Coding Interview Resources

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Here is a powerful 𝗜𝗡𝗧𝗘𝗥𝗩𝗜𝗘𝗪 𝗧𝗜𝗣 to help you land a job! Most people who are skilled enough would be able to clear technical rounds with ease. But when it comes to 𝗯𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹/𝗰𝘂𝗹𝘁𝘂𝗿𝗲 𝗳𝗶𝘁 rounds, some folks may falter and lose the potential offer. Many companies schedule a behavioral round with a top-level manager in the organization to understand the culture fit (except for freshers). One needs to clear this round to reach the salary negotiation round. Here are some tips to clear such rounds: 1️⃣ Once the HR schedules the interview, try to find the LinkedIn profile of the interviewer using the name in their email ID. 2️⃣ Learn more about his/her past experiences and try to strike up a conversation on that during the interview. 3️⃣ This shows that you have done good research and also helps strike a personal connection. 4️⃣ Also, this is the round not just to evaluate if you're a fit for the company, but also to assess if the company is a right fit for you. 5️⃣ Hence, feel free to ask many questions about your role and company to get a clear understanding before taking the offer. This shows that you really care about the role you're getting into. 💡 𝗕𝗼𝗻𝘂𝘀 𝘁𝗶𝗽 - Be polite yet assertive in such interviews. It impresses a lot of senior folks.

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Datasets for Data Science Projects

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Clean Code Tips

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Goldman Sachs senior data analyst interview asked questions SQL 1 find avg of salaries department wise from table 2 Write a SQL query to see employee name and manager name using a self-join on 'employees' table with columns 'emp_id', 'name', and 'manager_id'. 3 newest joinee for every department (solved using lead lag) POWER BI 1. What does Filter context in DAX mean? 2. Explain how to implement Row-Level Security (RLS) in Power BI. 3. Describe different types of filters in Power BI. 4. Explain the difference between 'ALL' and 'ALLSELECTED' in DAX. 5. How do you calculate the total sales for a specific product using DAX? PYTHON 1. Create a dictionary, add elements to it, modify an element, and then print the dictionary in alphabetical order of keys. 2. Find unique values in a list of assorted numbers and print the count of how many times each value is repeated. 3. Find and print duplicate values in a list of assorted numbers, along with the number of times each value is repeated. I have curated best 80+ top-notch Data Analytics Resources 👇👇 https://t.me/DataSimplifier Hope this helps you 😊

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Top Libraries & Frameworks by Language 📚💻 ❯ Python  • Pandas ➟ Data Analysis  • NumPy ➟ Math & Arrays  • Scikit-learn ➟ Machine Learning  • TensorFlow / PyTorch ➟ Deep Learning  • Flask / Django ➟ Web Development  • OpenCV ➟ Image Processing ❯ JavaScript / TypeScript  • React ➟ UI Development  • Vue ➟ Lightweight SPAs  • Angular ➟ Enterprise Apps  • Next.js ➟ Full-Stack Web  • Express ➟ Backend APIs  • Three.js ➟ 3D Web Graphics ❯ Java  • Spring Boot ➟ Microservices  • Hibernate ➟ ORM  • Apache Maven ➟ Build Automation  • Apache Kafka ➟ Real-Time Data ❯ C++  • Boost ➟ Utility Libraries  • Qt ➟ GUI Applications  • Unreal Engine ➟ Game Development ❯ C#  • .NET / ASP.NET ➟ Web Apps  • Unity ➟ Game Development  • Entity Framework ➟ ORM ❯ R  • ggplot2 ➟ Data Visualization  • dplyr ➟ Data Manipulation  • caret ➟ Machine Learning  • Shiny ➟ Interactive Dashboards ❯ PHP  • Laravel ➟ Full-Stack Web  • Symfony ➟ Web Framework  • PHPUnit ➟ Testing ❯ Go (Golang)  • Gin ➟ Web Framework  • Gorilla ➟ Web Toolkit  • GORM ➟ ORM for Go ❯ Rust  • Actix ➟ Web Framework  • Rocket ➟ Web Development  • Tokio ➟ Async Runtime Coding Resources: https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17 React with ❤️ for more useful content

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Different Types of Data Structures Explained shortly

Array Sorting Algorithms

💡 Must Have Tools for Programmers

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Questions & Answers for Data Analyst Interview Question 1: Describe a time when you used data analysis to solve a business problem. Ideal answer: This is your opportunity to showcase your data analysis skills in a real-world context. Be specific and provide examples of your work. For example, you could talk about a time when you used data analysis to identify customer churn, improve marketing campaigns, or optimize product development. Question 2: What are some of the challenges you have faced in previous data analysis projects, and how did you overcome them? Ideal answer: This question is designed to assess your problem-solving skills and your ability to learn from your experiences. Be honest and upfront about the challenges you have faced, but also focus on how you overcame them. For example, you could talk about a time when you had to deal with a large and messy dataset, or a time when you had to work with a tight deadline. Question 3: How do you handle missing values in a dataset? Ideal answer: Missing values are a common problem in data analysis, so it is important to know how to handle them properly. There are a variety of different methods that you can use, depending on the specific situation. For example, you could delete the rows with missing values, impute the missing values using a statistical method, or assign a default value to the missing values. Question 4: How do you identify and remove outliers? Ideal answer: Outliers are data points that are significantly different from the rest of the data. They can be caused by data errors or by natural variation in the data. It is important to identify and remove outliers before performing data analysis, as they can skew the results. There are a variety of different methods that you can use to identify outliers, such as the interquartile range (IQR) method or the standard deviation method. Question 5: How do you interpret and communicate the results of your data analysis to non-technical audiences? Ideal answer: It is important to be able to communicate your data analysis findings to both technical and non-technical audiences. When communicating to non-technical audiences, it is important to avoid using jargon and to focus on the key takeaways from your analysis. You can use data visualization tools to help you communicate your findings in a clear and concise way. In addition to providing specific examples and answers to the questions, it is also important to be enthusiastic and demonstrate your passion for data analysis. Show the interviewer that you are excited about the opportunity to use your skills to solve real-world problems.

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