اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
Data Analytics & AI | SQL Interviews | Power BI Resources
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🔓Explore the fascinating world of Data Analytics & Artificial Intelligence 💻 Best AI tools, free resources, and expert advice to land your dream tech job. Admin: @coderfun Buy ads: https://telega.io/c/Data_Visual
نمایش بیشتر📈 تحلیل کانال تلگرام Data Analytics & AI | SQL Interviews | Power BI Resources
کانال Data Analytics & AI | SQL Interviews | Power BI Resources (@data_visual) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 27 215 مشترک است و جایگاه 7 206 را در دسته آموزش و رتبه 15 981 را در منطقه الهند دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 27 215 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 14 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 255 و در ۲۴ ساعت گذشته برابر 26 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 3.99% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 0.72% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 0 بازدید دریافت میکند. در اولین روز معمولاً 197 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 0 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند |--, sql, learning, analytic, visualization تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“🔓Explore the fascinating world of Data Analytics & Artificial Intelligence
💻 Best AI tools, free resources, and expert advice to land your dream tech job.
Admin: @coderfun
Buy ads: https://telega.io/c/Data_Visual”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 15 ژوئن, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته آموزش تبدیل کردهاند.
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𝟰 𝗠𝘂𝘀𝘁-𝗗𝗼 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗯𝘆 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁!😍
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𝗖𝗿𝗮𝗰𝗸 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝘄𝗶𝘁𝗵 𝗧𝗵𝗶𝘀 𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗲 𝗚𝘂𝗶𝗱𝗲!😍
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How to be a Prompt Engineer 101
The shortest and most comprehensive guide
1. start with an explanation
Make a description and character situation at the beginning of the Prompt
Error example:
Please help me read the following code:
{your input here}
Correct example:
Now let's play the role, you are a senior information security engineer, I will give you a piece of code, please help me read the code and point out where there may be security vulnerable.
Text: """
{your input here}
"""
2. Prompt to describe the situation
In the prompt, it is necessary to describe the context, result, length, format and style as much as possible
Error example:
Write a short story for kids
Correct example:
Write a funny soccer story for kids that teaches the kid that persistence is the key for success in the style of Rowling.
3. gives output in the format
If you are doing data analysis, please give the input template of the format
Error example:
Extract house pricing data from the following text.
Text: """
{your text containing pricing data}
"""
Correct example:
Extract house pricing data from the following text.
Desired format: """
House 1 | $1,000,000 | 100 sqm
House 2 | $500,000 | 90 sqm
... (and so on)
"""
Text: """
{your text containing pricing data}
"""
4. Add some example questions and answers
Sometimes adding some question and answer examples can make GPT more intelligent
Correct example:
Extract brand names from the texts below.
Text 1: Finxter and YouTube are tech companies. Google is too.
Brand names 2: Finxter, YouTube, Google
###
Text 2: If you like tech, you'll love Finxter!
Brand names 2: Finxter
###
Text 3: {your text here}
Brand names 3:
The question and answer example is also a standard template example in fine-tune
5. Simplify the sentence and clarify the purpose
Keep your words as short as possible and don't say useless content
Error example:
ChatGPT, write a sales page for my company selling sand in the desert, please write only a few sentences, nothing long and complex
Correct example:
Write a 5-sentence sales page, sell sand in the desert.
6. Good at using introductory words
Error example:
Write a Python function that plots my net worth over 10 years for different inputs on the initial investment and a given ROI
Correct example:
# Python function that plots net worth over 10
# years for different inputs on the initial
# investment and a given ROI
import matplotlib
def plot_net_worth(initial, roi):
𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗠𝗮𝘀𝘁𝗲𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 & 𝗔𝗜!😍
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Data Science & Big Data Analytics ( PDFDrive ).pdf50.31 MB
𝗕𝗼𝗼𝘀𝘁 𝗬𝗼𝘂𝗿 𝗖𝗮𝗿𝗲𝗲𝗿 𝘄𝗶𝘁𝗵 𝗙𝗥𝗘𝗘 𝗚𝗼𝗼𝗴𝗹𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀!😍
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Building Machine Learning Powered Applications (2020)
#ml #en
𝟰 𝗔𝗜 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝘁𝗼 𝗕𝗼𝗼𝘀𝘁 𝗬𝗼𝘂𝗿 𝗖𝗮𝗿𝗲𝗲𝗿 𝗶𝗻 𝗔𝗜 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁!😍
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Repost from Data Science Projects
𝗧𝗼𝗽 𝗠𝗡𝗖𝘀 𝗛𝗶𝗿𝗶𝗻𝗴 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀 & 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 😍
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𝗢𝗿𝗮𝗰𝗹𝗲 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 | 𝗦𝗤𝗟 😍
SQL is a must-have skill for Data Science, Analytics, and Data Engineering roles!
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Repost from Generative AI
Important Generative AI Terms
Repost from Generative AI
𝟱 𝗕𝗲𝘀𝘁 𝗜𝗕𝗠 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍
1)Python for Data Science
2)SQL & Relational Databases
3)Applied Data Science with Python
4)Machine Learning with Python
5)Data Analysis with Python
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How do you start AI and ML ?
Where do you go to learn these skills? What courses are the best?
There’s no best answer🥺. Everyone’s path will be different. Some people learn better with books, others learn better through videos.
What’s more important than how you start is why you start.
Start with why.
Why do you want to learn these skills?
Do you want to make money?
Do you want to build things?
Do you want to make a difference?
Again, no right reason. All are valid in their own way.
Start with why because having a why is more important than how. Having a why means when it gets hard and it will get hard, you’ve got something to turn to. Something to remind you why you started.
Got a why? Good. Time for some hard skills.
I can only recommend what I’ve tried every week new course lauch better than others its difficult to recommend any course
You can completed courses from (in order):
Treehouse / youtube( free) - Introduction to Python
Udacity - Deep Learning & AI Nanodegree
fast.ai - Part 1and Part 2
They’re all world class. I’m a visual learner. I learn better seeing things being done/explained to me on. So all of these courses reflect that.
If you’re an absolute beginner, start with some introductory Python courses and when you’re a bit more confident, move into data science, machine learning and AI.
Join for more: https://t.me/machinelearning_deeplearning
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All the best 👍👍
𝗚𝗼𝗼𝗴𝗹𝗲 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍
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