Python Projects & Free Books
前往频道在 Telegram
📈 Telegram 频道 Python Projects & Free Books 的分析概览
频道 Python Projects & Free Books (@pythonfreebootcamp) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 40 801 名订阅者,在 技术与应用 类别中位列第 3 179,并在 印度 地区排名第 9 475 位。
📊 受众指标与增长动态
自 невідомо 创建以来,项目保持高速增长,吸引了 40 801 名订阅者。
根据 27 八月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 -59,过去 24 小时变化为 -12,整体触达仍然可观。
- 认证状态: 未认证
- 互动率 (ER): 平均受众互动率为 3.31%。内容发布后 24 小时内通常能获得 N/A% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 1 352 次浏览,首日通常累积 0 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 1。
- 主题关注点: 内容集中在 learning, analyst, framework, link:-, structure 等核心主题上。
📝 描述与内容策略
作者将该频道定位为表达主观观点的平台:
“Python Interview Projects & Free Courses
Admin: @Coderfun”
凭借高频更新(最新数据采集于 28 八月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 技术与应用 类别中的关键影响点。
40 801
订阅者
-1224 小时
-467 天
-5930 天
帖子存档
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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1️⃣ BCG Data Science & Analytics
2️⃣ TATA Data Visualization Internship
3️⃣ Accenture Data Analytics
4️⃣ PwC Power BI Internship
5️⃣ British Airways Data Science
6️⃣ Quantium Data Analytics
𝐋𝐢𝐧𝐤 👇:-
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Many people pay too much to learn Python, but my mission is to break down barriers. I have shared complete learning series to learn Python from scratch.
Here are the links to the Python series
Complete Python Topics for Data Analyst: https://t.me/sqlspecialist/548
Part-1: https://t.me/sqlspecialist/562
Part-2: https://t.me/sqlspecialist/564
Part-3: https://t.me/sqlspecialist/565
Part-4: https://t.me/sqlspecialist/566
Part-5: https://t.me/sqlspecialist/568
Part-6: https://t.me/sqlspecialist/570
Part-7: https://t.me/sqlspecialist/571
Part-8: https://t.me/sqlspecialist/572
Part-9: https://t.me/sqlspecialist/578
Part-10: https://t.me/sqlspecialist/577
Part-11: https://t.me/sqlspecialist/578
Part-12:
https://t.me/sqlspecialist/581
Part-13: https://t.me/sqlspecialist/583
Part-14: https://t.me/sqlspecialist/584
Part-15: https://t.me/sqlspecialist/585
I saw a lot of big influencers copy pasting my content after removing the credits. It's absolutely fine for me as more people are getting free education because of my content.
But I will really appreciate if you share credits for the time and efforts I put in to create such valuable content. I hope you can understand.
Complete SQL Topics for Data Analysts: https://t.me/sqlspecialist/523
Complete Power BI Topics for Data Analysts: https://t.me/sqlspecialist/588
I'll continue with learning series on Excel & Tableau.
Thanks to all who support our channel and share the content with proper credits. You guys are really amazing.
Hope it helps :)
𝗠𝗮𝘀𝘁𝗲𝗿 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻 – 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲!😍
Want to break into Machine Learning without spending a fortune?💡
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𝐋𝐢𝐧𝐤👇:-
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𝗗𝗲𝗹𝗼𝗶𝘁𝘁𝗲 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽 - 𝗝𝗼𝗶𝗻 𝗡𝗼𝘄😍
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𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/3WWMNLx
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𝗙𝗥𝗘𝗘 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝘀 𝗳𝗿𝗼𝗺 𝗚𝗹𝗼𝗯𝗮𝗹 𝗚𝗶𝗮𝗻𝘁𝘀!😍
Want real-world experience in 𝗖𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆, 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆, 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲, 𝗼𝗿 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜?
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/4hZlkAW
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1)Business Analysis – Foundation
2)Business Analysis Fundamentals
3)The Essentials of Business & Risk Analysis
4)Master Microsoft Power BI
𝗟𝗶𝗻𝗸 👇:-
https://pdlink.in/4hHxBdW
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Here is the list of few projects (found on kaggle). They cover Basics of Python, Advanced Statistics, Supervised Learning (Regression and Classification problems) & Data Science
Please also check the discussions and notebook submissions for different approaches and solution after you tried yourself.
1. Basic python and statistics
Pima Indians :- https://www.kaggle.com/uciml/pima-indians-diabetes-database
Cardio Goodness fit :- https://www.kaggle.com/saurav9786/cardiogoodfitness
Automobile :- https://www.kaggle.com/toramky/automobile-dataset
2. Advanced Statistics
Game of Thrones:-https://www.kaggle.com/mylesoneill/game-of-thrones
World University Ranking:-https://www.kaggle.com/mylesoneill/world-university-rankings
IMDB Movie Dataset:- https://www.kaggle.com/carolzhangdc/imdb-5000-movie-dataset
3. Supervised Learning
a) Regression Problems
How much did it rain :- https://www.kaggle.com/c/how-much-did-it-rain-ii/overview
Inventory Demand:- https://www.kaggle.com/c/grupo-bimbo-inventory-demand
Property Inspection predictiion:- https://www.kaggle.com/c/liberty-mutual-group-property-inspection-prediction
Restaurant Revenue prediction:- https://www.kaggle.com/c/restaurant-revenue-prediction/data
IMDB Box office Prediction:-https://www.kaggle.com/c/tmdb-box-office-prediction/overview
b) Classification problems
Employee Access challenge :- https://www.kaggle.com/c/amazon-employee-access-challenge/overview
Titanic :- https://www.kaggle.com/c/titanic
San Francisco crime:- https://www.kaggle.com/c/sf-crime
Customer satisfcation:-https://www.kaggle.com/c/santander-customer-satisfaction
Trip type classification:- https://www.kaggle.com/c/walmart-recruiting-trip-type-classification
Categorize cusine:- https://www.kaggle.com/c/whats-cooking
4. Some helpful Data science projects for beginners
https://www.kaggle.com/c/house-prices-advanced-regression-techniques
https://www.kaggle.com/c/digit-recognizer
https://www.kaggle.com/c/titanic
5. Intermediate Level Data science Projects
Black Friday Data : https://www.kaggle.com/sdolezel/black-friday
Human Activity Recognition Data : https://www.kaggle.com/uciml/human-activity-recognition-with-smartphones
Trip History Data : https://www.kaggle.com/pronto/cycle-share-dataset
Million Song Data : https://www.kaggle.com/c/msdchallenge
Census Income Data : https://www.kaggle.com/c/census-income/data
Movie Lens Data : https://www.kaggle.com/grouplens/movielens-20m-dataset
Twitter Classification Data : https://www.kaggle.com/c/twitter-sentiment-analysis2
Share with credits: https://t.me/sqlproject
ENJOY LEARNING 👍👍
