Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources
Kanalga Telegramβda oβtish
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
Ko'proq ko'rsatish
Tarmoq:π Telegram kanali Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources analitikasi
Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources (@sqlproject) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 39 600 obunachidan iborat bo'lib, TaΚΌlim toifasida 4 697-o'rinni va Hindiston mintaqasida 9 545-o'rinni egallagan.
π Auditoriya koβrsatkichlari va dinamika
Π½Π΅Π²ΡΠ΄ΠΎΠΌΠΎ sanasidan buyon loyiha tez oβsib, 39 600 obunachiga ega boβldi.
29 Oktabr, 2026 dagi oxirgi maβlumotlarga koβra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -48 ga, soβnggi 24 soatda esa -5 ga oβzgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya oβrtacha 2.24% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 0.70% ini tashkil etuvchi reaksiyalarni toβplaydi.
- Post qamrovi: Har bir post oβrtacha 886 marta koβriladi; birinchi sutkada odatda 276 ta koβrish yigβiladi.
- Reaksiyalar va oβzaro taβsir: Auditoriya faol: har bir postga oβrtacha 3 ta reaksiya keladi.
- Tematik yoβnalishlar: Kontent analytic, dataset, visualization, sql, learning kabi asosiy mavzularga jamlangan.
π Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida taβriflaydi:
βCovering 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_dataβ
Yuqori yangilanish chastotasi (oxirgi maβlumot 30 Oktabr, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli boβlib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni TaΚΌlim toifasidagi muhim taβsir nuqtasiga aylantirishini koβrsatadi.
39 600
Obunachilar
-524 soatlar
-477 kun
-4830 kun
Postlar arxiv
XGboost.pdf4.03 MB
Machine Learning
S. Sridhar, 2021
D Mart Products sales Analysis project πͺ.pdf3.51 MB
Count number of Faces using
Python β OpenCV π§ π
Don't forget to React β€οΈ to this msg if you want more content Like this π
20 high-income skills to learn in
2024 π
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
ππ
https://t.me/addlist/ID95piZJZa0wYzk5
Do react with β₯οΈ if you need more content like this
ENJOY LEARNING ππ
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 ππ
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 ππ
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 π
Credit_Risk_Analysis.pdf1.29 MB
βThe Best Public Datasets for Machine Learning and Data Scienceβ 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/
β
Free Courses with Certificate:
https://t.me/free4unow_backup
π₯ Fake news Detection Machine Learning Project with 92%Accuracy
β
it contain compressed file in which "jupyter notebook file and dataset" β
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! ππ
Share your responses to this πβ€οΈ
Graph Data Science For Dummies Book.pdf4.66 MB
Data Lake vs Data Warehouse
How to chose statistical test based on data
9. Database Design - Part 03.zip675.23 MB
9. Database Design - Part 02.zip745.78 MB
9. Database Design - Part 01.zip823.46 MB
