฆ๐ฉ๐ฎ๐ญ๐ข๐ง๐ ๐๐ง๐ ๐๐ข๐ ๐๐๐ญ๐:
Familiarity with cloud platforms (AWS, Google Cloud, Azure) and big data tools (Spark) is increasingly important as datasets grow larger. These skills help you manage and process large-scale data efficiently.
You can start here: Google Cloud Machine Learning - https://cloud.google.com/learn/training/machinelearning-ai
I love frameworks and libraries, and they can make anyone's job easier.
But the more solid your foundation, the easier it will be to pick up any new technologies and actually validate whether they solve your problems.
Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624
All the best ๐๐
โค3
List of topics you need to cover if you're preparing for Java Interviews based on current Job market:
1. Core Java Fundamentals (Refer to already posted topics)
2. Advanced Java
- Design Patterns
- Multithreading
- Java Memory Model
- Performance Optimization
- Reflection & Dynamic Proxies
3. Spring Framework
- Spring core concepts
- Spring boot
- Spring Data JPA
- Spring Security
- Spring cloud
- Spring webflux
4. Hibernate
5. Testing (JUnit, Mockito, Integration, Functional, Performance Testing)
6. Build Tools (Maven / Gradle)
7. Logging
8. RDBMS, NoSQL DBs
9. WebSecurity Concepts
10. REST API concepts
11. CI/CD (Jenkins, GitHub Actions)
12. Containerization (Docker, Kubernetes)
13. Version Control (GitHub)
14. Monitoring (Grafana, ELK Stack etc)
15. Cloud (AWS, Azure, GCP (Very rare) )
16. Spring boot microservices
16. Messaging systems
17. Caching Strategies
18. System Design
19. Data Structures
20. Algorithms
21. Agile Methodologies
22. Behavioral questions
1. Core Java Fundamentals (Refer to already posted topics)
2. Advanced Java
- Design Patterns
- Multithreading
- Java Memory Model
- Performance Optimization
- Reflection & Dynamic Proxies
3. Spring Framework
- Spring core concepts
- Spring boot
- Spring Data JPA
- Spring Security
- Spring cloud
- Spring webflux
4. Hibernate
5. Testing (JUnit, Mockito, Integration, Functional, Performance Testing)
6. Build Tools (Maven / Gradle)
7. Logging
8. RDBMS, NoSQL DBs
9. WebSecurity Concepts
10. REST API concepts
11. CI/CD (Jenkins, GitHub Actions)
12. Containerization (Docker, Kubernetes)
13. Version Control (GitHub)
14. Monitoring (Grafana, ELK Stack etc)
15. Cloud (AWS, Azure, GCP (Very rare) )
16. Spring boot microservices
16. Messaging systems
17. Caching Strategies
18. System Design
19. Data Structures
20. Algorithms
21. Agile Methodologies
22. Behavioral questions
โค3
๐ Web development project ideas for beginners
Personal Portfolio Website: Create a website showcasing your skills, projects, and resume. This will help you practice HTML, CSS, and potentially some JavaScript for interactivity.
To-Do List App: Build a simple to-do list application using HTML, CSS, and JavaScript. You can gradually enhance it by adding features like task priority, due dates, and local storage.
Blog Platform: Create a basic blog platform where users can create, edit, and delete posts. This will give you experience with user authentication, databases, and CRUD operations.
E-commerce Website: Design a mock e-commerce site to learn about product listings, shopping carts, and checkout processes. This project will introduce you to handling user input and creating dynamic content.
Weather App: Develop a weather app that fetches data from a weather API and displays current conditions and forecasts. This project will involve API integration and working with JSON data.
Recipe Sharing Site: Build a platform where users can share and browse recipes. You can implement search functionality and user authentication to enhance the project.
Social Media Dashboard: Create a simplified social media dashboard that displays metrics like followers, likes, and comments. This project will help you practice data visualization and working with APIs.
Online Quiz App: Develop an online quiz application that lets users take quizzes on various topics. You can include features like multiple-choice questions, timers, and score tracking.
Personal Blog: Start your own blog by developing a content management system (CMS) where you can create, edit, and publish articles. This will give you hands-on experience with database management.
Event Countdown Timer: Build a countdown timer for upcoming events. You can make it interactive by allowing users to set their own event names and dates.
Remember, the key is to start small and gradually add complexity to your projects as you become more comfortable with different technologies concepts. These projects will not only showcase your skills to potential employers but also help you learn and grow as a web developer.
Free Resources to learn web development https://t.me/free4unow_backup/554
ENJOY LEARNING ๐๐
Personal Portfolio Website: Create a website showcasing your skills, projects, and resume. This will help you practice HTML, CSS, and potentially some JavaScript for interactivity.
To-Do List App: Build a simple to-do list application using HTML, CSS, and JavaScript. You can gradually enhance it by adding features like task priority, due dates, and local storage.
Blog Platform: Create a basic blog platform where users can create, edit, and delete posts. This will give you experience with user authentication, databases, and CRUD operations.
E-commerce Website: Design a mock e-commerce site to learn about product listings, shopping carts, and checkout processes. This project will introduce you to handling user input and creating dynamic content.
Weather App: Develop a weather app that fetches data from a weather API and displays current conditions and forecasts. This project will involve API integration and working with JSON data.
Recipe Sharing Site: Build a platform where users can share and browse recipes. You can implement search functionality and user authentication to enhance the project.
Social Media Dashboard: Create a simplified social media dashboard that displays metrics like followers, likes, and comments. This project will help you practice data visualization and working with APIs.
Online Quiz App: Develop an online quiz application that lets users take quizzes on various topics. You can include features like multiple-choice questions, timers, and score tracking.
Personal Blog: Start your own blog by developing a content management system (CMS) where you can create, edit, and publish articles. This will give you hands-on experience with database management.
Event Countdown Timer: Build a countdown timer for upcoming events. You can make it interactive by allowing users to set their own event names and dates.
Remember, the key is to start small and gradually add complexity to your projects as you become more comfortable with different technologies concepts. These projects will not only showcase your skills to potential employers but also help you learn and grow as a web developer.
Free Resources to learn web development https://t.me/free4unow_backup/554
ENJOY LEARNING ๐๐
โค4
Top 10 Web Development Technologies ๐
1. ๐จ JavaScript โ 98% usage
2. ๐ต TypeScript โ 78% adoption
3. ๐ข Node.js โ 75% backend choice
4. โ๏ธ React โ 70% frontend framework
5. ๐ ฐ๏ธ Angular โ 55% enterprise use
6. ๐ Vue.js โ 49% growing popularity
7. ๐ Python โ 48% for full-stack
8. ๐ Ruby on Rails โ 45% rapid development
9. ๐ PHP โ 43% widespread use
10. โ Java โ 40% enterprise solutions
1. ๐จ JavaScript โ 98% usage
2. ๐ต TypeScript โ 78% adoption
3. ๐ข Node.js โ 75% backend choice
4. โ๏ธ React โ 70% frontend framework
5. ๐ ฐ๏ธ Angular โ 55% enterprise use
6. ๐ Vue.js โ 49% growing popularity
7. ๐ Python โ 48% for full-stack
8. ๐ Ruby on Rails โ 45% rapid development
9. ๐ PHP โ 43% widespread use
10. โ Java โ 40% enterprise solutions
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11. ๐ฆ Rust โ 38% performance-critical apps
12. ๐ฏ Dart โ 35% with Flutter for web
13. ๐ท GraphQL โ 33% API queries
14. ๐ MongoDB โ 30% NoSQL database
15. ๐ณ Docker โ 28% containerization
16. โ๏ธ AWS โ 25% cloud services
17. ๐ถ Svelte โ 22% compile-time framework
18. ๐ท Next.js โ 20% React framework
19. ๐ฃ Blazor โ 18% .NET web apps
20. ๐ข Deno โ 15% secure runtime
12. ๐ฏ Dart โ 35% with Flutter for web
13. ๐ท GraphQL โ 33% API queries
14. ๐ MongoDB โ 30% NoSQL database
15. ๐ณ Docker โ 28% containerization
16. โ๏ธ AWS โ 25% cloud services
17. ๐ถ Svelte โ 22% compile-time framework
18. ๐ท Next.js โ 20% React framework
19. ๐ฃ Blazor โ 18% .NET web apps
20. ๐ข Deno โ 15% secure runtime
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Interview QnAs For ML Engineer
1.What are the various steps involved in an data analytics project?
The steps involved in a data analytics project are:
Data collection
Data cleansing
Data pre-processing
EDA
Creation of train test and validation sets
Model creation
Hyperparameter tuning
Model deployment
2. Explain Star Schema.
Star schema is a data warehousing concept in which all schema is connected to a central schema.
3. What is root cause analysis?
Root cause analysis is the process of tracing back of occurrence of an event and the factors which lead to it. Itโs generally done when a software malfunctions. In data science, root cause analysis helps businesses understand the semantics behind certain outcomes.
4. Define Confounding Variables.
A confounding variable is an external influence in an experiment. In simple words, these variables change the effect of a dependent and independent variable. A variable should satisfy below conditions to be a confounding variable :
Variables should be correlated to the independent variable.
Variables should be informally related to the dependent variable.
For example, if you are studying whether a lack of exercise has an effect on weight gain, then the lack of exercise is an independent variable and weight gain is a dependent variable. A confounder variable can be any other factor that has an effect on weight gain. Amount of food consumed, weather conditions etc. can be a confounding variable.
Data Science & Machine Learning Resources: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D
ENJOY LEARNING ๐๐
1.What are the various steps involved in an data analytics project?
The steps involved in a data analytics project are:
Data collection
Data cleansing
Data pre-processing
EDA
Creation of train test and validation sets
Model creation
Hyperparameter tuning
Model deployment
2. Explain Star Schema.
Star schema is a data warehousing concept in which all schema is connected to a central schema.
3. What is root cause analysis?
Root cause analysis is the process of tracing back of occurrence of an event and the factors which lead to it. Itโs generally done when a software malfunctions. In data science, root cause analysis helps businesses understand the semantics behind certain outcomes.
4. Define Confounding Variables.
A confounding variable is an external influence in an experiment. In simple words, these variables change the effect of a dependent and independent variable. A variable should satisfy below conditions to be a confounding variable :
Variables should be correlated to the independent variable.
Variables should be informally related to the dependent variable.
For example, if you are studying whether a lack of exercise has an effect on weight gain, then the lack of exercise is an independent variable and weight gain is a dependent variable. A confounder variable can be any other factor that has an effect on weight gain. Amount of food consumed, weather conditions etc. can be a confounding variable.
Data Science & Machine Learning Resources: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D
ENJOY LEARNING ๐๐
โค4
How to master Python from scratch๐
1. Setup and Basics ๐
- Install Python ๐ฅ๏ธ: Download Python and set it up.
- Hello, World! ๐: Write your first Hello World program.
2. Basic Syntax ๐
- Variables and Data Types ๐: Learn about strings, integers, floats, and booleans.
- Control Structures ๐: Understand if-else statements, for loops, and while loops.
- Functions ๐ ๏ธ: Write reusable blocks of code.
3. Data Structures ๐
- Lists ๐: Manage collections of items.
- Dictionaries ๐: Store key-value pairs.
- Tuples ๐ฆ: Work with immutable sequences.
- Sets ๐ข: Handle collections of unique items.
4. Modules and Packages ๐ฆ
- Standard Library ๐: Explore built-in modules.
- Third-Party Packages ๐: Install and use packages with pip.
5. File Handling ๐
- Read and Write Files ๐
- CSV and JSON ๐
6. Object-Oriented Programming ๐งฉ
- Classes and Objects ๐๏ธ
- Inheritance and Polymorphism ๐จโ๐ฉโ๐ง
7. Web Development ๐
- Flask ๐ผ: Start with a micro web framework.
- Django ๐ฆ: Dive into a full-fledged web framework.
8. Data Science and Machine Learning ๐ง
- NumPy ๐: Numerical operations.
- Pandas ๐ผ: Data manipulation and analysis.
- Matplotlib ๐ and Seaborn ๐: Data visualization.
- Scikit-learn ๐ค: Machine learning.
9. Automation and Scripting ๐ค
- Automate Tasks ๐ ๏ธ: Use Python to automate repetitive tasks.
- APIs ๐: Interact with web services.
10. Testing and Debugging ๐
- Unit Testing ๐งช: Write tests for your code.
- Debugging ๐: Learn to debug efficiently.
11. Advanced Topics ๐
- Concurrency and Parallelism ๐
- Decorators ๐ and Generators โ๏ธ
- Web Scraping ๐ธ๏ธ: Extract data from websites using BeautifulSoup and Scrapy.
12. Practice Projects ๐ก
- Calculator ๐งฎ
- To-Do List App ๐
- Weather App โ๏ธ
- Personal Blog ๐
13. Community and Collaboration ๐ค
- Contribute to Open Source ๐
- Join Coding Communities ๐ฌ
- Participate in Hackathons ๐
14. Keep Learning and Improving ๐
- Read Books ๐: Like "Automate the Boring Stuff with Python".
- Watch Tutorials ๐ฅ: Follow video courses and tutorials.
- Solve Challenges ๐งฉ: On platforms like LeetCode, HackerRank, and CodeWars.
15. Teach and Share Knowledge ๐ข
- Write Blogs โ๏ธ
- Create Video Tutorials ๐น
- Mentor Others ๐จโ๐ซ
I have curated the best interview resources to crack Python Interviews ๐๐
https://topmate.io/coding/898340
Hope you'll like it
Like this post if you need more resources like this ๐โค๏ธ
1. Setup and Basics ๐
- Install Python ๐ฅ๏ธ: Download Python and set it up.
- Hello, World! ๐: Write your first Hello World program.
2. Basic Syntax ๐
- Variables and Data Types ๐: Learn about strings, integers, floats, and booleans.
- Control Structures ๐: Understand if-else statements, for loops, and while loops.
- Functions ๐ ๏ธ: Write reusable blocks of code.
3. Data Structures ๐
- Lists ๐: Manage collections of items.
- Dictionaries ๐: Store key-value pairs.
- Tuples ๐ฆ: Work with immutable sequences.
- Sets ๐ข: Handle collections of unique items.
4. Modules and Packages ๐ฆ
- Standard Library ๐: Explore built-in modules.
- Third-Party Packages ๐: Install and use packages with pip.
5. File Handling ๐
- Read and Write Files ๐
- CSV and JSON ๐
6. Object-Oriented Programming ๐งฉ
- Classes and Objects ๐๏ธ
- Inheritance and Polymorphism ๐จโ๐ฉโ๐ง
7. Web Development ๐
- Flask ๐ผ: Start with a micro web framework.
- Django ๐ฆ: Dive into a full-fledged web framework.
8. Data Science and Machine Learning ๐ง
- NumPy ๐: Numerical operations.
- Pandas ๐ผ: Data manipulation and analysis.
- Matplotlib ๐ and Seaborn ๐: Data visualization.
- Scikit-learn ๐ค: Machine learning.
9. Automation and Scripting ๐ค
- Automate Tasks ๐ ๏ธ: Use Python to automate repetitive tasks.
- APIs ๐: Interact with web services.
10. Testing and Debugging ๐
- Unit Testing ๐งช: Write tests for your code.
- Debugging ๐: Learn to debug efficiently.
11. Advanced Topics ๐
- Concurrency and Parallelism ๐
- Decorators ๐ and Generators โ๏ธ
- Web Scraping ๐ธ๏ธ: Extract data from websites using BeautifulSoup and Scrapy.
12. Practice Projects ๐ก
- Calculator ๐งฎ
- To-Do List App ๐
- Weather App โ๏ธ
- Personal Blog ๐
13. Community and Collaboration ๐ค
- Contribute to Open Source ๐
- Join Coding Communities ๐ฌ
- Participate in Hackathons ๐
14. Keep Learning and Improving ๐
- Read Books ๐: Like "Automate the Boring Stuff with Python".
- Watch Tutorials ๐ฅ: Follow video courses and tutorials.
- Solve Challenges ๐งฉ: On platforms like LeetCode, HackerRank, and CodeWars.
15. Teach and Share Knowledge ๐ข
- Write Blogs โ๏ธ
- Create Video Tutorials ๐น
- Mentor Others ๐จโ๐ซ
I have curated the best interview resources to crack Python Interviews ๐๐
https://topmate.io/coding/898340
Hope you'll like it
Like this post if you need more resources like this ๐โค๏ธ
โค2