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OrangeShark hiring Data Scientist

Apply link: https://www.linkedin.com/jobs/view/4235056975

👉WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226

👉Telegram Link: https://news.1rj.ru/str/addlist/4q2PYC0pH_VjZDk5

All the best 👍👍
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Forwarded from Python for Data Analysts
𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿’𝘀 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 𝘁𝗼 𝗦𝘄𝗶𝘁𝗰𝗵 𝘁𝗼 𝗮 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗮𝗿𝗲𝗲𝗿 𝗶𝗻 𝟮𝟬𝟮𝟱😍

🔍 Want to Switch to a Data Analytics Career but Don’t Know Where to Start?🎯

You’re not alone! Thousands of students, freshers, and professionals are switching to data analytics roles in 2025 — and with the right plan, you can too🚀

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All The Best 🎊
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𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗧𝗼 𝗘𝗻𝗿𝗼𝗹𝗹 𝗜𝗻 𝟮𝟬𝟮𝟱 😍

Data Analytics :- https://pdlink.in/3Fq7E4p

Data Science :- https://pdlink.in/4iSWjaP

SQL :- https://pdlink.in/3EyjUPt

Python :- https://pdlink.in/4c7hGDL

Web Dev :- https://bit.ly/4ffFnJZ

AI :- https://pdlink.in/4d0SrTG

Enroll For FREE & Get Certified 🎓
𝗙𝗮𝘀𝘁.𝗮𝗶 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗖𝗼𝘂𝗿𝘀𝗲 – 𝗧𝗵𝗲 𝗕𝗲𝘀𝘁 𝗙𝗿𝗲𝗲 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲 𝘁𝗼 𝗦𝘁𝗮𝗿𝘁 𝗬𝗼𝘂𝗿 𝗔𝗜 𝗝𝗼𝘂𝗿𝗻𝗲𝘆😍

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Everyone thinks being a great data analyst is about advanced algorithms and complex dashboards.

But real data excellence comes from methodical habits that build trust and deliver real insights.

Here are 20 signs of a truly effective analyst 👇

They document every step of their analysis
➝ Clear notes make their work reproducible and trustworthy.

They check data quality before the analysis begins
➝ Garbage in = garbage out. Always validate first.

They use version control religiously
➝ Every code change is tracked. Nothing gets lost.

They explore data thoroughly before diving in
➝ Understanding context prevents costly misinterpretations.

They create automated noscripts for repetitive tasks
➝ Efficiency isn’t a luxury—it’s a necessity.

They maintain a reusable code library
➝ Smart analysts never solve the same problem twice.

They test assumptions with multiple validation methods
➝ One test isn’t enough; they triangulate confidence.

They organize project files logically
➝ Their work is navigable by anyone, not just themselves.

They seek peer reviews on critical work
➝ Fresh eyes catch blind spots.

They continuously absorb industry knowledge
➝ Learning never stops. Trends change too quickly.

They prioritize business-impacting projects
➝ Every analysis must drive real decisions.

They explain complex findings simply
➝ Technical brilliance is useless without clarity.

They write readable, well-commented code
➝ Their work is accessible to others, long after they're gone.

They maintain robust backup systems
➝ Data loss is never an option.

They learn from analytical mistakes
➝ Errors become stepping stones, not roadblocks.

They build strong stakeholder relationships
➝ Data is only valuable when people use it.

They break complex projects into manageable chunks
➝ Progress happens through disciplined, incremental work.

They handle sensitive data with proper security
➝ Compliance isn’t optional—it’s foundational.

They create visualizations that tell clear stories
➝ A chart without a narrative is just decoration.

They actively seek evidence against their conclusions
➝ Confirmation bias is their biggest enemy.

The best analysts aren’t the ones with the most tools—they’re the ones with the most rigorous practices.
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𝗧𝗼𝗽 𝗠𝗡𝗖𝘀 𝗢𝗳𝗳𝗲𝗿𝗶𝗻𝗴 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍

Google :- https://pdlink.in/3H2YJX7

Microsoft :- https://pdlink.in/4iq8QlM

Infosys :- https://pdlink.in/4jsHZXf

IBM :- https://pdlink.in/3QyJyqk

Cisco :- https://pdlink.in/4fYr1xO

Enroll For FREE & Get Certified 🎓
𝗙𝗥𝗘𝗘 𝗧𝗔𝗧𝗔 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽😍

Gain Real-World Data Analytics Experience with TATA – 100% Free!

This free TATA Data Analytics Virtual Internship on Forage lets you step into the shoes of a data analyst — no experience required!

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𝗙𝗥𝗘𝗘 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗧𝗲𝗰𝗵 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍

🚀 Learn In-Demand Tech Skills for Free — Certified by Microsoft!

These free Microsoft-certified online courses are perfect for beginners, students, and professionals looking to upskill

𝐋𝐢𝐧𝐤👇:-

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Statistics Interview Questions

Topics to Cover:

• Denoscriptive statistics
• Probability
• Hypothesis testing
• Regression analysis

Questions and Answers:

1 Q: What is the difference between denoscriptive and inferential statistics?

A: Denoscriptive statistics summarize the main features of a dataset (e.g., mean, median, mode), while inferential statistics use samples to make inferences about a larger population.

2 Q: Define p-value in hypothesis testing.

  A: The p-value is the probability of obtaining test results at least as extreme as the observed results, assuming the null hypothesis is true. A low p-value (< 0.05) indicates strong evidence against the null hypothesis.

3 Q: What is the central limit theorem?

  A: The central limit theorem states that the distribution of the sample mean approximates a normal distribution as the sample size becomes large, regardless of the population's distribution.

4 Q: Explain the concept of correlation.

  A: Correlation measures the strength and direction of the relationship between two variables. It ranges from -1 (perfect negative) to +1 (perfect positive), with 0 indicating no correlation.

5 Q: What is linear regression?

  A: Linear regression is a statistical method for modeling the relationship between a dependent variable and one or more independent variables by fitting a linear equation to observed data.

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𝟴 𝗕𝗲𝘀𝘁 𝗙𝗿𝗲𝗲 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗳𝗿𝗼𝗺 𝗛𝗮𝗿𝘃𝗮𝗿𝗱, 𝗠𝗜𝗧 & 𝗦𝘁𝗮𝗻𝗳𝗼𝗿𝗱😍

🎓 Learn Data Science for Free from the World’s Best Universities🚀

Top institutions like Harvard, MIT, and Stanford are offering world-class data science courses online — and they’re 100% free. 🎯📍

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/3Hfpwjc

All The Best 👍
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