How to approach a DSA problem:
๐ญ. ๐ง๐ถ๐บ๐ฒ ๐ฏ๐ผ๐บ๐ฏ:
- Read the problem two times. Solve the examples using pen and paper and check if your answers match. Calculate the time complexity and see if it matches the constraints. If your algorithm approach is correct, attempt the question. If not, you have 45 minutes โ set a timer and move to the next step.
๐ฎ. ๐๐ถ๐ป๐ฑ ๐๐ต๐ฒ ๐ฟ๐ถ๐ด๐ต๐ ๐๐ผ๐น๐๐๐ถ๐ผ๐ป:
- Go to the discussion section and check the top solutions. Look for a solution that will help you get the job, not a fancy or exotic one. Focus on a simple approach, study it properly, and youโll start seeing patterns. Use that pattern and implement the solution.
๐ฏ. ๐๐ฑ๐ฒ๐ป๐๐ถ๐ณ๐ ๐๐ต๐ฒ ๐ฝ๐ฎ๐๐๐ฒ๐ฟ๐ป:
- Solve the suggested problems. This way, youโll learn multiple patterns. DSA works on patterns, not just learning. Focus on basic problems to improve your pattern recognition and then solve more problems related to that pattern to clear your concepts.
๐ฐ. ๐๐ฒ๐ฒ๐๐ฐ๐ผ๐ฑ๐ฒ ๐ด๐ฌ/๐ฎ๐ฌ ๐ฟ๐๐น๐ฒ:
- Solve the 20% of problems that are asked in 80% of interviews. Use Blind 75 or Neetcode 150. Check the company-specific discussion forums on Leetcode to see which questions are being asked recently. Focus on those questions, especially around common topics like graphs or dynamic programming, because companies tend to repeat similar questions. This will help you prepare better.
๐ฑ. ๐๐ผ๐ฐ๐๐ ๐ผ๐ป ๐พ๐๐ฎ๐น๐ถ๐๐, ๐ป๐ผ๐ ๐พ๐๐ฎ๐ป๐๐ถ๐๐:
- Solve quality questions that will help clarify your fundamentals. Copy-pasting solutions wonโt help. Jump to medium-level questions, as most interview questions are of medium difficulty. Aim for 65% accuracy, and once you reach that, move on to harder questions. This will build your confidence and improve your problem-solving skills.
Best DSA RESOURCES: https://topmate.io/coding/886874
All the best ๐๐
๐ญ. ๐ง๐ถ๐บ๐ฒ ๐ฏ๐ผ๐บ๐ฏ:
- Read the problem two times. Solve the examples using pen and paper and check if your answers match. Calculate the time complexity and see if it matches the constraints. If your algorithm approach is correct, attempt the question. If not, you have 45 minutes โ set a timer and move to the next step.
๐ฎ. ๐๐ถ๐ป๐ฑ ๐๐ต๐ฒ ๐ฟ๐ถ๐ด๐ต๐ ๐๐ผ๐น๐๐๐ถ๐ผ๐ป:
- Go to the discussion section and check the top solutions. Look for a solution that will help you get the job, not a fancy or exotic one. Focus on a simple approach, study it properly, and youโll start seeing patterns. Use that pattern and implement the solution.
๐ฏ. ๐๐ฑ๐ฒ๐ป๐๐ถ๐ณ๐ ๐๐ต๐ฒ ๐ฝ๐ฎ๐๐๐ฒ๐ฟ๐ป:
- Solve the suggested problems. This way, youโll learn multiple patterns. DSA works on patterns, not just learning. Focus on basic problems to improve your pattern recognition and then solve more problems related to that pattern to clear your concepts.
๐ฐ. ๐๐ฒ๐ฒ๐๐ฐ๐ผ๐ฑ๐ฒ ๐ด๐ฌ/๐ฎ๐ฌ ๐ฟ๐๐น๐ฒ:
- Solve the 20% of problems that are asked in 80% of interviews. Use Blind 75 or Neetcode 150. Check the company-specific discussion forums on Leetcode to see which questions are being asked recently. Focus on those questions, especially around common topics like graphs or dynamic programming, because companies tend to repeat similar questions. This will help you prepare better.
๐ฑ. ๐๐ผ๐ฐ๐๐ ๐ผ๐ป ๐พ๐๐ฎ๐น๐ถ๐๐, ๐ป๐ผ๐ ๐พ๐๐ฎ๐ป๐๐ถ๐๐:
- Solve quality questions that will help clarify your fundamentals. Copy-pasting solutions wonโt help. Jump to medium-level questions, as most interview questions are of medium difficulty. Aim for 65% accuracy, and once you reach that, move on to harder questions. This will build your confidence and improve your problem-solving skills.
Best DSA RESOURCES: https://topmate.io/coding/886874
All the best ๐๐
๐8
Interview Questions related to STAR (Situation, Task, Action, Result) approach for a Data Analyst ๐๐
1. Situation: In your previous role, describe a situation where you had to analyze a large and complex dataset.
Task: What was the specific task or problem you needed to address with this dataset?
Action: Explain the steps you took to clean, process, and analyze the data. What tools and techniques did you use?
Result: What insights or findings did you uncover, and how did they impact the project or organization?
2. Situation: Tell me about a time when you were asked to work on a project with tight deadlines.
Task: What was the project, and what were the specific data analysis requirements and deadlines?
Action: Describe how you organized your work and managed your time to meet the tight deadlines.
Result: What was the outcome, and how did your ability to deliver on time affect the project or team?
3. Situation: Share an example of a project where you needed to collaborate with cross-functional teams.
Task: What was the project, and what were the roles and responsibilities of the teams involved?
Action: Explain how you facilitated collaboration, communicated findings, and ensured that data analysis aligned with the project's goals.
Result: What was the impact of successful collaboration on the project's success?
4. Situation: Describe a scenario where you encountered a data quality issue in a dataset you were working with.
Task: What was the data quality problem, and how did it affect the analysis you needed to perform?
Action: Detail the steps you took to identify and rectify the data quality issue.
Result: What were the consequences of addressing the issue, and how did it improve the quality of your analysis?
5. Situation: Discuss a time when you were responsible for presenting your data analysis findings to non-technical stakeholders.
Task: What was the purpose of the presentation, and who were the stakeholders?
Action: Explain how you prepared and delivered the presentation, including any data visualization techniques used.
Result: What was the reaction of the stakeholders, and did your presentation lead to any actionable insights or decisions?
These STAR questions help assess not only a candidate's technical skills but also their ability to apply those skills in real-world situations and achieve meaningful results.
Like this post if you also need the sample answers for the above questions โค๏ธ๐
Share with credits: https://t.me/sqlspecialist
Hope it helps :)
1. Situation: In your previous role, describe a situation where you had to analyze a large and complex dataset.
Task: What was the specific task or problem you needed to address with this dataset?
Action: Explain the steps you took to clean, process, and analyze the data. What tools and techniques did you use?
Result: What insights or findings did you uncover, and how did they impact the project or organization?
2. Situation: Tell me about a time when you were asked to work on a project with tight deadlines.
Task: What was the project, and what were the specific data analysis requirements and deadlines?
Action: Describe how you organized your work and managed your time to meet the tight deadlines.
Result: What was the outcome, and how did your ability to deliver on time affect the project or team?
3. Situation: Share an example of a project where you needed to collaborate with cross-functional teams.
Task: What was the project, and what were the roles and responsibilities of the teams involved?
Action: Explain how you facilitated collaboration, communicated findings, and ensured that data analysis aligned with the project's goals.
Result: What was the impact of successful collaboration on the project's success?
4. Situation: Describe a scenario where you encountered a data quality issue in a dataset you were working with.
Task: What was the data quality problem, and how did it affect the analysis you needed to perform?
Action: Detail the steps you took to identify and rectify the data quality issue.
Result: What were the consequences of addressing the issue, and how did it improve the quality of your analysis?
5. Situation: Discuss a time when you were responsible for presenting your data analysis findings to non-technical stakeholders.
Task: What was the purpose of the presentation, and who were the stakeholders?
Action: Explain how you prepared and delivered the presentation, including any data visualization techniques used.
Result: What was the reaction of the stakeholders, and did your presentation lead to any actionable insights or decisions?
These STAR questions help assess not only a candidate's technical skills but also their ability to apply those skills in real-world situations and achieve meaningful results.
Like this post if you also need the sample answers for the above questions โค๏ธ๐
Share with credits: https://t.me/sqlspecialist
Hope it helps :)
โค1๐1
Sample email template to reach out to HRโs as fresher
I hope you will found this helpful ๐
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 ๐
๐2โค1
How to prepare for coding interview in 2025 ๐๐
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 ๐๐
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 ๐๐
๐1
Important DSA concepts:
โข Arrays
โข Strings
โข Sorting & Searching
โข Hashing
โข Linked List
โข Stack & Queue
โข Recursion & Backtracking
โข Binary Tree & BST
โข Heap & Priority Queue
โข Graph Theory
โข Dynamic Programming (DP)
โข Greedy Algorithms
โข Bit Manipulation
โข Math & Number Theory
โข Trie & Advanced Data Structures
โข Arrays
โข Strings
โข Sorting & Searching
โข Hashing
โข Linked List
โข Stack & Queue
โข Recursion & Backtracking
โข Binary Tree & BST
โข Heap & Priority Queue
โข Graph Theory
โข Dynamic Programming (DP)
โข Greedy Algorithms
โข Bit Manipulation
โข Math & Number Theory
โข Trie & Advanced Data Structures
๐3