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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How to prepare for coding interview in 2025 👇👇
1. Master Data Structures and Algorithms: Make sure you have a solid understanding of common data structures (such as arrays, linked lists, trees, graphs, etc.) and algorithms (sorting, searching, dynamic programming, etc.). Practice implementing them in your preferred programming language.
2. Practice Coding Problems: Solve coding problems on platforms like LeetCode, HackerRank, or CodeSignal. Focus on a variety of problem types to improve your problem-solving skills.
3. Review System Design Concepts: Understand the basics of system design principles and practice designing scalable systems. Resources like Grokking the System Design Interview can be helpful.
4. Learn the Latest Technologies: Stay updated with the latest technologies and trends in the industry. Familiarize yourself with popular frameworks, libraries, and tools that are commonly used in software development.
5. Mock Interviews: Practice mock interviews with friends, mentors, or through online platforms to simulate the interview experience. This will help you get comfortable with coding under pressure and receiving feedback.
6. Stay Consistent: Set aside dedicated time each day to practice coding problems and review concepts. Consistency is key to improving your skills over time.
7. Stay Calm and Confident: Remember that interviews are not just about technical skills but also about how you communicate and approach problem-solving. Stay calm, confident, and be prepared to explain your thought process during the interview.
Credits: https://t.me/free4unow_backup
All the best 👍👍
1. Master Data Structures and Algorithms: Make sure you have a solid understanding of common data structures (such as arrays, linked lists, trees, graphs, etc.) and algorithms (sorting, searching, dynamic programming, etc.). Practice implementing them in your preferred programming language.
2. Practice Coding Problems: Solve coding problems on platforms like LeetCode, HackerRank, or CodeSignal. Focus on a variety of problem types to improve your problem-solving skills.
3. Review System Design Concepts: Understand the basics of system design principles and practice designing scalable systems. Resources like Grokking the System Design Interview can be helpful.
4. Learn the Latest Technologies: Stay updated with the latest technologies and trends in the industry. Familiarize yourself with popular frameworks, libraries, and tools that are commonly used in software development.
5. Mock Interviews: Practice mock interviews with friends, mentors, or through online platforms to simulate the interview experience. This will help you get comfortable with coding under pressure and receiving feedback.
6. Stay Consistent: Set aside dedicated time each day to practice coding problems and review concepts. Consistency is key to improving your skills over time.
7. Stay Calm and Confident: Remember that interviews are not just about technical skills but also about how you communicate and approach problem-solving. Stay calm, confident, and be prepared to explain your thought process during the interview.
Credits: https://t.me/free4unow_backup
All the best 👍👍
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Important DSA concepts:
• Arrays
• Strings
• Sorting & Searching
• Hashing
• Linked List
• Stack & Queue
• Recursion & Backtracking
• Binary Tree & BST
• Heap & Priority Queue
• Graph Theory
• Dynamic Programming (DP)
• Greedy Algorithms
• Bit Manipulation
• Math & Number Theory
• Trie & Advanced Data Structures
• Arrays
• Strings
• Sorting & Searching
• Hashing
• Linked List
• Stack & Queue
• Recursion & Backtracking
• Binary Tree & BST
• Heap & Priority Queue
• Graph Theory
• Dynamic Programming (DP)
• Greedy Algorithms
• Bit Manipulation
• Math & Number Theory
• Trie & Advanced Data Structures
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Why Algorithm is Important for a Program
An efficient algorithm determines how fast and effectively a program can solve a problem. While modern hardware provides abundant memory, execution time remains a critical factor. Faster algorithms save time, enhance user experience, and enable scalability, especially for large datasets or real-time applications. A poor algorithm can lead to inefficiencies that no amount of hardware can fix.
Why Space is Less Important
With advancements in technology, storage has become cheaper and more abundant. For most applications, the cost of additional memory is negligible compared to the time lost due to an inefficient algorithm. However, in constrained environments (like embedded systems), space considerations may still matter.
An efficient algorithm determines how fast and effectively a program can solve a problem. While modern hardware provides abundant memory, execution time remains a critical factor. Faster algorithms save time, enhance user experience, and enable scalability, especially for large datasets or real-time applications. A poor algorithm can lead to inefficiencies that no amount of hardware can fix.
Why Space is Less Important
With advancements in technology, storage has become cheaper and more abundant. For most applications, the cost of additional memory is negligible compared to the time lost due to an inefficient algorithm. However, in constrained environments (like embedded systems), space considerations may still matter.
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