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Which programming language should I use on interview?

Companies usually let you choose, in which case you should use your most comfortable language. If you know a bunch of languages, prefer one that lets you express more with fewer characters and fewer lines of code, like Python or Ruby. It keeps your whiteboard cleaner.

Try to stick with the same language for the whole interview, but sometimes you might want to switch languages for a question. E.g., processing a file line by line will be far easier in Python than in C++.

Sometimes, though, your interviewer will do this thing where they have a pet question thatโ€™s, for example, C-specific. If you list C on your resume, theyโ€™ll ask it.

So keep that in mind! If youโ€™re not confident with a language, make that clear on your resume. Put your less-strong languages under a header like โ€˜Working Knowledge.โ€™
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๐Ÿš€๐—ง๐—ผ๐—ฝ ๐Ÿฏ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—š๐—ผ๐—ผ๐—ด๐—น๐—ฒ-๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฒ๐—ฑ ๐—ฃ๐˜†๐˜๐—ต๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ๐Ÿ˜

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โœ… Future You Will Thank You!
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Frontend development roadmap
โค1
Forwarded from Artificial Intelligence
๐—™๐—ฅ๐—˜๐—˜ ๐—ง๐—”๐—ง๐—” ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—ฉ๐—ถ๐—ฟ๐˜๐˜‚๐—ฎ๐—น ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐—ป๐˜€๐—ต๐—ถ๐—ฝ ๐—ณ๐—ผ๐—ฟ ๐—•๐—ฒ๐—ด๐—ถ๐—ป๐—ป๐—ฒ๐—ฟ๐˜€ (๐—ช๐—ถ๐˜๐—ต ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ฒ)๐Ÿ˜

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5 Handy Tips to master Data Science โฌ‡๏ธ


1๏ธโƒฃ Begin with introductory projects that cover the fundamental concepts of data science, such as data exploration, cleaning, and visualization. These projects will help you get familiar with common data science tools and libraries like Python (Pandas, NumPy, Matplotlib), R, SQL, and Excel

2๏ธโƒฃ Look for publicly available datasets from sources like Kaggle, UCI Machine Learning Repository. Working with real-world data will expose you to the challenges of messy, incomplete, and heterogeneous data, which is common in practical scenarios.

3๏ธโƒฃ Explore various data science techniques like regression, classification, clustering, and time series analysis. Apply these techniques to different datasets and domains to gain a broader understanding of their strengths, weaknesses, and appropriate use cases.

4๏ธโƒฃ Work on projects that involve the entire data science lifecycle, from data collection and cleaning to model building, evaluation, and deployment. This will help you understand how different components of the data science process fit together.

5๏ธโƒฃ Consistent practice is key to mastering any skill. Set aside dedicated time to work on data science projects, and gradually increase the complexity and scope of your projects as you gain more experience.
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Forwarded from Artificial Intelligence
๐Ÿณ ๐— ๐˜‚๐˜€๐˜-๐—ž๐—ป๐—ผ๐˜„ ๐—ฆ๐—ค๐—Ÿ ๐—–๐—ผ๐—ป๐—ฐ๐—ฒ๐—ฝ๐˜๐˜€ ๐—˜๐˜ƒ๐—ฒ๐—ฟ๐˜† ๐—”๐˜€๐—ฝ๐—ถ๐—ฟ๐—ถ๐—ป๐—ด ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜€๐˜ ๐—ฆ๐—ต๐—ผ๐˜‚๐—น๐—ฑ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ๐Ÿ˜

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This guide covers 7 key SQL concepts that every beginner must learnโœ…๏ธ
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How HTTPS Works
โค3๐Ÿ‘1
๐—”๐—ฐ๐—ฒ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—ฆ๐—ค๐—Ÿ ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐˜„๐—ถ๐˜๐—ต ๐—ง๐—ต๐—ฒ๐˜€๐—ฒ ๐Ÿฏ๐Ÿฌ ๐— ๐—ผ๐˜€๐˜-๐—”๐˜€๐—ธ๐—ฒ๐—ฑ ๐—ค๐˜‚๐—ฒ๐˜€๐˜๐—ถ๐—ผ๐—ป๐˜€! ๐Ÿ˜

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Rest vs GraphQL
โค1
Types of API โœ…
โค1๐Ÿ‘1
9 Types of API Testing
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๐Ÿฒ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—™๐˜‚๐—น๐—น ๐—ง๐—ฒ๐—ฐ๐—ต ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐—ฌ๐—ผ๐˜‚ ๐—–๐—ฎ๐—ป ๐—ช๐—ฎ๐˜๐—ฐ๐—ต ๐—ฅ๐—ถ๐—ด๐—ต๐˜ ๐—ก๐—ผ๐˜„๐Ÿ˜

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Save this list and start crushing your tech goals today!โœ…๏ธ
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