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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
Показати більше📈 Аналітичний огляд Telegram-каналу Data Analytics & AI | SQL Interviews | Power BI Resources
Канал Data Analytics & AI | SQL Interviews | Power BI Resources (@data_visual) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 27 215 підписників, посідаючи 7 206 місце в категорії Освіта та 15 981 місце у регіоні Індія.
📊 Показники аудиторії та динаміка
З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 27 215 підписників.
За останніми даними від 14 червня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 255, а за останні 24 години на 26, загальне охоплення залишається високим.
- Статус верифікації: Не верифікований
- Рівень залученості (ER): Середній показник залученості аудиторії становить 3.99%. Протягом перших 24 годин після публікації контент зазвичай збирає 0.72% реакцій від загальної кількості підписників.
- Охоплення публікацій: В середньому кожен допис отримує 0 переглядів. Протягом першої доби публікація в середньому набирає 197 переглядів.
- Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 0.
- Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як |--, sql, learning, analytic, visualization.
📝 Опис та контентна політика
Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“🔓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”
Завдяки високій частоті оновлень (останні дані отримано 15 червня, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Освіта.
27 215
Підписники
+2624 години
+527 днів
+25530 день
Архів дописів
𝟰 𝗠𝘂𝘀𝘁-𝗗𝗼 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗯𝘆 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁!😍
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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):
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Building Machine Learning Powered Applications (2020)
#ml #en
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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 😍
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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.
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All the best 👍👍
𝗚𝗼𝗼𝗴𝗹𝗲 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍
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