Coding is tricky. Coding in interviews feels even harder. Itโs intimidating, uncertain and hard to prepare. Here are 4 ways to do it!
1. Interview Cake: I think it is some of the best prep available and it is targeted toward weaknesses many data scientists have in algorithms and data structures: https://www.interviewcake.com/
2. Leetcode: While developed for software engineering interviews, it has a LOT of useful content for learning algorithms. For data science, I'd suggest focusing on Easy/Medium: https://leetcode.com/
3. Cracking the Coding Interview: Amazing book, sometimes referred to as CTCI. A classic and one you should have: https://cin.ufpe.br/~fbma/Crack/Cracking%20the%20Coding%20Interview%20189%20Programming%20Questions%20and%20Solutions.pdf
4. Daily Coding Problem: The book and the website are awesome. Work on a daily problem. This was my go to resource for when I was looking to stay sharp: https://www.dailycodingproblem.com/
#coding
1. Interview Cake: I think it is some of the best prep available and it is targeted toward weaknesses many data scientists have in algorithms and data structures: https://www.interviewcake.com/
2. Leetcode: While developed for software engineering interviews, it has a LOT of useful content for learning algorithms. For data science, I'd suggest focusing on Easy/Medium: https://leetcode.com/
3. Cracking the Coding Interview: Amazing book, sometimes referred to as CTCI. A classic and one you should have: https://cin.ufpe.br/~fbma/Crack/Cracking%20the%20Coding%20Interview%20189%20Programming%20Questions%20and%20Solutions.pdf
4. Daily Coding Problem: The book and the website are awesome. Work on a daily problem. This was my go to resource for when I was looking to stay sharp: https://www.dailycodingproblem.com/
#coding
๐6
Master DSA in 160 days
๐๐
https://gfgcdn.com/tu/TX9/
This is a very good course by Geekforgeeks, designed for freshers to help them crack coding interviews.
The best part about such courses is it helps you build consistency and disciplineโtwo key habits that not only make DSA easier but also set you up for long-term success in your career.
Like if you need similar FREE resources in the channel
ENJOY LEARNING ๐๐
๐๐
https://gfgcdn.com/tu/TX9/
This is a very good course by Geekforgeeks, designed for freshers to help them crack coding interviews.
The best part about such courses is it helps you build consistency and disciplineโtwo key habits that not only make DSA easier but also set you up for long-term success in your career.
Like if you need similar FREE resources in the channel
ENJOY LEARNING ๐๐
๐6โค5
10 Ways to Speed Up Your Python Code
1. List Comprehensions
numbers = [x**2 for x in range(100000) if x % 2 == 0]
instead of
numbers = []
for x in range(100000):
if x % 2 == 0:
numbers.append(x**2)
2. Use the Built-In Functions
Many of Pythonโs built-in functions are written in C, which makes them much faster than a pure python solution.
3. Function Calls Are Expensive
Function calls are expensive in Python. While it is often good practice to separate code into functions, there are times where you should be cautious about calling functions from inside of a loop. It is better to iterate inside a function than to iterate and call a function each iteration.
4. Lazy Module Importing
If you want to use the time.sleep() function in your code, you don't necessarily need to import the entire time package. Instead, you can just do from time import sleep and avoid the overhead of loading basically everything.
5. Take Advantage of Numpy
Numpy is a highly optimized library built with C. It is almost always faster to offload complex math to Numpy rather than relying on the Python interpreter.
6. Try Multiprocessing
Multiprocessing can bring large performance increases to a Python script, but it can be difficult to implement properly compared to other methods mentioned in this post.
7. Be Careful with Bulky Libraries
One of the advantages Python has over other programming languages is the rich selection of third-party libraries available to developers. But, what we may not always consider is the size of the library we are using as a dependency, which could actually decrease the performance of your Python code.
8. Avoid Global Variables
Python is slightly faster at retrieving local variables than global ones. It is simply best to avoid global variables when possible.
9. Try Multiple Solutions
Being able to solve a problem in multiple ways is nice. But, there is often a solution that is faster than the rest and sometimes it comes down to just using a different method or data structure.
10. Think About Your Data Structures
Searching a dictionary or set is insanely fast, but lists take time proportional to the length of the list. However, sets and dictionaries do not maintain order. If you care about the order of your data, you canโt make use of dictionaries or sets.
1. List Comprehensions
numbers = [x**2 for x in range(100000) if x % 2 == 0]
instead of
numbers = []
for x in range(100000):
if x % 2 == 0:
numbers.append(x**2)
2. Use the Built-In Functions
Many of Pythonโs built-in functions are written in C, which makes them much faster than a pure python solution.
3. Function Calls Are Expensive
Function calls are expensive in Python. While it is often good practice to separate code into functions, there are times where you should be cautious about calling functions from inside of a loop. It is better to iterate inside a function than to iterate and call a function each iteration.
4. Lazy Module Importing
If you want to use the time.sleep() function in your code, you don't necessarily need to import the entire time package. Instead, you can just do from time import sleep and avoid the overhead of loading basically everything.
5. Take Advantage of Numpy
Numpy is a highly optimized library built with C. It is almost always faster to offload complex math to Numpy rather than relying on the Python interpreter.
6. Try Multiprocessing
Multiprocessing can bring large performance increases to a Python script, but it can be difficult to implement properly compared to other methods mentioned in this post.
7. Be Careful with Bulky Libraries
One of the advantages Python has over other programming languages is the rich selection of third-party libraries available to developers. But, what we may not always consider is the size of the library we are using as a dependency, which could actually decrease the performance of your Python code.
8. Avoid Global Variables
Python is slightly faster at retrieving local variables than global ones. It is simply best to avoid global variables when possible.
9. Try Multiple Solutions
Being able to solve a problem in multiple ways is nice. But, there is often a solution that is faster than the rest and sometimes it comes down to just using a different method or data structure.
10. Think About Your Data Structures
Searching a dictionary or set is insanely fast, but lists take time proportional to the length of the list. However, sets and dictionaries do not maintain order. If you care about the order of your data, you canโt make use of dictionaries or sets.
๐4โค1
Tips for Google Interview Preparation
Understand the work culture at Google well - It is always good to understand how the company works and what are the things that are expected out of an employee at Google. This shows that you are really interested in working at Google and leaves a good impression on the interviewer as well.
Be Thorough with Data Structures and Algorithms - At Google, there is always an appreciation for good problem solvers. If you want to have a good impression on the interviewers, the best way is to prove that you have worked a lot on developing your logic structures and solving algorithmic problems. A good understanding of Data Structures and Algorithms and having one or two good projects always earn you brownie points with Amazon.
Use the STAR method to format your Response - STAR is an acronym for Situation, Task, Action, and Result. The STAR method is a structured way to respond to behavioral based interview questions. To answer a provided question using the STAR method, you start by describing the situation that was at hand, the Task which needed to be done, the action taken by you as a response to the Task, and finally the Result of the experience. It is important to think about all the details and recall everyone and everything that was involved in the situation. Let the interviewer know how much of an impact that experience had on your life and in the lives of all others who were involved. It is always a good practice to be prepared with a real-life story that you can describe using the STAR method.
Know and Describe your Strengths - Many people who interview at various companies, stay shy during the interviews and feel uncomfortable when they are asked to describe their strengths. Remember that if you do not show how good you are at the skills you know, no one will ever be able to know about the same and this might just cost you a lot. So it is okay to think about yourself and highlight your strengths properly and honestly as and when required.
Discuss with your interviewer and keep the conversation going - Remember that an interview is not a written exam and therefore even if you come up with the best of solutions for the given problems, it is not worth anything until and unless the interviewer understands what you are trying to say. Therefore, it is important to make the interviewer that he or she is also a part of the interview. Also, asking questions might always prove to be helpful during the interview.
Best DSA RESOURCES: https://topmate.io/coding/886874
All the best ๐๐
Understand the work culture at Google well - It is always good to understand how the company works and what are the things that are expected out of an employee at Google. This shows that you are really interested in working at Google and leaves a good impression on the interviewer as well.
Be Thorough with Data Structures and Algorithms - At Google, there is always an appreciation for good problem solvers. If you want to have a good impression on the interviewers, the best way is to prove that you have worked a lot on developing your logic structures and solving algorithmic problems. A good understanding of Data Structures and Algorithms and having one or two good projects always earn you brownie points with Amazon.
Use the STAR method to format your Response - STAR is an acronym for Situation, Task, Action, and Result. The STAR method is a structured way to respond to behavioral based interview questions. To answer a provided question using the STAR method, you start by describing the situation that was at hand, the Task which needed to be done, the action taken by you as a response to the Task, and finally the Result of the experience. It is important to think about all the details and recall everyone and everything that was involved in the situation. Let the interviewer know how much of an impact that experience had on your life and in the lives of all others who were involved. It is always a good practice to be prepared with a real-life story that you can describe using the STAR method.
Know and Describe your Strengths - Many people who interview at various companies, stay shy during the interviews and feel uncomfortable when they are asked to describe their strengths. Remember that if you do not show how good you are at the skills you know, no one will ever be able to know about the same and this might just cost you a lot. So it is okay to think about yourself and highlight your strengths properly and honestly as and when required.
Discuss with your interviewer and keep the conversation going - Remember that an interview is not a written exam and therefore even if you come up with the best of solutions for the given problems, it is not worth anything until and unless the interviewer understands what you are trying to say. Therefore, it is important to make the interviewer that he or she is also a part of the interview. Also, asking questions might always prove to be helpful during the interview.
Best DSA RESOURCES: https://topmate.io/coding/886874
All the best ๐๐
๐8โค1
Type of problem, while solving DSA problem in Array
โ There are many types of problems that can be solved using arrays and different techniques in Data Structures and Algorithms. Here are some common problem types and techniques that you might encounter:
๐. ๐๐ฅ๐ข๐๐ข๐ง๐ ๐ฐ๐ข๐ง๐๐จ๐ฐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are given an array and a window size, and you have to find a subarray of that size that satisfies certain conditions. You can use a sliding window technique to efficiently search through the array by maintaining a current window of fixed size and updating it as you move forward.
๐. ๐๐ฐ๐จ ๐ฉ๐จ๐ข๐ง๐ญ๐๐ซ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you use two pointers to traverse the array from both ends and find a certain pattern or condition. For example, you can use two pointers to find a pair of elements that sum up to a target value, or to reverse an array.
๐. ๐๐จ๐ซ๐ญ๐ข๐ง๐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to sort an array in a certain way, such as in ascending or descending order, or according to certain criteria such as frequency or value. You can use sorting algorithms such as merge sort or quick sort to efficiently sort the array.
๐. ๐๐๐๐ซ๐๐ก๐ข๐ง๐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to find a specific element in the array or to search for a certain pattern. You can use searching algorithms such as binary search or linear search to efficiently search through the array.
๐. ๐๐ฎ๐๐๐ซ๐ซ๐๐ฒ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to find a contiguous subarray that satisfies certain conditions. You can use techniques such as prefix sum or Kadane's algorithm to efficiently find the subarray with the maximum sum.
๐. ๐๐จ๐ฎ๐ง๐ญ๐ข๐ง๐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to count the occurrences of certain elements or to count the number of subarrays or subsequences that satisfy certain conditions. You can use techniques such as hashing or dynamic programming to efficiently count the occurrences or number of subarrays.
Best DSA RESOURCES: https://topmate.io/coding/886874
All the best ๐๐
โ There are many types of problems that can be solved using arrays and different techniques in Data Structures and Algorithms. Here are some common problem types and techniques that you might encounter:
๐. ๐๐ฅ๐ข๐๐ข๐ง๐ ๐ฐ๐ข๐ง๐๐จ๐ฐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are given an array and a window size, and you have to find a subarray of that size that satisfies certain conditions. You can use a sliding window technique to efficiently search through the array by maintaining a current window of fixed size and updating it as you move forward.
๐. ๐๐ฐ๐จ ๐ฉ๐จ๐ข๐ง๐ญ๐๐ซ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you use two pointers to traverse the array from both ends and find a certain pattern or condition. For example, you can use two pointers to find a pair of elements that sum up to a target value, or to reverse an array.
๐. ๐๐จ๐ซ๐ญ๐ข๐ง๐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to sort an array in a certain way, such as in ascending or descending order, or according to certain criteria such as frequency or value. You can use sorting algorithms such as merge sort or quick sort to efficiently sort the array.
๐. ๐๐๐๐ซ๐๐ก๐ข๐ง๐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to find a specific element in the array or to search for a certain pattern. You can use searching algorithms such as binary search or linear search to efficiently search through the array.
๐. ๐๐ฎ๐๐๐ซ๐ซ๐๐ฒ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to find a contiguous subarray that satisfies certain conditions. You can use techniques such as prefix sum or Kadane's algorithm to efficiently find the subarray with the maximum sum.
๐. ๐๐จ๐ฎ๐ง๐ญ๐ข๐ง๐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to count the occurrences of certain elements or to count the number of subarrays or subsequences that satisfy certain conditions. You can use techniques such as hashing or dynamic programming to efficiently count the occurrences or number of subarrays.
Best DSA RESOURCES: https://topmate.io/coding/886874
All the best ๐๐
๐5โค1
Here is how you can explain your project in an interview
When youโre in an interview, itโs super important to know how to talk about your projects in a way that impresses the interviewer. Here are some key points to help you do just that:
โค ๐ฃ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐ ๐ข๐๐ฒ๐ฟ๐๐ถ๐ฒ๐:
- Start with a quick summary of the project you worked on. What was it all about? What were the main goals? Keep it short and sweet something you can explain in about 30 seconds.
โค ๐ฃ๐ฟ๐ผ๐ฏ๐น๐ฒ๐บ ๐ฆ๐๐ฎ๐๐ฒ๐บ๐ฒ๐ป๐:
- What problem were you trying to solve with this project? Explain why this problem was important and needed addressing.
โค ๐ฃ๐ฟ๐ผ๐ฝ๐ผ๐๐ฒ๐ฑ ๐ฆ๐ผ๐น๐๐๐ถ๐ผ๐ป:
- Describe the solution you came up with. How does it work, and why is it a good fix for the problem?
โค ๐ฌ๐ผ๐๐ฟ ๐ฅ๐ผ๐น๐ฒ:
- Talk about what you specifically did. What were your main tasks? Did you face any challenges, and how did you overcome them? Make sure itโs clear whether you were leading the project, a key player, or supporting the team.
โค ๐ง๐ฒ๐ฐ๐ต๐ป๐ผ๐น๐ผ๐ด๐ถ๐ฒ๐ ๐ฎ๐ป๐ฑ ๐ง๐ผ๐ผ๐น๐:
- Mention the tech and tools you used. This shows your technical know-how and your ability to choose the right tools for the job.
โค ๐๐บ๐ฝ๐ฎ๐ฐ๐ ๐ฎ๐ป๐ฑ ๐๐ฐ๐ต๐ถ๐ฒ๐๐ฒ๐บ๐ฒ๐ป๐๐:
- Share the results of your project. Did it make things better? How? Mention any improvements, efficiencies, or positive feedback you got. This helps show the project was a success and highlights your contribution.
โค ๐ง๐ฒ๐ฎ๐บ ๐๐ผ๐น๐น๐ฎ๐ฏ๐ผ๐ฟ๐ฎ๐๐ถ๐ผ๐ป:
- If you worked with a team, talk about how you collaborated. What was your role in the team? How did you communicate and contribute to the teamโs success?
โค ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐ฎ๐ป๐ฑ ๐๐ฒ๐๐ฒ๐น๐ผ๐ฝ๐บ๐ฒ๐ป๐:
- Reflect on what you learned from the project. How did it help you grow professionally? What new skills did you gain, and what would you do differently next time?
โค ๐ง๐ถ๐ฝ๐ ๐ณ๐ผ๐ฟ ๐ฌ๐ผ๐๐ฟ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐ฃ๐ฟ๐ฒ๐ฝ๐ฎ๐ฟ๐ฎ๐๐ถ๐ผ๐ป:
- Be ready with a 30 second elevator pitch about your projects, and also have a five-minute detailed overview ready.
- Know why you chose the project, what your role was, what decisions you made, and how the results compared to what you expected.
- Be clear on the scope of the project whether it was a long-term effort or a quick task.
- If thereโs a pause after you describe the project, donโt hesitate to ask if theyโd like more details or if thereโs a specific part theyโre interested in.
You can check these resources for Coding interview Preparation
Like for more ๐๐
When youโre in an interview, itโs super important to know how to talk about your projects in a way that impresses the interviewer. Here are some key points to help you do just that:
โค ๐ฃ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐ ๐ข๐๐ฒ๐ฟ๐๐ถ๐ฒ๐:
- Start with a quick summary of the project you worked on. What was it all about? What were the main goals? Keep it short and sweet something you can explain in about 30 seconds.
โค ๐ฃ๐ฟ๐ผ๐ฏ๐น๐ฒ๐บ ๐ฆ๐๐ฎ๐๐ฒ๐บ๐ฒ๐ป๐:
- What problem were you trying to solve with this project? Explain why this problem was important and needed addressing.
โค ๐ฃ๐ฟ๐ผ๐ฝ๐ผ๐๐ฒ๐ฑ ๐ฆ๐ผ๐น๐๐๐ถ๐ผ๐ป:
- Describe the solution you came up with. How does it work, and why is it a good fix for the problem?
โค ๐ฌ๐ผ๐๐ฟ ๐ฅ๐ผ๐น๐ฒ:
- Talk about what you specifically did. What were your main tasks? Did you face any challenges, and how did you overcome them? Make sure itโs clear whether you were leading the project, a key player, or supporting the team.
โค ๐ง๐ฒ๐ฐ๐ต๐ป๐ผ๐น๐ผ๐ด๐ถ๐ฒ๐ ๐ฎ๐ป๐ฑ ๐ง๐ผ๐ผ๐น๐:
- Mention the tech and tools you used. This shows your technical know-how and your ability to choose the right tools for the job.
โค ๐๐บ๐ฝ๐ฎ๐ฐ๐ ๐ฎ๐ป๐ฑ ๐๐ฐ๐ต๐ถ๐ฒ๐๐ฒ๐บ๐ฒ๐ป๐๐:
- Share the results of your project. Did it make things better? How? Mention any improvements, efficiencies, or positive feedback you got. This helps show the project was a success and highlights your contribution.
โค ๐ง๐ฒ๐ฎ๐บ ๐๐ผ๐น๐น๐ฎ๐ฏ๐ผ๐ฟ๐ฎ๐๐ถ๐ผ๐ป:
- If you worked with a team, talk about how you collaborated. What was your role in the team? How did you communicate and contribute to the teamโs success?
โค ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐ฎ๐ป๐ฑ ๐๐ฒ๐๐ฒ๐น๐ผ๐ฝ๐บ๐ฒ๐ป๐:
- Reflect on what you learned from the project. How did it help you grow professionally? What new skills did you gain, and what would you do differently next time?
โค ๐ง๐ถ๐ฝ๐ ๐ณ๐ผ๐ฟ ๐ฌ๐ผ๐๐ฟ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐ฃ๐ฟ๐ฒ๐ฝ๐ฎ๐ฟ๐ฎ๐๐ถ๐ผ๐ป:
- Be ready with a 30 second elevator pitch about your projects, and also have a five-minute detailed overview ready.
- Know why you chose the project, what your role was, what decisions you made, and how the results compared to what you expected.
- Be clear on the scope of the project whether it was a long-term effort or a quick task.
- If thereโs a pause after you describe the project, donโt hesitate to ask if theyโd like more details or if thereโs a specific part theyโre interested in.
You can check these resources for Coding interview Preparation
Like for more ๐๐
๐9โค1
Important topics of Object Oriented Programming System
1. Classes and Objects:
-> Basics of defining classes and creating objects.
-> Class members: attributes (properties) and methods (functions).
2. Inheritance:
-> Creating a new class by inheriting properties and methods from an existing class.
-> Superclasses (base classes) and subclasses (derived classes).
3. Polymorphism:
-> Ability to take multiple forms.
-> Method overriding and method overloading.
4. Encapsulation:
-> Hiding the internal details of a class and providing a controlled interface.
-> Access modifiers: public, private, protected.
5. Abstraction:
-> Simplifying complex reality by modeling classes based on real-world entities.
-> Abstract classes and interfaces.
6. Constructors and Destructors:
-> Special methods for initializing and cleaning up objects.
-> Constructor overloading.
7. Method Access and Modifiers:
-> Public, private, protected, and package-private access modifiers.
-> Static methods and variables.
A few advanced topics :-
Composition and Aggregation:
Combining objects to create more complex structures.
Has-a and Is-a relationships.
Object Relationships:
Association, aggregation, and composition.
One-to-one, one-to-many, and many-to-many relationships.
Interfaces:
Defining contracts that classes must adhere to.
Multiple interface implementation.
Polymorphic Behavior:
Achieving flexibility through polymorphism.
Method overriding and dynamic method binding.
Inheritance vs. Composition:
Comparing and choosing between inheritance and object composition.
Design Patterns:
Common solutions to recurring design problems.
Examples: Singleton, Factory, Observer, etc.
Exception Handling:
Handling errors and exceptions gracefully in OOP.
Try-catch blocks.
Object Serialization:
Converting objects into a format suitable for storage or transmission.
Reading and writing objects to/from files.
Garbage Collection:
Automatic memory management to reclaim unused memory.
Mark and sweep, reference counting, and generations.
UML (Unified Modeling Language):
A visual language for modeling software systems.
Class diagrams, sequence diagrams, and use cases.
Method Overriding vs. Method Overloading:
Understanding the differences between these two concepts.
Abstract Classes vs. Interfaces:
Comparing and contrasting abstract classes and interfaces in OOP.
Encapsulation Benefits:
Discussing the advantages of encapsulation, such as data protection and code organization.
P.S - These are just the name of topics which you should be aware of. You can get enough articles on every topic just on a Google search.
Best DSA RESOURCES: https://topmate.io/coding/886874
All the best ๐๐
1. Classes and Objects:
-> Basics of defining classes and creating objects.
-> Class members: attributes (properties) and methods (functions).
2. Inheritance:
-> Creating a new class by inheriting properties and methods from an existing class.
-> Superclasses (base classes) and subclasses (derived classes).
3. Polymorphism:
-> Ability to take multiple forms.
-> Method overriding and method overloading.
4. Encapsulation:
-> Hiding the internal details of a class and providing a controlled interface.
-> Access modifiers: public, private, protected.
5. Abstraction:
-> Simplifying complex reality by modeling classes based on real-world entities.
-> Abstract classes and interfaces.
6. Constructors and Destructors:
-> Special methods for initializing and cleaning up objects.
-> Constructor overloading.
7. Method Access and Modifiers:
-> Public, private, protected, and package-private access modifiers.
-> Static methods and variables.
A few advanced topics :-
Composition and Aggregation:
Combining objects to create more complex structures.
Has-a and Is-a relationships.
Object Relationships:
Association, aggregation, and composition.
One-to-one, one-to-many, and many-to-many relationships.
Interfaces:
Defining contracts that classes must adhere to.
Multiple interface implementation.
Polymorphic Behavior:
Achieving flexibility through polymorphism.
Method overriding and dynamic method binding.
Inheritance vs. Composition:
Comparing and choosing between inheritance and object composition.
Design Patterns:
Common solutions to recurring design problems.
Examples: Singleton, Factory, Observer, etc.
Exception Handling:
Handling errors and exceptions gracefully in OOP.
Try-catch blocks.
Object Serialization:
Converting objects into a format suitable for storage or transmission.
Reading and writing objects to/from files.
Garbage Collection:
Automatic memory management to reclaim unused memory.
Mark and sweep, reference counting, and generations.
UML (Unified Modeling Language):
A visual language for modeling software systems.
Class diagrams, sequence diagrams, and use cases.
Method Overriding vs. Method Overloading:
Understanding the differences between these two concepts.
Abstract Classes vs. Interfaces:
Comparing and contrasting abstract classes and interfaces in OOP.
Encapsulation Benefits:
Discussing the advantages of encapsulation, such as data protection and code organization.
P.S - These are just the name of topics which you should be aware of. You can get enough articles on every topic just on a Google search.
Best DSA RESOURCES: https://topmate.io/coding/886874
All the best ๐๐
โค2๐2
Hey Everyone! ๐
Don't miss out on this exciting opportunity! ๐
๐ ๐ ๐๐๐ ๐๐ง๐ฅ๐ข๐ง๐ ๐๐๐ฌ๐ญ๐๐ซ๐๐ฅ๐๐ฌ๐ฌ ๐จ๐ง ๐๐๐ญ๐ ๐๐๐ข๐๐ง๐๐ ๐
Learn Top Career Opportunities In The Data Science Industry
Become a Successful Data Scientist In Top MNCs
Eligibility:- Students ,Freshers & Working Professionals
๐ Date & Time:- November 23, 2024, at 7 PM
๐๏ธ ๐๐๐ ๐ข๐ฌ๐ญ๐๐ซ ๐๐จ๐ฐ ๐๐จ๐ซ ๐ ๐๐๐๐:
https://bit.ly/494sqkp
โก Limited slots availableโdonโt wait! ๐โโ๏ธ
Don't miss out on this exciting opportunity! ๐
๐ ๐ ๐๐๐ ๐๐ง๐ฅ๐ข๐ง๐ ๐๐๐ฌ๐ญ๐๐ซ๐๐ฅ๐๐ฌ๐ฌ ๐จ๐ง ๐๐๐ญ๐ ๐๐๐ข๐๐ง๐๐ ๐
Learn Top Career Opportunities In The Data Science Industry
Become a Successful Data Scientist In Top MNCs
Eligibility:- Students ,Freshers & Working Professionals
๐ Date & Time:- November 23, 2024, at 7 PM
๐๏ธ ๐๐๐ ๐ข๐ฌ๐ญ๐๐ซ ๐๐จ๐ฐ ๐๐จ๐ซ ๐ ๐๐๐๐:
https://bit.ly/494sqkp
โก Limited slots availableโdonโt wait! ๐โโ๏ธ
๐3
Junior Developer:
- I will never learn if I rely on Chatgpt. Maybe I can try writing this code on my own?
Mid Level Developer
- I'll only turn to chatGPT when I'm really stuck
Senior Developer
- How many R's are in the word strawberry?
- I will never learn if I rely on Chatgpt. Maybe I can try writing this code on my own?
Mid Level Developer
- I'll only turn to chatGPT when I'm really stuck
Senior Developer
- How many R's are in the word strawberry?
๐14
Here is how you can explain your project in an interview
When youโre in an interview, itโs super important to know how to talk about your projects in a way that impresses the interviewer. Here are some key points to help you do just that:
โค ๐ฃ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐ ๐ข๐๐ฒ๐ฟ๐๐ถ๐ฒ๐:
- Start with a quick summary of the project you worked on. What was it all about? What were the main goals? Keep it short and sweet something you can explain in about 30 seconds.
โค ๐ฃ๐ฟ๐ผ๐ฏ๐น๐ฒ๐บ ๐ฆ๐๐ฎ๐๐ฒ๐บ๐ฒ๐ป๐:
- What problem were you trying to solve with this project? Explain why this problem was important and needed addressing.
โค ๐ฃ๐ฟ๐ผ๐ฝ๐ผ๐๐ฒ๐ฑ ๐ฆ๐ผ๐น๐๐๐ถ๐ผ๐ป:
- Describe the solution you came up with. How does it work, and why is it a good fix for the problem?
โค ๐ฌ๐ผ๐๐ฟ ๐ฅ๐ผ๐น๐ฒ:
- Talk about what you specifically did. What were your main tasks? Did you face any challenges, and how did you overcome them? Make sure itโs clear whether you were leading the project, a key player, or supporting the team.
โค ๐ง๐ฒ๐ฐ๐ต๐ป๐ผ๐น๐ผ๐ด๐ถ๐ฒ๐ ๐ฎ๐ป๐ฑ ๐ง๐ผ๐ผ๐น๐:
- Mention the tech and tools you used. This shows your technical know-how and your ability to choose the right tools for the job.
โค ๐๐บ๐ฝ๐ฎ๐ฐ๐ ๐ฎ๐ป๐ฑ ๐๐ฐ๐ต๐ถ๐ฒ๐๐ฒ๐บ๐ฒ๐ป๐๐:
- Share the results of your project. Did it make things better? How? Mention any improvements, efficiencies, or positive feedback you got. This helps show the project was a success and highlights your contribution.
โค ๐ง๐ฒ๐ฎ๐บ ๐๐ผ๐น๐น๐ฎ๐ฏ๐ผ๐ฟ๐ฎ๐๐ถ๐ผ๐ป:
- If you worked with a team, talk about how you collaborated. What was your role in the team? How did you communicate and contribute to the teamโs success?
โค ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐ฎ๐ป๐ฑ ๐๐ฒ๐๐ฒ๐น๐ผ๐ฝ๐บ๐ฒ๐ป๐:
- Reflect on what you learned from the project. How did it help you grow professionally? What new skills did you gain, and what would you do differently next time?
โค ๐ง๐ถ๐ฝ๐ ๐ณ๐ผ๐ฟ ๐ฌ๐ผ๐๐ฟ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐ฃ๐ฟ๐ฒ๐ฝ๐ฎ๐ฟ๐ฎ๐๐ถ๐ผ๐ป:
- Be ready with a 30 second elevator pitch about your projects, and also have a five-minute detailed overview ready.
- Know why you chose the project, what your role was, what decisions you made, and how the results compared to what you expected.
- Be clear on the scope of the project whether it was a long-term effort or a quick task.
- If thereโs a pause after you describe the project, donโt hesitate to ask if theyโd like more details or if thereโs a specific part theyโre interested in.
Remember, ๐ฐ๐ผ๐บ๐บ๐๐ป๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐ถ๐ ๐ธ๐ฒ๐. You might have done great work, but if you donโt explain it well, itโs hard for the interviewer to understand your impact. So, practice explaining your projects with clarity.
When youโre in an interview, itโs super important to know how to talk about your projects in a way that impresses the interviewer. Here are some key points to help you do just that:
โค ๐ฃ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐ ๐ข๐๐ฒ๐ฟ๐๐ถ๐ฒ๐:
- Start with a quick summary of the project you worked on. What was it all about? What were the main goals? Keep it short and sweet something you can explain in about 30 seconds.
โค ๐ฃ๐ฟ๐ผ๐ฏ๐น๐ฒ๐บ ๐ฆ๐๐ฎ๐๐ฒ๐บ๐ฒ๐ป๐:
- What problem were you trying to solve with this project? Explain why this problem was important and needed addressing.
โค ๐ฃ๐ฟ๐ผ๐ฝ๐ผ๐๐ฒ๐ฑ ๐ฆ๐ผ๐น๐๐๐ถ๐ผ๐ป:
- Describe the solution you came up with. How does it work, and why is it a good fix for the problem?
โค ๐ฌ๐ผ๐๐ฟ ๐ฅ๐ผ๐น๐ฒ:
- Talk about what you specifically did. What were your main tasks? Did you face any challenges, and how did you overcome them? Make sure itโs clear whether you were leading the project, a key player, or supporting the team.
โค ๐ง๐ฒ๐ฐ๐ต๐ป๐ผ๐น๐ผ๐ด๐ถ๐ฒ๐ ๐ฎ๐ป๐ฑ ๐ง๐ผ๐ผ๐น๐:
- Mention the tech and tools you used. This shows your technical know-how and your ability to choose the right tools for the job.
โค ๐๐บ๐ฝ๐ฎ๐ฐ๐ ๐ฎ๐ป๐ฑ ๐๐ฐ๐ต๐ถ๐ฒ๐๐ฒ๐บ๐ฒ๐ป๐๐:
- Share the results of your project. Did it make things better? How? Mention any improvements, efficiencies, or positive feedback you got. This helps show the project was a success and highlights your contribution.
โค ๐ง๐ฒ๐ฎ๐บ ๐๐ผ๐น๐น๐ฎ๐ฏ๐ผ๐ฟ๐ฎ๐๐ถ๐ผ๐ป:
- If you worked with a team, talk about how you collaborated. What was your role in the team? How did you communicate and contribute to the teamโs success?
โค ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐ฎ๐ป๐ฑ ๐๐ฒ๐๐ฒ๐น๐ผ๐ฝ๐บ๐ฒ๐ป๐:
- Reflect on what you learned from the project. How did it help you grow professionally? What new skills did you gain, and what would you do differently next time?
โค ๐ง๐ถ๐ฝ๐ ๐ณ๐ผ๐ฟ ๐ฌ๐ผ๐๐ฟ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐ฃ๐ฟ๐ฒ๐ฝ๐ฎ๐ฟ๐ฎ๐๐ถ๐ผ๐ป:
- Be ready with a 30 second elevator pitch about your projects, and also have a five-minute detailed overview ready.
- Know why you chose the project, what your role was, what decisions you made, and how the results compared to what you expected.
- Be clear on the scope of the project whether it was a long-term effort or a quick task.
- If thereโs a pause after you describe the project, donโt hesitate to ask if theyโd like more details or if thereโs a specific part theyโre interested in.
Remember, ๐ฐ๐ผ๐บ๐บ๐๐ป๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐ถ๐ ๐ธ๐ฒ๐. You might have done great work, but if you donโt explain it well, itโs hard for the interviewer to understand your impact. So, practice explaining your projects with clarity.
๐12โค3๐1
๐๐ข๐ฉ๐ซ๐จ ๐๐ฎ๐ฅ๐ค ๐๐ข๐ซ๐ข๐ง๐ | ๐๐๐+ ๐๐ฉ๐๐ง๐ข๐ง๐ ๐ฌ๐
Role :- Data Analyst
Job Location:- Bangalore/Hyderabad
๐๐ฉ๐ฉ๐ฅ๐ฒ ๐๐ข๐ง๐ค๐ฌ :-
For 0 To 2 Years๐ :-
https://bit.ly/4ijUTqS
For 2 To 10 Years ๐:-
https://bit.ly/4gbrVYw
Apply Before The Link Expires
Role :- Data Analyst
Job Location:- Bangalore/Hyderabad
๐๐ฉ๐ฉ๐ฅ๐ฒ ๐๐ข๐ง๐ค๐ฌ :-
For 0 To 2 Years๐ :-
https://bit.ly/4ijUTqS
For 2 To 10 Years ๐:-
https://bit.ly/4gbrVYw
Apply Before The Link Expires
โค1
Leetcode patterns you should definitely checkout to Learn DSA(Java) from scratch
1๏ธโฃ Arrays: Data structures, such as arrays, store elements in contiguous memory locations. They are versatile and useful for a wide variety of purposes.
LeetCode Problems:
โข Search in Rotated Sorted Array (Problem #33)
โข Product of Array Except Self (Problem #238)
โข Find the Missing Number (Problem #268)
2๏ธโฃTwo Pointers: In Two Pointers, two pointers are maintained in the collection and can be manipulated to solve a problem efficiently.
LeetCode problems:
โข Trapping Rain Water (Problem #42)
โข Longest Substring Without Repeating Characters (Problem #3)
โข Squares of a Sorted Array (Problem #977)
3๏ธโฃIn-place Linked List Traversal: As an explanation, in-place traversal is a technique for modifying linked list nodes without using extra space.
LeetCode Problems:
โข Remove Nth Node From End of List (Problem #19)
โข Reorder List (Problem #143)
4๏ธโฃFast & Slow Pointers: This pattern uses two pointers to traverse a sequence at different speeds (fast and slow), often used to detect cycles or find a specific position in the sequence.
LeetCode Problems:
โข Happy Number (Problem #202)
โข Subarray Sum Equals K (Problem #560)
โข Intersection of Two Linked Lists (Problem #160)
5๏ธโฃMerge Intervals: This pattern involves merging overlapping intervals in a collection, often used in problems dealing with intervals or ranges.
LeetCode problems:
โข Non-overlapping Intervals (Problem #435)
โข Minimum Number of Arrows to Burst Balloons (Problem #452)
Join for more: https://t.me/crackingthecodinginterview
DSA Interview Preparation Resources: https://topmate.io/coding/886874
ENJOY LEARNING ๐๐
1๏ธโฃ Arrays: Data structures, such as arrays, store elements in contiguous memory locations. They are versatile and useful for a wide variety of purposes.
LeetCode Problems:
โข Search in Rotated Sorted Array (Problem #33)
โข Product of Array Except Self (Problem #238)
โข Find the Missing Number (Problem #268)
2๏ธโฃTwo Pointers: In Two Pointers, two pointers are maintained in the collection and can be manipulated to solve a problem efficiently.
LeetCode problems:
โข Trapping Rain Water (Problem #42)
โข Longest Substring Without Repeating Characters (Problem #3)
โข Squares of a Sorted Array (Problem #977)
3๏ธโฃIn-place Linked List Traversal: As an explanation, in-place traversal is a technique for modifying linked list nodes without using extra space.
LeetCode Problems:
โข Remove Nth Node From End of List (Problem #19)
โข Reorder List (Problem #143)
4๏ธโฃFast & Slow Pointers: This pattern uses two pointers to traverse a sequence at different speeds (fast and slow), often used to detect cycles or find a specific position in the sequence.
LeetCode Problems:
โข Happy Number (Problem #202)
โข Subarray Sum Equals K (Problem #560)
โข Intersection of Two Linked Lists (Problem #160)
5๏ธโฃMerge Intervals: This pattern involves merging overlapping intervals in a collection, often used in problems dealing with intervals or ranges.
LeetCode problems:
โข Non-overlapping Intervals (Problem #435)
โข Minimum Number of Arrows to Burst Balloons (Problem #452)
Join for more: https://t.me/crackingthecodinginterview
DSA Interview Preparation Resources: https://topmate.io/coding/886874
ENJOY LEARNING ๐๐
๐4
Tips for Google Interview Preparation
Now that we know all about the hiring process of Google, here are a few tips which you can use to crack Googleโs interview and get a job.
Understand the work culture at Google well - It is always good to understand how the company works and what are the things that are expected out of an employee at Google. This shows that you are really interested in working at Google and leaves a good impression on the interviewer as well.
Be Thorough with Data Structures and Algorithms - At Google, there is always an appreciation for good problem solvers. If you want to have a good impression on the interviewers, the best way is to prove that you have worked a lot on developing your logic structures and solving algorithmic problems. A good understanding of Data Structures and Algorithms and having one or two good projects always earn you brownie points with Amazon.
Use the STAR method to format your Response - STAR is an acronym for Situation, Task, Action, and Result. The STAR method is a structured way to respond to behavioral based interview questions. To answer a provided question using the STAR method, you start by describing the situation that was at hand, the Task which needed to be done, the action taken by you as a response to the Task, and finally the Result of the experience. It is important to think about all the details and recall everyone and everything that was involved in the situation. Let the interviewer know how much of an impact that experience had on your life and in the lives of all others who were involved. It is always a good practice to be prepared with a real-life story that you can describe using the STAR method.
Know and Describe your Strengths - Many people who interview at various companies, stay shy during the interviews and feel uncomfortable when they are asked to describe their strengths. Remember that if you do not show how good you are at the skills you know, no one will ever be able to know about the same and this might just cost you a lot. So it is okay to think about yourself and highlight your strengths properly and honestly as and when required.
Discuss with your interviewer and keep the conversation going - Remember that an interview is not a written exam and therefore even if you come up with the best of solutions for the given problems, it is not worth anything until and unless the interviewer understands what you are trying to say. Therefore, it is important to make the interviewer that he or she is also a part of the interview. Also, asking questions might always prove to be helpful during the interview.
Now that we know all about the hiring process of Google, here are a few tips which you can use to crack Googleโs interview and get a job.
Understand the work culture at Google well - It is always good to understand how the company works and what are the things that are expected out of an employee at Google. This shows that you are really interested in working at Google and leaves a good impression on the interviewer as well.
Be Thorough with Data Structures and Algorithms - At Google, there is always an appreciation for good problem solvers. If you want to have a good impression on the interviewers, the best way is to prove that you have worked a lot on developing your logic structures and solving algorithmic problems. A good understanding of Data Structures and Algorithms and having one or two good projects always earn you brownie points with Amazon.
Use the STAR method to format your Response - STAR is an acronym for Situation, Task, Action, and Result. The STAR method is a structured way to respond to behavioral based interview questions. To answer a provided question using the STAR method, you start by describing the situation that was at hand, the Task which needed to be done, the action taken by you as a response to the Task, and finally the Result of the experience. It is important to think about all the details and recall everyone and everything that was involved in the situation. Let the interviewer know how much of an impact that experience had on your life and in the lives of all others who were involved. It is always a good practice to be prepared with a real-life story that you can describe using the STAR method.
Know and Describe your Strengths - Many people who interview at various companies, stay shy during the interviews and feel uncomfortable when they are asked to describe their strengths. Remember that if you do not show how good you are at the skills you know, no one will ever be able to know about the same and this might just cost you a lot. So it is okay to think about yourself and highlight your strengths properly and honestly as and when required.
Discuss with your interviewer and keep the conversation going - Remember that an interview is not a written exam and therefore even if you come up with the best of solutions for the given problems, it is not worth anything until and unless the interviewer understands what you are trying to say. Therefore, it is important to make the interviewer that he or she is also a part of the interview. Also, asking questions might always prove to be helpful during the interview.
๐4
DSA INTERVIEW QUESTIONS AND ANSWERS
1. What is the difference between file structure and storage structure?
The difference lies in the memory area accessed. Storage structure refers to the data structure in the memory of the computer system,
whereas file structure represents the storage structure in the auxiliary memory.
2. Are linked lists considered linear or non-linear Data Structures?
Linked lists are considered both linear and non-linear data structures depending upon the application they are used for. When used for
access strategies, it is considered as a linear data-structure. When used for data storage, it is considered a non-linear data structure.
3. How do you reference all of the elements in a one-dimension array?
All of the elements in a one-dimension array can be referenced using an indexed loop as the array subscript so that the counter runs
from 0 to the array size minus one.
4. What are dynamic Data Structures? Name a few.
They are collections of data in memory that expand and contract to grow or shrink in size as a program runs. This enables the programmer
to control exactly how much memory is to be utilized.Examples are the dynamic array, linked list, stack, queue, and heap.
5. What is a Dequeue?
It is a double-ended queue, or a data structure, where the elements can be inserted or deleted at both ends (FRONT and REAR).
6. What operations can be performed on queues?
enqueue() adds an element to the end of the queue
dequeue() removes an element from the front of the queue
init() is used for initializing the queue
isEmpty tests for whether or not the queue is empty
The front is used to get the value of the first data item but does not remove it
The rear is used to get the last item from a queue.
7. What is the merge sort? How does it work?
Merge sort is a divide-and-conquer algorithm for sorting the data. It works by merging and sorting adjacent data to create bigger sorted
lists, which are then merged recursively to form even bigger sorted lists until you have one single sorted list.
8.How does the Selection sort work?
Selection sort works by repeatedly picking the smallest number in ascending order from the list and placing it at the beginning. This process is repeated moving toward the end of the list or sorted subarray.
Scan all items and find the smallest. Switch over the position as the first item. Repeat the selection sort on the remaining N-1 items. We always iterate forward (i from 0 to N-1) and swap with the smallest element (always i).
Time complexity: best case O(n2); worst O(n2)
Space complexity: worst O(1)
9. What are the applications of graph Data Structure?
Transport grids where stations are represented as vertices and routes as the edges of the graph
Utility graphs of power or water, where vertices are connection points and edge the wires or pipes connecting them
Social network graphs to determine the flow of information and hotspots (edges and vertices)
Neural networks where vertices represent neurons and edge the synapses between them
10. What is an AVL tree?
An AVL (Adelson, Velskii, and Landi) tree is a height balancing binary search tree in which the difference of heights of the left
and right subtrees of any node is less than or equal to one. This controls the height of the binary search tree by not letting
it get skewed. This is used when working with a large data set, with continual pruning through insertion and deletion of data.
11. Differentiate NULL and VOID ?
Null is a value, whereas Void is a data type identifier
Null indicates an empty value for a variable, whereas void indicates pointers that have no initial size
Null means it never existed; Void means it existed but is not in effect
You can check these resources for Coding interview Preparation
Credits: https://t.me/free4unow_backup
All the best ๐๐
1. What is the difference between file structure and storage structure?
The difference lies in the memory area accessed. Storage structure refers to the data structure in the memory of the computer system,
whereas file structure represents the storage structure in the auxiliary memory.
2. Are linked lists considered linear or non-linear Data Structures?
Linked lists are considered both linear and non-linear data structures depending upon the application they are used for. When used for
access strategies, it is considered as a linear data-structure. When used for data storage, it is considered a non-linear data structure.
3. How do you reference all of the elements in a one-dimension array?
All of the elements in a one-dimension array can be referenced using an indexed loop as the array subscript so that the counter runs
from 0 to the array size minus one.
4. What are dynamic Data Structures? Name a few.
They are collections of data in memory that expand and contract to grow or shrink in size as a program runs. This enables the programmer
to control exactly how much memory is to be utilized.Examples are the dynamic array, linked list, stack, queue, and heap.
5. What is a Dequeue?
It is a double-ended queue, or a data structure, where the elements can be inserted or deleted at both ends (FRONT and REAR).
6. What operations can be performed on queues?
enqueue() adds an element to the end of the queue
dequeue() removes an element from the front of the queue
init() is used for initializing the queue
isEmpty tests for whether or not the queue is empty
The front is used to get the value of the first data item but does not remove it
The rear is used to get the last item from a queue.
7. What is the merge sort? How does it work?
Merge sort is a divide-and-conquer algorithm for sorting the data. It works by merging and sorting adjacent data to create bigger sorted
lists, which are then merged recursively to form even bigger sorted lists until you have one single sorted list.
8.How does the Selection sort work?
Selection sort works by repeatedly picking the smallest number in ascending order from the list and placing it at the beginning. This process is repeated moving toward the end of the list or sorted subarray.
Scan all items and find the smallest. Switch over the position as the first item. Repeat the selection sort on the remaining N-1 items. We always iterate forward (i from 0 to N-1) and swap with the smallest element (always i).
Time complexity: best case O(n2); worst O(n2)
Space complexity: worst O(1)
9. What are the applications of graph Data Structure?
Transport grids where stations are represented as vertices and routes as the edges of the graph
Utility graphs of power or water, where vertices are connection points and edge the wires or pipes connecting them
Social network graphs to determine the flow of information and hotspots (edges and vertices)
Neural networks where vertices represent neurons and edge the synapses between them
10. What is an AVL tree?
An AVL (Adelson, Velskii, and Landi) tree is a height balancing binary search tree in which the difference of heights of the left
and right subtrees of any node is less than or equal to one. This controls the height of the binary search tree by not letting
it get skewed. This is used when working with a large data set, with continual pruning through insertion and deletion of data.
11. Differentiate NULL and VOID ?
Null is a value, whereas Void is a data type identifier
Null indicates an empty value for a variable, whereas void indicates pointers that have no initial size
Null means it never existed; Void means it existed but is not in effect
You can check these resources for Coding interview Preparation
Credits: https://t.me/free4unow_backup
All the best ๐๐
๐7
Object-Oriented Design (OOD) Interview
Interview-ready:
Tools and courses to help you prepare for OOD interviews.
Educative:
Interactive learning paths for mastering design patterns and OOD principles.
Codemia io
They have recently added OOAD sections with many questions like parking lot design, vending machine design and much more.
Head First Design Patterns Book:
An engaging book that simplifies complex design patterns with practical examples.
Interview-ready:
Tools and courses to help you prepare for OOD interviews.
Educative:
Interactive learning paths for mastering design patterns and OOD principles.
Codemia io
They have recently added OOAD sections with many questions like parking lot design, vending machine design and much more.
Head First Design Patterns Book:
An engaging book that simplifies complex design patterns with practical examples.
๐7
โ
Learn Trending Skills in 2025 ๐ฐ
1. Web Development โ
โ๏ธ https://t.me/webdevcoursefree
2. CSS โ
โ๏ธ http://css-tricks.com
3. JavaScript โ
โ๏ธ http://t.me/javascript_courses
4. React โ
โ๏ธ http://react-tutorial.app
5. Tailwind CSS โ
โ๏ธ http://scrimba.com
6. Data Science โ
โ๏ธ https://t.me/datasciencefun
7. Python โ
โ๏ธ http://pythontutorial.net
8. SQL โ
โ๏ธ https://t.me/sqlanalyst
โ๏ธ https://stratascratch.com/?via=free
9. Git and GitHub โ
โ๏ธ http://GitFluence.com
10. Blockchain โ
โ๏ธ https://t.me/Bitcoin_Crypto_Web
11. Mongo DB โ
โ๏ธ http://mongodb.com
12. Node JS โ
โ๏ธ http://nodejsera.com
13. English Speaking โ
โ๏ธ https://t.me/englishlearnerspro
14. C#โ
โ๏ธhttps://learn.microsoft.com/en-us/training/paths/get-started-c-sharp-part-1/
15. Excelโ
โ๏ธ https://t.me/excel_analyst
16. Generative AIโ
โ๏ธ https://t.me/generativeai_gpt
17. App Development โ
โ๏ธ https://t.me/appsuser
18. Power BI โ
โ๏ธ https://t.me/powerbi_analyst
19. Tableau โ
โ๏ธ https://www.tableau.com/learn/training
20. Machine Learning โ
โ๏ธ http://developers.google.com/machine-learning/crash-course
21. Artificial intelligence โ
โ๏ธ http://t.me/machinelearning_deeplearning/
22. Data Analytics โ
โ๏ธ https://medium.com/@data_analyst
โ๏ธ https://www.linkedin.com/company/sql-analysts
23. Java โ
โ๏ธ https://t.me/Java_Programming_Notes
โ๏ธ http://learn.microsoft.com/shows/java-for-beginners/
24. C/C++ โ
โ๏ธ http://imp.i115008.net/kjoq9V
โ๏ธ https://docs.microsoft.com/en-us/cpp/c-language/?view=msvc-170&viewFallbackFrom=vs-2019
25. Data Structures โ
โ๏ธ https://leetcode.com/study-plan/data-structure/
26. Cybersecurity โ
โ๏ธ https://t.me/EthicalHackingToday
27. Linux โ
โ๏ธ https://bit.ly/3KhPdf1
โ๏ธ https://training.linuxfoundation.org/resources/
28. Typescript โ
โ๏ธ http://learn.microsoft.com/training/paths/build-javascript-applications-typescript/
29. Deep Learning โ
โ๏ธ http://introtodeeplearning.com
30. Compiler Design โ
โ๏ธ http://online.stanford.edu/courses/soe-ycscs1-compilers
31. DSA โ
โ๏ธ http://techdevguide.withgoogle.com/paths/data-structures-and-algorithms/
32. Prompt Engineering โ
โ๏ธ https://www.promptingguide.ai/
โ๏ธ https://t.me/aiindi
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1. Web Development โ
โ๏ธ https://t.me/webdevcoursefree
2. CSS โ
โ๏ธ http://css-tricks.com
3. JavaScript โ
โ๏ธ http://t.me/javascript_courses
4. React โ
โ๏ธ http://react-tutorial.app
5. Tailwind CSS โ
โ๏ธ http://scrimba.com
6. Data Science โ
โ๏ธ https://t.me/datasciencefun
7. Python โ
โ๏ธ http://pythontutorial.net
8. SQL โ
โ๏ธ https://t.me/sqlanalyst
โ๏ธ https://stratascratch.com/?via=free
9. Git and GitHub โ
โ๏ธ http://GitFluence.com
10. Blockchain โ
โ๏ธ https://t.me/Bitcoin_Crypto_Web
11. Mongo DB โ
โ๏ธ http://mongodb.com
12. Node JS โ
โ๏ธ http://nodejsera.com
13. English Speaking โ
โ๏ธ https://t.me/englishlearnerspro
14. C#โ
โ๏ธhttps://learn.microsoft.com/en-us/training/paths/get-started-c-sharp-part-1/
15. Excelโ
โ๏ธ https://t.me/excel_analyst
16. Generative AIโ
โ๏ธ https://t.me/generativeai_gpt
17. App Development โ
โ๏ธ https://t.me/appsuser
18. Power BI โ
โ๏ธ https://t.me/powerbi_analyst
19. Tableau โ
โ๏ธ https://www.tableau.com/learn/training
20. Machine Learning โ
โ๏ธ http://developers.google.com/machine-learning/crash-course
21. Artificial intelligence โ
โ๏ธ http://t.me/machinelearning_deeplearning/
22. Data Analytics โ
โ๏ธ https://medium.com/@data_analyst
โ๏ธ https://www.linkedin.com/company/sql-analysts
23. Java โ
โ๏ธ https://t.me/Java_Programming_Notes
โ๏ธ http://learn.microsoft.com/shows/java-for-beginners/
24. C/C++ โ
โ๏ธ http://imp.i115008.net/kjoq9V
โ๏ธ https://docs.microsoft.com/en-us/cpp/c-language/?view=msvc-170&viewFallbackFrom=vs-2019
25. Data Structures โ
โ๏ธ https://leetcode.com/study-plan/data-structure/
26. Cybersecurity โ
โ๏ธ https://t.me/EthicalHackingToday
27. Linux โ
โ๏ธ https://bit.ly/3KhPdf1
โ๏ธ https://training.linuxfoundation.org/resources/
28. Typescript โ
โ๏ธ http://learn.microsoft.com/training/paths/build-javascript-applications-typescript/
29. Deep Learning โ
โ๏ธ http://introtodeeplearning.com
30. Compiler Design โ
โ๏ธ http://online.stanford.edu/courses/soe-ycscs1-compilers
31. DSA โ
โ๏ธ http://techdevguide.withgoogle.com/paths/data-structures-and-algorithms/
32. Prompt Engineering โ
โ๏ธ https://www.promptingguide.ai/
โ๏ธ https://t.me/aiindi
Join @free4unow_backup for more free courses
Like for more โค๏ธ
ENJOY LEARNING๐๐
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