LIST OF 40 WEBSITES TO FIND REMOTE JOBS
1. Linkedin. com
2. Indeed. com
3. Glassdoor. com
4. FlexJobs. com
5. weworkremotely. com
6. Remote. com
7. Upwork. com
8. Freelancer. com
9. Fiverr. com
10. Guru. com
11. Toptal. com
12. AngelList. com
13. Hubstafftalent. com
14. Simplyhired. com
15. Remotive. com
16. Virtualvocations. com
17. workingnomads. com
18. Hired. com
19. cloudpeeps. com
20. taskrabbit. com
21. talent. com
22. Remote OK - remoteok. io
23. DRemote - dremote. io
24. Jooble - jooble. org
25. stackoverflow. com/jobs
26. jobspresso. com
27. onlinejobs. ph
28. simplyhired. com
29. themuse. com
30. skipthedrive. com
31. zirtual. com
32. justremote. com
33. hireable. com
34. remoteworkhub. com
35. jobbatical. com
36. freelancewritinggigs. com
37. contentwritingjobs. com
38. problogger. com/jobs
39. behance. net
40. designhill. com
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Reviving my days of learning integral notations.
I genuinely used to think mathematicians kept adding extra ∫ symbols just to make equations look more intimidating.
But each version actually changes what the mathematics is measuring.
A single integral accumulates values along one dimension.
That could represent:
→ distance traveled
→ velocity over time
→ area under a curve
A double integral extends the same idea across a 2D region.
Now the quantity is distributed over an area or surface.
This shows up in things like:
→ heat over a plate
→ probability density over a region
→ mass spread across a thin sheet
A triple integral pushes the idea into 3D space.
Now you can measure:
→ mass inside an object
→ charge distribution
→ fluid density
→ total energy within a volume
Then the notation changes again.
The small circle added to the integral sign is important.
It means the integration is taken over a closed curve or a closed surface.
That distinction becomes fundamental in vector calculus and physics.
These closed integrals appear throughout:
→ electromagnetism
→ fluid mechanics
→ Maxwell’s equations
→ Gauss’s theorem
→ Stokes’ theorem
At some point, calculus stops feeling like "finding the area under a curve."
It starts becoming a language for describing how matter, energy, and fields behave in space.
And despite how complicated the notation looks, every one of these symbols is built on the same underlying idea:
breaking something continuous into infinitely small pieces, then adding those pieces together.
Save this if you actually want to build with Python in 2026 🐍🚀
Most people learn random tutorials.
Very few learn the actual ecosystem behind real AI apps, automation systems, APIs, dashboards, and machine learning products.
This roadmap shows which Python tools are used for: 📊 Data analysis
🧠 Machine learning
🤖 AI agents
🌐 APIs & web apps
👁️ Computer vision
⚡ Automation
☁️ Deployment
📈 Big data
If you master even half of these tools, you’ll already be ahead of most beginners.
The best part?
Python connects almost every major AI technology together now. 🔥
#python #ai #programming #coding #developer
𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 vs 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿
A lot of beginners think these are almost the same role.
They’re not.
Both work with data.
But the actual work is very different.
𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁:
Focused on insights, dashboards, and business decisions.
Typical work:
• SQL queries
• Power BI / Tableau dashboards
• Ad-hoc analysis
• Reporting
• Presenting findings to stakeholders
You explore data and turn it into business insights.
𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿:
Focused on building the data foundation analysts rely on.
Typical work:
• data modeling
• dbt transformations
• testing
• documentation
• metric definitions
• reusable data layers
• Git + engineering practices
You transform raw data into clean, scalable, trusted datasets.
This role sits between:
Data Engineering ↔ Analytics
𝗦𝗼... 𝘄𝗵𝗶𝗰𝗵 𝗼𝗻𝗲 𝘀𝗵𝗼𝘂𝗹𝗱 𝘆𝗼𝘂 𝗰𝗵𝗼𝗼𝘀𝗲?
You may enjoy Analytics Engineering if you:
⟶ love SQL deeply
⟶ enjoy clean and modular logic
⟶ like building systems
⟶ prefer scalable solutions over one-off dashboards
⟶ are interested in Git, dbt, testing, and modeling
You may enjoy Data Analytics more if you:
⟶ love dashboards and storytelling
⟶ enjoy stakeholder interaction
⟶ like business discussions
⟶ prefer variety and exploration
⟶ don’t enjoy engineering-heavy workflows
𝗧𝗵𝗲 𝘀𝗺𝗮𝗿𝘁𝗲𝘀𝘁 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 𝗻𝗼𝘄?
Don’t think in rigid titles.
Become T-shaped.
Strong analytics fundamentals + engineering skills = powerful combination.
That’s where the industry is moving.
প্রথম আলো ডেইলি স্টার পোড়ানোর জন্য ২০ মিনিট সময় চেয়ে নিচ্ছে সেনাবাহিনী যাতে ভবনের ভেতরের সাংবাদিকদের বের করে দিতে পারে! সেনাবাহিনী হামলাকারীদের বলছে, আমরা আপনাদের সম্মান করি! হামলাকারীরা আবার হাসতে হাসতে বলছে, ঠিক আছে ২০ মিনিট সময় দেয়া হলো।