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๐Ÿฐ ๐—™๐—ฅ๐—˜๐—˜ ๐— ๐—ถ๐—ฐ๐—ฟ๐—ผ๐˜€๐—ผ๐—ณ๐˜ & ๐—ฆ๐˜๐—ฎ๐—ป๐—ณ๐—ผ๐—ฟ๐—ฑ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐—ง๐—ต๐—ฎ๐˜ ๐—ช๐—ถ๐—น๐—น ๐—”๐—ฐ๐˜๐˜‚๐—ฎ๐—น๐—น๐˜† ๐—จ๐—ฝ๐—ด๐—ฟ๐—ฎ๐—ฑ๐—ฒ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—ฅ๐—ฒ๐˜€๐˜‚๐—บ๐—ฒ๐Ÿ˜

I failed my first data interview โ€” and hereโ€™s why:โฌ‡๏ธ

โŒ No structured learning
โŒ No real projects
โŒ Just random YouTube tutorials and half-read blogs

If this sounds like you, donโ€™t repeat my mistakeโœจ๏ธ
Recruiters want proof of skills, not just buzzwords๐Ÿ“Š

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All The Best ๐ŸŽŠ
โค2
Forwarded from Artificial Intelligence
๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ถ๐—ป๐—ด ๐—ฆ๐—ค๐—Ÿ ๐—–๐—ฎ๐—ป ๐—•๐—ฒ ๐—™๐˜‚๐—ป! ๐Ÿฐ ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐—ฎ๐—ฐ๐˜๐—ถ๐˜ƒ๐—ฒ ๐—ฃ๐—น๐—ฎ๐˜๐—ณ๐—ผ๐—ฟ๐—บ๐˜€ ๐—ง๐—ต๐—ฎ๐˜ ๐—™๐—ฒ๐—ฒ๐—น ๐—Ÿ๐—ถ๐—ธ๐—ฒ ๐—ฎ ๐—š๐—ฎ๐—บ๐—ฒ๐Ÿ˜

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โค2
This is how data analytics teams work!

Example:
1) Senior Management at Swiggy/Infosys/HDFC/XYZ company needs data-driven insights to solve a critical business challenge.

So, they onboard a data analytics team to provide support.

2) A team from Analytics Team/Consulting Firm/Internal Data Science Division is onboarded.
The team typically consists of a Lead Analyst/Manager and 2-3 Data Analysts/Junior Analysts.

3) This data analytics team (1 manager + 2-3 analysts) is part of a bigger ecosystem that they can rely upon:
- A Senior Data Scientist/Analytics Lead who has industry knowledge and experience solving similar problems.
- Subject Matter Experts (SMEs) from various domains like AI, Machine Learning, or industry-specific fields (e.g., Marketing, Supply Chain, Finance).
- Business Intelligence (BI) Experts and Data Engineers who ensure that the data is well-structured and easy to interpret.
- External Tools & Platforms (e.g., Power BI, Tableau, Google Analytics) that can be leveraged for advanced analytics.
- Data Experts who specialize in various data sources, research, and methods to get the right information.

4) Every member of this ecosystem collaborates to create value for the client:
- The entire team works toward solving the clientโ€™s business problem using data-driven insights.
- The Manager & Analysts may not be industry experts but have access to the right tools and people to bring the expertise required.
- If help is needed from a Data Scientist sitting in New York or a Cloud Engineer in Singapore, itโ€™s availableโ€”collaboration is key!

End of the day:
1) Data analytics teams arenโ€™t just about crunching numbersโ€”theyโ€™re about solving problems using data-driven insights.
2) EVERYONE in this ecosystem plays a vital role and is rewarded well because the value they create helps the business make informed decisions!
3) You should consider working in this field for a few years, at least. Itโ€™ll teach you how to break down complex business problems and solve them with data. And trust me, data-driven decision-making is one of the most powerful skills to have today!

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Hope it helps :)
โค1
๐—™๐—ฅ๐—˜๐—˜ ๐—ง๐—ฒ๐—ฐ๐—ต ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐—ง๐—ผ ๐—œ๐—บ๐—ฝ๐—ฟ๐—ผ๐˜ƒ๐—ฒ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—ฆ๐—ธ๐—ถ๐—น๐—น๐˜€๐—ฒ๐˜ ๐Ÿ˜

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Practice projects to consider:

1. Implement a basic search engine:
Read a set of documents and build an index of keywords. Then, implement a search function that returns a list of documents that match the query.

2. Build a recommendation system: Read a set of user-item interactions and build a recommendation system that suggests items to users based on their past behavior.

3. Create a data analysis tool: Read a large dataset and implement a tool that performs various analyses, such as calculating summary statistics, visualizing distributions, and identifying patterns and correlations.

4. Implement a graph algorithm: Study a graph algorithm such as Dijkstra's shortest path algorithm, and implement it in Python. Then, test it on real-world graphs to see how it performs.
โค2
๐—ง๐—ผ๐—ฝ ๐—–๐—ผ๐—บ๐—ฝ๐—ฎ๐—ป๐—ถ๐—ฒ๐˜€ ๐—ข๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ถ๐—ป๐—ด ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐Ÿ˜

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โค2
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SQL Joins โœ…
โค3
๐—™๐—ฅ๐—˜๐—˜ ๐—ข๐—ป๐—น๐—ถ๐—ป๐—ฒ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐—ง๐—ผ ๐—˜๐—ป๐—ฟ๐—ผ๐—น๐—น ๐—œ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ ๐Ÿ˜

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