How to Learn Java in 2024
1. Set Clear Goals:
- Define your learning objectives. Do you want to build web applications, mobile apps, or work on enterprise-level software?
2. Choose a Structured Learning Path:
- Follow a structured learning path that covers the fundamentals of Java, object-oriented programming principles, and essential libraries.
3. Start with the Basics:
- Begin with the core concepts of Java, such as variables, data types, operators, and control flow statements.
4. Master Object-Oriented Programming:
- Learn about classes, objects, inheritance, polymorphism, and encapsulation.
5. Explore Java Libraries:
- Familiarize yourself with commonly used Java libraries, such as those for input/output, networking, and data structures.
6. Practice Regularly:
- Write code regularly to reinforce your understanding and identify areas where you need more practice.
7. Leverage Online Resources:
- Utilize online courses, tutorials, and documentation to supplement your learning.
8. Join a Coding Community:
- Engage with online coding communities and forums to ask questions, share knowledge, and collaborate on projects.
9. Build Projects:
- Create simple projects to apply your skills and gain practical experience.
10. Stay Updated with Java Releases:
- Keep up with the latest Java releases and updates to ensure your knowledge remains current.
11. Explore Frameworks and Tools:
- Learn about popular Java frameworks and tools, such as Spring Boot, Maven, and IntelliJ IDEA.
12. Contribute to Open Source Projects:
- Contribute to open source Java projects to gain real-world experience and showcase your skills.
13. Seek Feedback and Mentoring:
- Seek feedback from experienced Java developers and consider mentorship opportunities to accelerate your learning.
14. Prepare for Certifications:
- Consider pursuing Java certifications, such as the Oracle Certified Java Programmer (OCJP), to validate your skills.
15. Network with Java Developers:
- Attend Java meetups, conferences, and online events to connect with other Java developers and learn from their experiences.
Best Programming Resources: https://topmate.io/coding/898340
Java Programming Resources: https://t.iss.one/Java_Programming_Notes
ENJOY LEARNING 👍👍
1. Set Clear Goals:
- Define your learning objectives. Do you want to build web applications, mobile apps, or work on enterprise-level software?
2. Choose a Structured Learning Path:
- Follow a structured learning path that covers the fundamentals of Java, object-oriented programming principles, and essential libraries.
3. Start with the Basics:
- Begin with the core concepts of Java, such as variables, data types, operators, and control flow statements.
4. Master Object-Oriented Programming:
- Learn about classes, objects, inheritance, polymorphism, and encapsulation.
5. Explore Java Libraries:
- Familiarize yourself with commonly used Java libraries, such as those for input/output, networking, and data structures.
6. Practice Regularly:
- Write code regularly to reinforce your understanding and identify areas where you need more practice.
7. Leverage Online Resources:
- Utilize online courses, tutorials, and documentation to supplement your learning.
8. Join a Coding Community:
- Engage with online coding communities and forums to ask questions, share knowledge, and collaborate on projects.
9. Build Projects:
- Create simple projects to apply your skills and gain practical experience.
10. Stay Updated with Java Releases:
- Keep up with the latest Java releases and updates to ensure your knowledge remains current.
11. Explore Frameworks and Tools:
- Learn about popular Java frameworks and tools, such as Spring Boot, Maven, and IntelliJ IDEA.
12. Contribute to Open Source Projects:
- Contribute to open source Java projects to gain real-world experience and showcase your skills.
13. Seek Feedback and Mentoring:
- Seek feedback from experienced Java developers and consider mentorship opportunities to accelerate your learning.
14. Prepare for Certifications:
- Consider pursuing Java certifications, such as the Oracle Certified Java Programmer (OCJP), to validate your skills.
15. Network with Java Developers:
- Attend Java meetups, conferences, and online events to connect with other Java developers and learn from their experiences.
Best Programming Resources: https://topmate.io/coding/898340
Java Programming Resources: https://t.iss.one/Java_Programming_Notes
ENJOY LEARNING 👍👍
👍8❤2
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++?
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ENJOY LEARNING 👍👍
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++?
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-> https://t.iss.one/addlist/4q2PYC0pH_VjZDk5
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👍8❤2
Here are some interview preparation tips 👇👇
Technical Interview
1. Review Core Concepts:
- Data Structures: Be comfortable with LinkedLists, Trees, Graphs, and their representations.
- Algorithms: Brush up on searching and sorting algorithms, time complexities, and common algorithms (like Dijkstra’s or A*).
- Programming Languages: Ensure you understand the language you are most comfortable with (e.g., C++, Java, Python) and know its standard library functions.
2. Practice Coding Problems:
- Utilize platforms like LeetCode, HackerRank, or CodeSignal to practice medium-level coding questions. Focus on common patterns and problem-solving strategies.
3. Mock Interviews: Conduct mock technical interviews with peers or mentors to build confidence and receive feedback.
Personal Interview
1. Prepare Your Story:
- Outline your educational journey, achievements, and any relevant projects. Emphasize experiences that demonstrate leadership, teamwork, and problem-solving skills.
- Be ready to discuss your challenges and how you overcame them.
2. Articulate Your Goals:
- Be clear about why you want to join the program and how it aligns with your career aspirations. Reflect on what you hope to gain from the experience.
- Focus on Fundamentals:
Be thorough with basic subjects like Operating Systems, Networking, OOP, and Databases. Clear concepts are key for technical interviews.
2. Common Interview Questions:
DSA:
- Implement various data structures like Linked Lists, Trees, Graphs, Stacks, and Queues.
- Understand searching and sorting algorithms: Binary Search, Merge Sort, Quick Sort, etc.
- Solve problems involving HashMaps, Sets, and other collections.
Sample DSA Questions
- Reverse a linked list.
- Find the first non-repeating character in a string.
- Detect a cycle in a graph.
- Implement a queue using two stacks.
- Find the lowest common ancestor in a binary tree.
3. Key Topics to Focus On
DSA:
- Arrays, Strings, Linked Lists, Trees, Graphs
- Recursion, Backtracking, Dynamic Programming
- Sorting and Searching Algorithms
- Time and Space Complexity
Core Subjects
- Operating Systems: Concepts like processes, threads, deadlocks, concurrency, and memory management.
- Database Management Systems (DBMS): Understanding SQL, Normalization, and database design.
- Object-Oriented Programming (OOP): Know about inheritance, polymorphism, encapsulation, and design patterns.
5. Tips
- Optimize Your Code: Write clean, optimized code. Discuss time and space complexities during interviews.
- Review Your Projects: Be ready to explain your past projects, the challenges you faced, and the technologies you used.....
Best Programming Resources: https://topmate.io/coding/898340
All the best 👍👍
Technical Interview
1. Review Core Concepts:
- Data Structures: Be comfortable with LinkedLists, Trees, Graphs, and their representations.
- Algorithms: Brush up on searching and sorting algorithms, time complexities, and common algorithms (like Dijkstra’s or A*).
- Programming Languages: Ensure you understand the language you are most comfortable with (e.g., C++, Java, Python) and know its standard library functions.
2. Practice Coding Problems:
- Utilize platforms like LeetCode, HackerRank, or CodeSignal to practice medium-level coding questions. Focus on common patterns and problem-solving strategies.
3. Mock Interviews: Conduct mock technical interviews with peers or mentors to build confidence and receive feedback.
Personal Interview
1. Prepare Your Story:
- Outline your educational journey, achievements, and any relevant projects. Emphasize experiences that demonstrate leadership, teamwork, and problem-solving skills.
- Be ready to discuss your challenges and how you overcame them.
2. Articulate Your Goals:
- Be clear about why you want to join the program and how it aligns with your career aspirations. Reflect on what you hope to gain from the experience.
- Focus on Fundamentals:
Be thorough with basic subjects like Operating Systems, Networking, OOP, and Databases. Clear concepts are key for technical interviews.
2. Common Interview Questions:
DSA:
- Implement various data structures like Linked Lists, Trees, Graphs, Stacks, and Queues.
- Understand searching and sorting algorithms: Binary Search, Merge Sort, Quick Sort, etc.
- Solve problems involving HashMaps, Sets, and other collections.
Sample DSA Questions
- Reverse a linked list.
- Find the first non-repeating character in a string.
- Detect a cycle in a graph.
- Implement a queue using two stacks.
- Find the lowest common ancestor in a binary tree.
3. Key Topics to Focus On
DSA:
- Arrays, Strings, Linked Lists, Trees, Graphs
- Recursion, Backtracking, Dynamic Programming
- Sorting and Searching Algorithms
- Time and Space Complexity
Core Subjects
- Operating Systems: Concepts like processes, threads, deadlocks, concurrency, and memory management.
- Database Management Systems (DBMS): Understanding SQL, Normalization, and database design.
- Object-Oriented Programming (OOP): Know about inheritance, polymorphism, encapsulation, and design patterns.
5. Tips
- Optimize Your Code: Write clean, optimized code. Discuss time and space complexities during interviews.
- Review Your Projects: Be ready to explain your past projects, the challenges you faced, and the technologies you used.....
Best Programming Resources: https://topmate.io/coding/898340
All the best 👍👍
👍15❤4
👍19❤9
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 Python’s 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 can’t make use of dictionaries or sets.
Best Programming Resources: https://topmate.io/coding/898340
All the best 👍👍
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 Python’s 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 can’t make use of dictionaries or sets.
Best Programming Resources: https://topmate.io/coding/898340
All the best 👍👍
👍10🥰2👌1
If you aspire to work in top product companies, here’s my advice:
👉 For SDE-1 or SWE positions, focus on:
✔️ Continuously upskilling and improving your abilities.
✔️ Developing strong problem-solving skills.
✔️Mastering DSA – trust me, you’ll be tested on it, so aim to excel.
Also, learn how to design scalable systems and understand how to build solutions that can handle growth in users and data.
👉 For higher-level roles (SDE-2 and SDE-3), focus on:
✔️ DSA + System Design (both LLD and HLD).
✔️ Building your leadership skills, as you’ll need to lead teams and projects.
🔸I know it’s challenging to do this while working full-time, but you’ll need to carve out time to consistently upskill yourself.
Remember, your learning plan should be sensible and well-organized.
Best Programming Resources: https://topmate.io/coding/886839
ENJOY LEARNING 👍👍
👉 For SDE-1 or SWE positions, focus on:
✔️ Continuously upskilling and improving your abilities.
✔️ Developing strong problem-solving skills.
✔️Mastering DSA – trust me, you’ll be tested on it, so aim to excel.
Also, learn how to design scalable systems and understand how to build solutions that can handle growth in users and data.
👉 For higher-level roles (SDE-2 and SDE-3), focus on:
✔️ DSA + System Design (both LLD and HLD).
✔️ Building your leadership skills, as you’ll need to lead teams and projects.
🔸I know it’s challenging to do this while working full-time, but you’ll need to carve out time to consistently upskill yourself.
Remember, your learning plan should be sensible and well-organized.
Best Programming Resources: https://topmate.io/coding/886839
ENJOY LEARNING 👍👍
👍7❤4
30-day roadmap to learn Java up to an intermediate level.
This roadmap is designed for beginners, so adjust your pace as needed.
Week 1: Java Basics
*Day 1-2:*
- Day 1: Get Java installed on your computer and set up your development environment.
- Day 2: Learn about Java's history, its role in programming, and write your first "Hello, World!" program.
*Day 3-4:*
- Day 3: Study Java syntax, data types, and variables.
- Day 4: Understand operators and perform basic arithmetic operations.
*Day 5-7:*
- Day 5: Explore control flow with if-else statements and loops (for and while).
- Day 6: Dive into switch statements and understand how to handle user choices.
- Day 7: Practice writing small programs that use conditions and loops.
Week 2: Functions and Object-Oriented Programming
*Day 8-9:*
- Day 8: Learn about functions (methods) and how to define your own functions in Java.
- Day 9: Study function parameters, return types, and method overloading.
*Day 10-12:*
- Day 10: Understand the basics of object-oriented programming (OOP) in Java.
- Day 11: Learn about classes, objects, and constructors.
- Day 12: Explore encapsulation, inheritance, and polymorphism.
*Day 13-14:*
- Day 13: Study Java packages and access modifiers (public, private, protected).
- Day 14: Practice creating classes and objects in real-world scenarios.
Week 3: Data Structures and Collections
*Day 15-17:*
- Day 15: Dive into arrays in Java and understand their usage.
- Day 16: Study Java's collection framework and ArrayList.
- Day 17: Learn about iterating through collections using loops and iterators.
*Day 18-19:*
- Day 18: Explore other collection types like LinkedList and HashMap.
- Day 19: Understand when to use different collection types in Java.
*Day 20-21:*
- Day 20: Study exception handling in Java and how to deal with errors.
- Day 21: Practice working with try-catch blocks and handling exceptions effectively.
Week 4: Intermediate Topics and Projects
*Day 22-23:*
- Day 22: Study file handling in Java, including reading and writing files.
- Day 23: Create a small project that involves file operations.
*Day 24-26:*
- Day 24: Learn about multithreading and how to create and manage threads in Java.
- Day 25: Study Java's built-in libraries for networking and socket programming.
- Day 26: Work on a project that involves multithreading or networking.
*Day 27-28:*
- Day 27: Explore more advanced Java topics like JavaFX for GUI development or JDBC for database connectivity.
- Day 28: Work on a more complex project that combines your knowledge from the past weeks.
*Day 29-30:*
- Day 29: Review and revisit any topics you found challenging.
- Day 30: Continue building projects and exploring areas of Java that interest you.
Consider joining Java communities and forums to seek help and advice. Java is a versatile language with many applications, so your learning journey can continue well beyond this roadmap. Good luck!
This roadmap is designed for beginners, so adjust your pace as needed.
Week 1: Java Basics
*Day 1-2:*
- Day 1: Get Java installed on your computer and set up your development environment.
- Day 2: Learn about Java's history, its role in programming, and write your first "Hello, World!" program.
*Day 3-4:*
- Day 3: Study Java syntax, data types, and variables.
- Day 4: Understand operators and perform basic arithmetic operations.
*Day 5-7:*
- Day 5: Explore control flow with if-else statements and loops (for and while).
- Day 6: Dive into switch statements and understand how to handle user choices.
- Day 7: Practice writing small programs that use conditions and loops.
Week 2: Functions and Object-Oriented Programming
*Day 8-9:*
- Day 8: Learn about functions (methods) and how to define your own functions in Java.
- Day 9: Study function parameters, return types, and method overloading.
*Day 10-12:*
- Day 10: Understand the basics of object-oriented programming (OOP) in Java.
- Day 11: Learn about classes, objects, and constructors.
- Day 12: Explore encapsulation, inheritance, and polymorphism.
*Day 13-14:*
- Day 13: Study Java packages and access modifiers (public, private, protected).
- Day 14: Practice creating classes and objects in real-world scenarios.
Week 3: Data Structures and Collections
*Day 15-17:*
- Day 15: Dive into arrays in Java and understand their usage.
- Day 16: Study Java's collection framework and ArrayList.
- Day 17: Learn about iterating through collections using loops and iterators.
*Day 18-19:*
- Day 18: Explore other collection types like LinkedList and HashMap.
- Day 19: Understand when to use different collection types in Java.
*Day 20-21:*
- Day 20: Study exception handling in Java and how to deal with errors.
- Day 21: Practice working with try-catch blocks and handling exceptions effectively.
Week 4: Intermediate Topics and Projects
*Day 22-23:*
- Day 22: Study file handling in Java, including reading and writing files.
- Day 23: Create a small project that involves file operations.
*Day 24-26:*
- Day 24: Learn about multithreading and how to create and manage threads in Java.
- Day 25: Study Java's built-in libraries for networking and socket programming.
- Day 26: Work on a project that involves multithreading or networking.
*Day 27-28:*
- Day 27: Explore more advanced Java topics like JavaFX for GUI development or JDBC for database connectivity.
- Day 28: Work on a more complex project that combines your knowledge from the past weeks.
*Day 29-30:*
- Day 29: Review and revisit any topics you found challenging.
- Day 30: Continue building projects and exploring areas of Java that interest you.
Consider joining Java communities and forums to seek help and advice. Java is a versatile language with many applications, so your learning journey can continue well beyond this roadmap. Good luck!
👍9❤4
Beginner’s Roadmap to Learn Data Structures & Algorithms
1. Foundations: Start with the basics of programming and mathematical concepts to build a strong foundation.
2. Data Structure: Dive into essential data structures like arrays, linked lists, stacks, and queues to organise and store data efficiently.
3. Searching & Sorting: Learn various search and sort techniques to optimise data retrieval and organisation.
4. Trees & Graphs: Understand the concepts of binary trees and graph representation to tackle complex hierarchical data.
5. Recursion: Grasp the principles of recursion and how to implement recursive algorithms for problem-solving.
6. Advanced Data Structures: Explore advanced structures like hashing, heaps, and hash maps to enhance data manipulation.
7. Algorithms: Master algorithms such as greedy, divide and conquer, and dynamic programming to solve intricate problems.
8. Advanced Topics: Delve into backtracking, string algorithms, and bit manipulation for a deeper understanding.
9. Problem Solving: Practice on coding platforms like LeetCode to sharpen your skills and solve real-world algorithmic challenges.
10. Projects & Portfolio: Build real-world projects and showcase your skills on GitHub to create an impressive portfolio.
Best DSA RESOURCES: https://topmate.io/coding/886874
All the best 👍👍
1. Foundations: Start with the basics of programming and mathematical concepts to build a strong foundation.
2. Data Structure: Dive into essential data structures like arrays, linked lists, stacks, and queues to organise and store data efficiently.
3. Searching & Sorting: Learn various search and sort techniques to optimise data retrieval and organisation.
4. Trees & Graphs: Understand the concepts of binary trees and graph representation to tackle complex hierarchical data.
5. Recursion: Grasp the principles of recursion and how to implement recursive algorithms for problem-solving.
6. Advanced Data Structures: Explore advanced structures like hashing, heaps, and hash maps to enhance data manipulation.
7. Algorithms: Master algorithms such as greedy, divide and conquer, and dynamic programming to solve intricate problems.
8. Advanced Topics: Delve into backtracking, string algorithms, and bit manipulation for a deeper understanding.
9. Problem Solving: Practice on coding platforms like LeetCode to sharpen your skills and solve real-world algorithmic challenges.
10. Projects & Portfolio: Build real-world projects and showcase your skills on GitHub to create an impressive portfolio.
Best DSA RESOURCES: https://topmate.io/coding/886874
All the best 👍👍
👍11❤1
Best Resources to learn Programming
👇👇
https://topmate.io/coding/886839
Most programmers hoard resources without actually opening them even once! The reason for keeping a small price for these resources is to ensure that you value the content available inside this and encourage you to make the best out of it.
Hope this helps in your job search journey... All the best!👍✌️
👇👇
https://topmate.io/coding/886839
Most programmers hoard resources without actually opening them even once! The reason for keeping a small price for these resources is to ensure that you value the content available inside this and encourage you to make the best out of it.
Hope this helps in your job search journey... All the best!👍✌️
❤7👍4🫡1
Here's a good list of cheat sheets for programmers (all free):
Data Science Cheatsheet
https://github.com/aaronwangy/Data-Science-Cheatsheet
SQL Cheatsheet
sqltutorial.org/sql-cheat-sheet
t.iss.one/sqlspecialist/827
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htmlcheatsheet.com
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t.iss.one/webdevelopmentbook/90
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Data Science Cheatsheet
https://github.com/aaronwangy/Data-Science-Cheatsheet
SQL Cheatsheet
sqltutorial.org/sql-cheat-sheet
t.iss.one/sqlspecialist/827
https://www.sqltutorial.org/wp-content/uploads/2016/04/SQL-cheat-sheet.pdf
Java Programming Cheatsheet
https://introcs.cs.princeton.edu/java/11cheatsheet/
Javascript Cheatsheet
quickref.me/javascript.html
t.iss.one/javascript_courses/532
Data Analytics Cheatsheets
https://dataanalytics.beehiiv.com/p/data
Python Cheat sheet
quickref.me/python.html
https://t.iss.one/pythondevelopersindia/314
GIT and Machine Learning Cheatsheet
https://t.iss.one/datasciencefun/714
HTML Cheatsheet
https://web.stanford.edu/group/csp/cs21/htmlcheatsheet.pdf
htmlcheatsheet.com
CSS Cheatsheet
htmlcheatsheet.com/css
jQuery Cheatsheet
t.iss.one/webdevelopmentbook/90
Data Visualization
t.iss.one/datasciencefun/698
Free entry to our WhatsApp channel
Join @free4unow_backup for more free resources
Like for more ❤️
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Sample email template to reach out to HR’s as fresher
I hope you will found this helpful 🙂
Hi Jasneet,
I recently came across your LinkedIn post seeking a React.js developer intern, and I am writing to express my interest in the position at Airtel. As a recent graduate, I am eager to begin my career and am excited about the opportunity.
I am a quick learner and have developed a strong set of dynamic and user-friendly web applications using various technologies, including HTML, CSS, JavaScript, Bootstrap, React.js, Vue.js, PHP, and MySQL. I am also well-versed in creating reusable components, implementing responsive designs, and ensuring cross-browser compatibility.
I am confident that my eagerness to learn and strong work ethic will make me an asset to your team.
I have attached my resume for your review. Thank you for considering my application. I look forward to hearing from you soon.
Thanks!I hope you will found this helpful 🙂
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If you're a job seeker, these well structured resources will help you to know and learn all the real time Python Interview questions with their exact answer. Folks who are having 0-4 years of experience have cracked the interview using this guide!
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How can you stand out as a software engineer?
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Most fall short here.
Learn the skills that others avoid:
• Learn unit testing.
• Learn CI/CD pipelines.
• Learn automation tools.
• Learn performance tuning.
• Learn security best practices.
• Learn effective branching strategies.
• Learn cloud infrastructure management.
Most fall short here.
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How to apply for Tech companies.pdf
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Don't overwhelm to learn Git,🙌
Git is only this much👇😇
1.Core:
• git init
• git clone
• git add
• git commit
• git status
• git diff
• git checkout
• git reset
• git log
• git show
• git tag
• git push
• git pull
2.Branching:
• git branch
• git checkout -b
• git merge
• git rebase
• git branch --set-upstream-to
• git branch --unset-upstream
• git cherry-pick
3.Merging:
• git merge
• git rebase
4.Stashing:
• git stash
• git stash pop
• git stash list
• git stash apply
• git stash drop
5.Remotes:
• git remote
• git remote add
• git remote remove
• git fetch
• git pull
• git push
• git clone --mirror
6.Configuration:
• git config
• git global config
• git reset config
7. Plumbing:
• git cat-file
• git checkout-index
• git commit-tree
• git diff-tree
• git for-each-ref
• git hash-object
• git ls-files
• git ls-remote
• git merge-tree
• git read-tree
• git rev-parse
• git show-branch
• git show-ref
• git symbolic-ref
• git tag --list
• git update-ref
8.Porcelain:
• git blame
• git bisect
• git checkout
• git commit
• git diff
• git fetch
• git grep
• git log
• git merge
• git push
• git rebase
• git reset
• git show
• git tag
9.Alias:
• git config --global alias.<alias> <command>
10.Hook:
• git config --local core.hooksPath <path>
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Git is only this much👇😇
1.Core:
• git init
• git clone
• git add
• git commit
• git status
• git diff
• git checkout
• git reset
• git log
• git show
• git tag
• git push
• git pull
2.Branching:
• git branch
• git checkout -b
• git merge
• git rebase
• git branch --set-upstream-to
• git branch --unset-upstream
• git cherry-pick
3.Merging:
• git merge
• git rebase
4.Stashing:
• git stash
• git stash pop
• git stash list
• git stash apply
• git stash drop
5.Remotes:
• git remote
• git remote add
• git remote remove
• git fetch
• git pull
• git push
• git clone --mirror
6.Configuration:
• git config
• git global config
• git reset config
7. Plumbing:
• git cat-file
• git checkout-index
• git commit-tree
• git diff-tree
• git for-each-ref
• git hash-object
• git ls-files
• git ls-remote
• git merge-tree
• git read-tree
• git rev-parse
• git show-branch
• git show-ref
• git symbolic-ref
• git tag --list
• git update-ref
8.Porcelain:
• git blame
• git bisect
• git checkout
• git commit
• git diff
• git fetch
• git grep
• git log
• git merge
• git push
• git rebase
• git reset
• git show
• git tag
9.Alias:
• git config --global alias.<alias> <command>
10.Hook:
• git config --local core.hooksPath <path>
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