Python Programming & AI Resources
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✅ Python Programming Books ✅ Coding Projects ✅ Important Pdfs ✅ Artificial Intelligence Courses ✅ Data Science Notes For promotions: @love_data Buy ads: https://telega.io/c/pythonproz
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Red:📈 Análisis del canal de Telegram Python Programming & AI Resources
El canal Python Programming & AI Resources (@pythonproz) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 13 506 suscriptores, ocupando la posición 9 206 en la categoría Tecnologías y Aplicaciones y el puesto 30 035 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 13 506 suscriptores.
Según los últimos datos del 25 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 124, y en las últimas 24 horas de -6, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 16.31%. Durante las primeras 24 horas tras publicar, el contenido suele obtener N/A% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 2 202 visualizaciones. En el primer día suele acumular 0 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 46.
- Intereses temáticos: El contenido se centra en temas clave como tuple, comprehension, learning, programming, loop.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“✅ Python Programming Books
✅ Coding Projects
✅ Important Pdfs
✅ Artificial Intelligence Courses
✅ Data Science Notes
For promotions: @love_data
Buy ads: https://telega.io/c/pythonproz”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 26 agosto, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
13 506
Suscriptores
-624 horas
-117 días
+12430 días
Archivo de publicaciones
✅ 50 Must-Know Python Concepts for Interviews 🐍📊
📍 Core Concepts
1. Data Types: int, float, str, bool, list, tuple, dict, set
2. Operators: Arithmetic, Comparison, Logical
3. Control Flow: if, elif, else
4. Loops: for, while
5. Functions: def, lambda
6. Variables & Scope
📍 Data Structures
7. Lists: Manipulation, indexing, slicing
8. Tuples: Immutability
9. Dictionaries: Key-value pairs
10. Sets: Unique elements
📍 Object-Oriented Programming (OOP)
11. Classes and Objects
12. Inheritance
13. Polymorphism
14. Encapsulation
📍 File Handling
15. Opening, reading, writing files
16. Context Managers (with statement)
📍 Modules & Packages
17. Importing modules
18. Creating and using packages
19. Popular Libraries: NumPy, Pandas, Matplotlib, Scikit-learn
📍 NumPy
20. Arrays: Creation, indexing, slicing
21. Mathematical Operations
22. Broadcasting
📍 Pandas
23. Series and DataFrames
24. Data Selection, Filtering
25. Grouping and Aggregation
26. Joining and Merging
27. Handling Missing Data
📍 Data Cleaning & Preprocessing
28. Handling Missing Values
29. Outlier Detection and Treatment
30. Data Transformation (scaling, normalization)
📍 Data Visualization
31. Matplotlib: Plots, charts, customizations
32. Seaborn: Statistical visualizations
📍 Machine Learning Basics
33. Supervised Learning
34. Unsupervised Learning
35. Model Evaluation Metrics
36. Cross-Validation
📍 Common ML Algorithms
37. Linear Regression
38. Logistic Regression
39. Decision Trees
40. Random Forests
📍 Advanced Concepts
41. List Comprehensions
42. Generators
43. Decorators
44. Error Handling (try, except)
45. Regular Expressions
📍 Best Practices
46. Code Style (PEP 8)
47. Documentation
48. Testing
49. Version Control (Git)
📍 Real-World Scenarios
50. Data Analysis Projects
💡 Tap ❤️ for more! #python #coding #interview #datascience #machinelearning #programming
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Advanced Python Programming Accelerate your Python programs.pdf8.46 MB
Goldman Sachs Python Interview Questions 🚀
🚀 Master Python interviews like a pro! 📌 Must-know questions for every Data Analyst & Python Developer — save & practice now!
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Difference between list and tuple in python
🔸List is mutable ( you can modify the original list) and it's values are written in sqare brackets [ ]
🔸Tuple is immutable ( you can't modify it) and it's values are written in parentheses ( ) delimited by comma( , )
🔸To convert list to tuple - we use tuple() function
list1 = [1,2,3]
print(tuple(list1)) Output : (1,2,3)
🔸 For single element list
list1 = [1]
print(tuple(list1)) Output : (1, )
▪️a tuple is a tuple because of comma not because of parentheses
How to master Python from scratch🚀
1. Setup and Basics 🏁
- Install Python 🖥️: Download Python and set it up.
- Hello, World! 🌍: Write your first Hello World program.
2. Basic Syntax 📜
- Variables and Data Types 📊: Learn about strings, integers, floats, and booleans.
- Control Structures 🔄: Understand if-else statements, for loops, and while loops.
- Functions 🛠️: Write reusable blocks of code.
3. Data Structures 📂
- Lists 📋: Manage collections of items.
- Dictionaries 📖: Store key-value pairs.
- Tuples 📦: Work with immutable sequences.
- Sets 🔢: Handle collections of unique items.
4. Modules and Packages 📦
- Standard Library 📚: Explore built-in modules.
- Third-Party Packages 🌐: Install and use packages with pip.
5. File Handling 📁
- Read and Write Files 📝
- CSV and JSON 📑
6. Object-Oriented Programming 🧩
- Classes and Objects 🏛️
- Inheritance and Polymorphism 👨👩👧
7. Web Development 🌐
- Flask 🍼: Start with a micro web framework.
- Django 🦄: Dive into a full-fledged web framework.
8. Data Science and Machine Learning 🧠
- NumPy 📊: Numerical operations.
- Pandas 🐼: Data manipulation and analysis.
- Matplotlib 📈 and Seaborn 📊: Data visualization.
- Scikit-learn 🤖: Machine learning.
9. Automation and Scripting 🤖
- Automate Tasks 🛠️: Use Python to automate repetitive tasks.
- APIs 🌐: Interact with web services.
10. Testing and Debugging 🐞
- Unit Testing 🧪: Write tests for your code.
- Debugging 🔍: Learn to debug efficiently.
11. Advanced Topics 🚀
- Concurrency and Parallelism 🕒
- Decorators 🌀 and Generators ⚙️
- Web Scraping 🕸️: Extract data from websites using BeautifulSoup and Scrapy.
12. Practice Projects 💡
- Calculator 🧮
- To-Do List App 📋
- Weather App ☀️
- Personal Blog 📝
13. Community and Collaboration 🤝
- Contribute to Open Source 🌍
- Join Coding Communities 💬
- Participate in Hackathons 🏆
14. Keep Learning and Improving 📈
- Read Books 📖: Like "Automate the Boring Stuff with Python".
- Watch Tutorials 🎥: Follow video courses and tutorials.
- Solve Challenges 🧩: On platforms like LeetCode, HackerRank, and CodeWars.
15. Teach and Share Knowledge 📢
- Write Blogs ✍️
- Create Video Tutorials 📹
- Mentor Others 👨🏫
I have curated the best interview resources to crack Python Interviews 👇👇
https://topmate.io/coding/898340
Hope you'll like it
Like this post if you need more resources like this 👍❤️
Think Python
2nd edition
by Allen B. Downey
O'REILLY 2016
291 pages
