اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources
رفتن به کانال در Telegram
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
نمایش بیشتر📈 تحلیل کانال تلگرام Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources
کانال Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources (@sqlproject) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 39 505 مشترک است و جایگاه 4 747 را در دسته آموزش و رتبه 10 383 را در منطقه الهند دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 39 505 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 11 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 205 و در ۲۴ ساعت گذشته برابر 11 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 2.87% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 0.98% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 1 133 بازدید دریافت میکند. در اولین روز معمولاً 388 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 3 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند analytic, dataset, visualization, sql, learning تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“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”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 12 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.
39 505
مشترکین
+1124 ساعت
+367 روز
+20530 روز
آرشیو پست ها
Day 1 Advanced Data Cleaning.pdf3.78 KB
Data Cleaning.pdf3.92 MB
Sales Data Analysis.pdf5.58 KB
XGboost.pdf4.03 MB
Machine Learning
S. Sridhar, 2021
D Mart Products sales Analysis project 🏪.pdf3.51 MB
Count number of Faces using
Python – OpenCV 🧠🚀
Don't forget to React ❤️ to this msg if you want more content Like this 👍
20 high-income skills to learn in
2024 👇
1. Artificial intelligence (AI)
2. Cloud computing
3. Data science
4. Machine learning
5. Blockchain/ Crypto
6. Data analytics and business intelligence
7. Data engineering
8. Finance
9. Web Development
10. Software development
11. UX design
12. Web design
13. Graphic design
14. Video editing
15. Content marketing
16. Blogging
17. Tech skills
18. Business analysis
19. Cybersecurity
20. Entrepreneurship
21. Freelancing
22. Sales and marketing
Free access to all the Paid Channels
👇👇
https://t.me/addlist/ID95piZJZa0wYzk5
Do react with ♥️ if you need more content like this
ENJOY LEARNING 👍👍
House Price Prediction Models.pdf1.25 MB
Are you a data science beginner?
Here are 5 beginner-friendly data science project ideas
Loan Approval Prediction
Predict whether a loan will be approved based on customer demographic and financial data. This requires data preprocessing, feature engineering, and binary classification techniques.
Credit Card Fraud Detection
Detect fraudulent credit card transactions with a dataset that contains transactions made by credit cards. This is a good project for learning about imbalanced datasets and anomaly detection methods.
Netflix Movies and TV Shows Analysis
Analyze Netflix's movies and TV shows to discover trends in ratings, popularity, and genre distributions. Visualization tools and exploratory data analysis are key components here.
Sentiment Analysis of Tweets
Analyze the sentiment of tweets to determine whether they are positive, negative, or neutral. This project involves natural language processing and working with text data.
Weather Data Analysis
Analyze historical weather data from the National Oceanic and Atmospheric Administration (NOAA) to look for seasonal trends, weather anomalies, or climate change indicators. This project involves time series analysis and data visualization.
Join for more: https://t.me/sqlproject
ENJOY LEARNING 👍👍
5 Best beginner-friendly data science projects!
1-Loan Approval Prediction
2-Credit Card Fraud Detection
3-Netflix Movies and TV Shows Analysis
4-Sentiment Analysis of Tweets 5-Weather Data Analysis
These projects are ideal for beginners who want to grasp the fundamentals and get closer to solving real-life projects.
How to choose the right portfolio project?
Here are my best tips:
Pick What You Like: Choose a topic you enjoy to keep the project fun.
Show Your Skills: Make sure your project shows off what you can do, like organizing data or making charts.
Keep It Simple: Start with a simple project that you can expand later.
Use Available Data: Choose a project with easy-to-find data.
Underrated Telegram Channel for Data Analysts 👇👇
https://t.me/sqlspecialist
Here, you will get free tutorials to learn SQL, Python, Power BI, Excel and many more
Hope you guys will like it 😄
Credit_Risk_Analysis.pdf1.29 MB
“The Best Public Datasets for Machine Learning and Data Science” by Stacy Stanford
https://datasimplifier.com/best-data-analyst-projects-for-freshers/
https://toolbox.google.com/datasetsearch
https://www.kaggle.com/datasets
http://mlr.cs.umass.edu/ml/
https://www.visualdata.io/
https://guides.library.cmu.edu/machine-learning/datasets
https://www.data.gov/
https://nces.ed.gov/
https://www.ukdataservice.ac.uk/
https://datausa.io/
https://www.cs.toronto.edu/~delve/data/boston/bostonDetail.html
https://www.kaggle.com/xiuchengwang/python-dataset-download
https://www.quandl.com/
https://data.worldbank.org/
https://www.imf.org/en/Data
https://markets.ft.com/data/
https://trends.google.com/trends/?q=google&ctab=0&geo=all&date=all&sort=0
https://www.aeaweb.org/resources/data/us-macro-regional
http://xviewdataset.org/#dataset
http://labelme.csail.mit.edu/Release3.0/browserTools/php/dataset.php
http://image-net.org/
http://cocodataset.org/
http://visualgenome.org/
https://ai.googleblog.com/2016/09/introducing-open-images-dataset.html?m=1
http://vis-www.cs.umass.edu/lfw/
http://vision.stanford.edu/aditya86/ImageNetDogs/
http://web.mit.edu/torralba/www/indoor.html
http://www.cs.jhu.edu/~mdredze/datasets/sentiment/
http://ai.stanford.edu/~amaas/data/sentiment/
http://nlp.stanford.edu/sentiment/code.html
http://help.sentiment140.com/for-students/
https://www.kaggle.com/crowdflower/twitter-airline-sentiment
https://hotpotqa.github.io/
https://www.cs.cmu.edu/~./enron/
https://snap.stanford.edu/data/web-Amazon.html
https://aws.amazon.com/datasets/google-books-ngrams/
http://u.cs.biu.ac.il/~koppel/BlogCorpus.htm
https://code.google.com/archive/p/wiki-links/downloads
http://www.dt.fee.unicamp.br/~tiago/smsspamcollection/
https://www.yelp.com/dataset
https://t.me/DataPortfolio/2
https://archive.ics.uci.edu/ml/datasets/Spambase
https://bdd-data.berkeley.edu/
http://apolloscape.auto/
https://archive.org/details/comma-dataset
https://www.cityscapes-dataset.com/
http://aplicaciones.cimat.mx/Personal/jbhayet/ccsad-dataset
http://www.vision.ee.ethz.ch/~timofter/traffic_signs/
http://cvrr.ucsd.edu/LISA/datasets.html
https://hci.iwr.uni-heidelberg.de/node/6132
http://www.lara.prd.fr/benchmarks/trafficlightsrecognition
http://computing.wpi.edu/dataset.html
https://mimic.physionet.org/
✅ Free Courses with Certificate:
https://t.me/free4unow_backup
🖥 Fake news Detection Machine Learning Project with 92%Accuracy
✅ it contain compressed file in which "jupyter notebook file and dataset" ✅
Learning MongoDB
Stack Overflow
In 2024, mastering data science is expected to blend conventional educational methods with innovative approaches.
Here are the steps to learn data science in 2024:
Enroll in a data science program: Whether it's at a university or through online platforms, find a program covering machine learning, statistics, and data visualization.
Take online courses: Utilize platforms like Udacity, Udemy, or DataCamp to learn specific data science skills.
Engage in data science competitions: Join competitions on platforms like Kaggle to apply your skills to real-world problems and learn from others.
Connect with data science communities: Participate in forums, attend meetups, or join social media groups to network and learn from experienced data scientists.
Keep up with industry trends: Stay informed about the latest developments in data science by following blogs, podcasts, and industry publications.
Build a portfolio: Create projects to showcase your data science abilities and demonstrate your skills to potential employers or clients.
Happy learning! 👍👍
Share your responses to this 👍❤️
Graph Data Science For Dummies Book.pdf4.66 MB
Data Lake vs Data Warehouse
How to chose statistical test based on data
