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Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources
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Covering all technical and popular stuff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former. Ads/ Promo: @love_data
Больше📈 Аналитический обзор Telegram-канала Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources
Канал Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources (@sqlproject) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 39 497 подписчиков, занимая 4 747 место в категории Образование и 10 383 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 39 497 подписчиков.
Согласно последним данным от 10 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 198, а за последние 24 часа — 3, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 2.80%. В первые 24 часа после публикации контент обычно набирает 1.00% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 1 107 просмотров. В течение первых суток публикация набирает 393 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 3.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как analytic, dataset, visualization, sql, learning.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“Covering all technical and popular stuff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former.
Ads/ Promo: @love_data”
Благодаря высокой частоте обновлений (последние данные получены 11 июня, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Образование.
39 497
Подписчики
+324 часа
+377 дней
+19830 день
Архив постов
Please go through this top 5 SQL projects with Datasets that you can practice and can add in your resume
🚀1. Web Analytics:
(https://www.kaggle.com/zynicide/wine-reviews)
🚀2. Healthcare Data Analysis:
(https://www.kaggle.com/cdc/mortality)
📌3. E-commerce Analysis:
(https://www.kaggle.com/olistbr/brazilian-ecommerce)
🚀4. Inventory Management:
(https://www.kaggle.com/code/govindji/inventory-management)
🚀 5. Analysis of Sales Data:
(https://www.kaggle.com/kyanyoga/sample-sales-data)
Small suggestion from my side for non tech students: kindly pick those datasets which you like the subject in general, that way you will be more excited to practice it, instead of just doing it for the sake of resume, you will learn SQL more passionately, since it’s a programming language try to make it more exciting for yourself.
Hope this piece of information helps you
Join for more -> https://t.me/dataportfolio
ENJOY LEARNING 👍👍
How to enter into Data Science
👉Start with the basics: Learn programming languages like Python and R to master data analysis and machine learning techniques. Familiarize yourself with tools such as TensorFlow, sci-kit-learn, and Tableau to build a strong foundation.
👉Choose your target field: From healthcare to finance, marketing, and more, data scientists play a pivotal role in extracting valuable insights from data. You should choose which field you want to become a data scientist in and start learning more about it.
👉Build a portfolio: Start building small projects and add them to your portfolio. This will help you build credibility and showcase your skills.
Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624
Credits: https://t.me/datasciencefun
Like if you need similar content 😄👍
Hope this helps you 😊
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Want to Become a Business Analyst?
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Link: https://link.guvi.in/SQLspecialist01398
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Practical Python and OpenCV.pdf8.40 MB
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🚀 Free Webinar Series: "To Become a Successfull Data scientist"
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AI Journey 2024: Glimpse into AI-Driven Future
The AI Journey International Conference on Artificial Intelligence and Machine Learning once again brought together developers, scientists, and AI enthusiasts. With 200 speakers from more than ten countries, including China, India, UAE, Indonesia, and Iran, the conference glimpsed an AI-enriched future.
AI Journey was held in Moscow on December 11–13, with each day highlighting a different track: Society, Business and Science.
On December 11, the focus was on Society, where BRICS experts, business and government representatives discussed the key role of technologies and AI as a means to address social issues. Attendees gained insights into various AI-related success stories and how AI supports the sustainable development of the planet.
December 12 was dedicated to Business. This track featured leading experts such as Jaspreet Bindra, Dr. Aisha Bin Bishr, Janet Sawari, Karuna Gopal, and Hammam Riza, who elaborated on real-world implementation of AI in business, and how business and industry can benefit from it.
December 13 was all about Science. Sessions featured international researchers sharing insights into the latest AI technology and the AI’s impact on research and science in general. Swagatam Das, Vladimir Spokoiny, Dedi Darwis, Gonzalo Ferrer, and other international experts delved into the latest scientific advances ranging from generative models and quantum technologies to cybersecurity, educational tools and medicine. Speakers from Sber, Moscow Institute of Physics and Technology, Innopolis University and others shared how AI is transforming learning, development, reading, and art in everyday life. The Science Day also immersed all AI newbies in the world of artificial intelligence with a special AIJ Junior track.
The AI Journey hosted the awards ceremony for the finalists of the AI Challenge for young data scientists and the AIJ Contest for experienced AI professionals.
Watch the recording. Be up to date with the top AI news!
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One of the most effective ways to learn machine learning is by getting hands-on experience and building something yourself.
While finding inspiration can be challenging, exploring projects by others can open your eyes to the endless possibilities. 💡
The projects I am sharing are perfect for those new to machine learning and curious about its potential.
Hello friends,
I hope you all are very well, see many of you are messaging me about the roadmap and career of Python, Java, Power BI, SQL, message everyone one by one for me, so I created a WhatsApp group where you get all this, I give the link below, you can join it from here 👇
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AI/ML (Daily Schedule) 👨🏻💻
Morning:
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- 10:30 AM - 11:00 AM: Break
- 11:00 AM - 12:30 PM: AI/ML Theory Study
Lunch:
- 12:30 PM - 1:30 PM: Lunch and Rest
Afternoon:
- 1:30 PM - 3:00 PM: Project Development
- 3:00 PM - 3:30 PM: Break
- 3:30 PM - 5:00 PM: Model Training/Testing
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- 5:00 PM - 6:00 PM: Review and Debug
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Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624
ENJOY LEARNING 👍👍
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Stock Market Price prediction using Regression.pdf1.16 MB
