Endi mavjud! Telegram Tadqiqoti 2025 โ yilning asosiy insaytlari 
Python Programming & AI Resources
Kanalga Telegramโda oโtish
โ Python Programming Books โ Coding Projects โ Important Pdfs โ Artificial Intelligence Courses โ Data Science Notes For promotions: @love_data Buy ads: https://telega.io/c/pythonproz
Ko'proq ko'rsatish๐ Telegram kanali Python Programming & AI Resources analitikasi
Python Programming & AI Resources (@pythonproz) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 13 224 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 9 633-o'rinni va Hindiston mintaqasida 31 603-o'rinni egallagan.
๐ Auditoriya koโrsatkichlari va dinamika
ะฝะตะฒัะดะพะผะพ sanasidan buyon loyiha tez oโsib, 13 224 obunachiga ega boโldi.
25 Iyun, 2026 dagi oxirgi maโlumotlarga koโra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 77 ga, soโnggi 24 soatda esa 2 ga oโzgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya oโrtacha 17.02% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 5.43% ini tashkil etuvchi reaksiyalarni toโplaydi.
- Post qamrovi: Har bir post oโrtacha 2 251 marta koโriladi; birinchi sutkada odatda 718 ta koโrish yigโiladi.
- Reaksiyalar va oโzaro taโsir: Auditoriya faol: har bir postga oโrtacha 8 ta reaksiya keladi.
- Tematik yoโnalishlar: Kontent tuple, comprehension, learning, programming, loop kabi asosiy mavzularga jamlangan.
๐ Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida taโriflaydi:
โโ
Python Programming Books
โ
Coding Projects
โ
Important Pdfs
โ
Artificial Intelligence Courses
โ
Data Science Notes
For promotions: @love_data
Buy ads: https://telega.io/c/pythonprozโ
Yuqori yangilanish chastotasi (oxirgi maโlumot 26 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli boโlib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim taโsir nuqtasiga aylantirishini koโrsatadi.
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Muammo bormi? Iltimos, sahifani yangilang yoki bizning qo'llab-quvvatlash boshqaruvchimizga murojaat qiling>.
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Kanal postlari
| 2 | IntermediatePython.pdf | 2 204 |
| 3 | ๐ฃ๐ฟ๐ฒ๐ถ๐บ๐ถ๐ฎ๐น ๐ฃ๐๐๐ต๐ผ๐ป ๐จ๐น๐๐ถ๐บ๐ฎ๐๐ฒ ๐๐๐ถ๐ฑ๐ฒ! ๐๐โจ
๐๐ป๐ฝ๐๐/๐ข๐๐๐ฝ๐๐ ๐๐๐ป๐ฐ๐๐ถ๐ผ๐ป๐ ๐ฅ๐ค
- print()
- input()
- format()
๐๐ฎ๐๐ฎ ๐ง๐๐ฝ๐ฒ ๐๐ผ๐ป๐๐ฒ๐ฟ๐๐ถ๐ผ๐ป ๐๐๐ป๐ฐ๐๐ถ๐ผ๐ป๐ ๐
- int()
- float()
- str()
- bool()
- complex()
- list()
- tuple()
- set()
- dict()
- frozenset()
- bytes()
- bytearray()
- memoryview()
๐ ๐ฎ๐๐ต๐ฒ๐บ๐ฎ๐๐ถ๐ฐ๐ฎ๐น ๐๐๐ป๐ฐ๐๐ถ๐ผ๐ป๐ ๐งฎ๐
- abs()
- pow()
- round()
- divmod()
- sum()
- min()
- max()
๐ฆ๐ฒ๐พ๐๐ฒ๐ป๐ฐ๐ฒ & ๐๐ผ๐น๐น๐ฒ๐ฐ๐๐ถ๐ผ๐ป ๐๐๐ป๐ฐ๐๐ถ๐ผ๐ป๐ ๐๐
- len()
- sorted()
- range()
- zip()
- enumerate()
- reversed()
- all()
- any()
๐ง๐๐ฝ๐ฒ & ๐๐ฑ๐ฒ๐ป๐๐ถ๐๐ ๐๐๐ป๐ฐ๐๐ถ๐ผ๐ป๐ ๐๐
- type()
- id()
- isinstance()
- issubclass()
๐๐ถ๐น๐ฒ ๐๐ฎ๐ป๐ฑ๐น๐ถ๐ป๐ด ๐๐๐ป๐ฐ๐๐ถ๐ผ๐ป๐ ๐๐
- open()
- close()
- read()
- write()
- seek()
- tell()
๐ฆ๐๐ฟ๐ถ๐ป๐ด ๐๐๐ป๐ฐ๐๐ถ๐ผ๐ป๐ ๐ค๐
- ord()
- chr()
- ascii()
- repr()
๐จ๐๐ถ๐น๐ถ๐๐ ๐๐๐ป๐ฐ๐๐ถ๐ผ๐ป๐ ๐ โ๏ธ
- help()
- dir()
- eval()
- exec()
- hash()
๐๐ผ๐ด๐ถ๐ฐ๐ฎ๐น & ๐๐ถ๐ป๐ฎ๐ฟ๐ ๐๐ผ๐ป๐๐ฒ๐ฟ๐๐ถ๐ผ๐ป ๐๐๐ป๐ฐ๐๐ถ๐ผ๐ป๐ ๐ง ๐ข
- bin()
- oct()
- hex()
- bool()
๐ ๐ฒ๐บ๐ผ๐ฟ๐ & ๐ข๐ฏ๐ท๐ฒ๐ฐ๐ ๐๐ฎ๐ป๐ฑ๐น๐ถ๐ป๐ด ๐๐๐ป๐ฐ๐๐ถ๐ผ๐ป๐ ๐พ๐ฆ
- memoryview()
- object()
- callable()
#PythonGuide #PythonFunctions #CodingLife #LearnPython #DevCommunity #PyTips
https://t.me/pythonRe โ
| 2 396 |
| 4 | ๐งฉ Local AI is no longer just a toy project.
In 2026, you can run a practical AI stack on a laptop: small LLMs, local embeddings, RAG, Jupyter/IDE integration, and no token bill.
This post breaks down what is actually usable right now: Qwen, Gemma, Llama, Ollama, Chroma/LanceDB, local RAG, Jupyter AI, hardware limits, and where local video still hurts.
Read the local stack | 1 388 |
| 5 | โ
Python Data Types! ๐โจ
Data types define what kind of value a variable stores in Python.
name = "Python"
age = 25
price = 99.99
is_easy = True
1. String (str):
Used to store text values.
language = "Python"
city = 'Delhi'
โ Written inside quotes "" or ''
โ Used for names, messages, text data
2. Integer (int):
Used to store whole numbers.
age = 25
marks = 95
โ No decimal point
โ Positive or negative numbers allowed
3. Float (float):
Used to store decimal numbers.
price = 99.99
temperature = 36.6
โ Numbers with decimal values
4. Boolean (bool):
Used for True or False values.
is_logged_in = True
is_admin = False
โ Mostly used in conditions and comparisons
5. List (list):
Stores multiple values in one variable.
fruits = ["apple", "banana", "mango"]
โ Ordered collection
โ Can store duplicate values
โ Uses square brackets []
6. Tuple (tuple):
Similar to list but cannot be changed.
colors = ("red", "blue", "green")
โ Immutable unchangeable
โ Uses parentheses ()
7. Set (set):
Stores unique values only.
nums = {1, 2, 3, 3, 4}
print(nums)
โ Output โ {1, 2, 3, 4}
โ Removes duplicates automatically
8. Dictionary (dict):
Stores data in key-value pairs.
student = {
"name": "Alex",
"age": 22
}
โ Uses curly braces {}
โ Access values using keys
9. Check Data Type:
Use type() to check variable type.
name = "Python"
print(type(name))
โ Output โ
10. Type Conversion:
Convert one data type into another.
age = int("25")
price = float("99.5")
โ int() โ Integer
โ float() โ Decimal
โ str() โ String
11. Practice Examples:
โ Add integers
a = 10
b = 20
print(a + b)
โ Print list items
fruits = ["apple", "banana"]
print(fruits)
โ Access dictionary value
student = {"name": "Alex"}
print(student["name"])
๐ก Understanding data types is important because every Python program uses them.
๐ฌ Tap โค๏ธ if this helped you! | 3 340 |
| 6 | Python Beginner Roadmap ๐
๐ Start Here
โ๐ Install Python & VS Code
โ๐ Learn How to Run Python Files
๐ Python Basics
โ๐ Variables & Data Types
โ๐ Input & Output
โ๐ Operators (Arithmetic, Comparison)
โ๐ if, else, elif
โ๐ for & while loops
๐ Data Structures
โ๐ Lists
โ๐ Tuples
โ๐ Sets
โ๐ Dictionaries
๐ Functions
โ๐ Defining & Calling Functions
โ๐ Arguments & Return Values
๐ Basic File Handling
โ๐ Read & Write to Files (.txt)
๐ Practice Projects
โ๐ Calculator
โ๐ Number Guessing Game
โ๐ To-Do List (store in file)
๐ โ
Move to Next Level (Only After Basics)
โ๐ Learn Modules & Libraries
โ๐ Small Real-World Scripts
For detailed explanation, join this channel ๐
https://whatsapp.com/channel/0029Vau5fZECsU9HJFLacm2a
React "โค๏ธ" For More :) | 4 073 |
| 7 |  15 Best Project Ideas for Python : ๐
๐ Beginner Level:
1. Simple Calculator
2. To-Do List
3. Number Guessing Game
4. Dice Rolling Simulator
5. Word Counter
๐ Intermediate Level:
6. Weather App
7. URL Shortener
8. Movie Recommender System
9. Chatbot
10. Image Caption Generator
๐ Advanced Level:
11. Stock Market Analysis
12. Autonomous Drone Control
13. Music Genre Classification
14. Real-Time Object Detection
15. Natural Language Processing (NLP) Sentiment Analysis | 3 740 |
| 8 | Complete roadmap to learn Python and Data Structures & Algorithms (DSA) in 2 months
### Week 1: Introduction to Python
Day 1-2: Basics of Python
- Python setup (installation and IDE setup)
- Basic syntax, variables, and data types
- Operators and expressions
Day 3-4: Control Structures
- Conditional statements (if, elif, else)
- Loops (for, while)
Day 5-6: Functions and Modules
- Function definitions, parameters, and return values
- Built-in functions and importing modules
Day 7: Practice Day
- Solve basic problems on platforms like HackerRank or LeetCode
### Week 2: Advanced Python Concepts
Day 8-9: Data Structures in Python
- Lists, tuples, sets, and dictionaries
- List comprehensions and generator expressions
Day 10-11: Strings and File I/O
- String manipulation and methods
- Reading from and writing to files
Day 12-13: Object-Oriented Programming (OOP)
- Classes and objects
- Inheritance, polymorphism, encapsulation
Day 14: Practice Day
- Solve intermediate problems on coding platforms
### Week 3: Introduction to Data Structures
Day 15-16: Arrays and Linked Lists
- Understanding arrays and their operations
- Singly and doubly linked lists
Day 17-18: Stacks and Queues
- Implementation and applications of stacks
- Implementation and applications of queues
Day 19-20: Recursion
- Basics of recursion and solving problems using recursion
- Recursive vs iterative solutions
Day 21: Practice Day
- Solve problems related to arrays, linked lists, stacks, and queues
### Week 4: Fundamental Algorithms
Day 22-23: Sorting Algorithms
- Bubble sort, selection sort, insertion sort
- Merge sort and quicksort
Day 24-25: Searching Algorithms
- Linear search and binary search
- Applications and complexity analysis
Day 26-27: Hashing
- Hash tables and hash functions
- Collision resolution techniques
Day 28: Practice Day
- Solve problems on sorting, searching, and hashing
### Week 5: Advanced Data Structures
Day 29-30: Trees
- Binary trees, binary search trees (BST)
- Tree traversals (in-order, pre-order, post-order)
Day 31-32: Heaps and Priority Queues
- Understanding heaps (min-heap, max-heap)
- Implementing priority queues using heaps
Day 33-34: Graphs
- Representation of graphs (adjacency matrix, adjacency list)
- Depth-first search (DFS) and breadth-first search (BFS)
Day 35: Practice Day
- Solve problems on trees, heaps, and graphs
### Week 6: Advanced Algorithms
Day 36-37: Dynamic Programming
- Introduction to dynamic programming
- Solving common DP problems (e.g., Fibonacci, knapsack)
Day 38-39: Greedy Algorithms
- Understanding greedy strategy
- Solving problems using greedy algorithms
Day 40-41: Graph Algorithms
- Dijkstraโs algorithm for shortest path
- Kruskalโs and Primโs algorithms for minimum spanning tree
Day 42: Practice Day
- Solve problems on dynamic programming, greedy algorithms, and advanced graph algorithms
### Week 7: Problem Solving and Optimization
Day 43-44: Problem-Solving Techniques
- Backtracking, bit manipulation, and combinatorial problems
Day 45-46: Practice Competitive Programming
- Participate in contests on platforms like Codeforces or CodeChef
Day 47-48: Mock Interviews and Coding Challenges
- Simulate technical interviews
- Focus on time management and optimization
Day 49: Review and Revise
- Go through notes and previously solved problems
- Identify weak areas and work on them
### Week 8: Final Stretch and Project
Day 50-52: Build a Project
- Use your knowledge to build a substantial project in Python involving DSA concepts
Day 53-54: Code Review and Testing
- Refactor your project code
- Write tests for your project
Day 55-56: Final Practice
- Solve problems from previous contests or new challenging problems
Day 57-58: Documentation and Presentation
- Document your project and prepare a presentation or a detailed report
Day 59-60: Reflection and Future Plan
- Reflect on what you've learned
- Plan your next steps (advanced topics, more projects, etc.)
Best DSA RESOURCES: https://topmate.io/coding/886874
Credits: https://t.me/free4unow_backup
ENJOY LEARNING ๐๐ | 0 |
| 9 | Building Chatbots with Python | 0 |
| 10 | Found this - AI Builders, pay attention.
A curated marketplace just launched where AI builders list their systems and get paid - setup fee + monthly recurring. No sales, no client chasing. They handle everything, you just build.
100% free to join. No fees, no subscription, no hidden costs. They only take 20% when you earn - on setup fee and recurring. That's it.
Accepted builders are earning from day one. Spots are limited by design.
Takes 5 minutes to apply. You'll need a 90-second video of your system in action.
โ https://tglink.io/3508aa8711f389
Daily updates from the CEO: https://tglink.io/e2ba74d53c7039
Follow, like & share in "your network" - these guys are building something seriously worth watching.
PS: First systems go live tomorrow. Builders who join early get the best positioning... investor-backed marketing means they bring the clients to you. | 0 |
| 11 | Python Projects for your Data Science Portfolio
โก๏ธ| Data Analysis Portfolio Projects
https://github.com/AlexTheAnalyst/PortfolioProjects
โก๏ธ| Python for Data Analysis (pydata-book)
https://github.com/wesm/pydata-book
โก๏ธ| Data Science Projects
https://github.com/CodeCutTech/Data-science
โก๏ธ| End-to-End ML Projects
https://github.com/GokuMohandas/Made-With-ML
โก๏ธ| Python Project Scripts
https://github.com/hastagAB/Awesome-Python-Scripts
โก๏ธ| Applied ML in Production
https://github.com/eugeneyan/applied-ml
โก๏ธ| Data Engineering Projects (Zoomcamp)
https://github.com/DataTalksClub/data-engineering-zoomcamp
โก๏ธ| Real-Time Data Processing
https://github.com/andkret/Cookbook
โก๏ธ| Plotly Dash Examples
https://github.com/plotly/dash-sample-apps
โก๏ธ| Streamlit Gallery
https://github.com/streamlit/streamlit
โก๏ธ| Web Scraping Projects
https://github.com/NirantK/awesome-project-ideas
โก๏ธ| API Projects
https://github.com/public-apis/public-apis | 0 |
| 12 | ๐ฐ Python Statements | 0 |
| 13 | ๐ฑ Python enthusiasts, this is for you โ 15 BEST REPOSITORIES on GitHub for learning Python
โถ๏ธ Awesome Python โ https://github.com/vinta/awesome-python
โ the largest and most authoritative collection of frameworks, libraries, and resources for Python โ a must-save
โถ๏ธ TheAlgorithms/Python โ https://github.com/TheAlgorithms/Python
โ a huge collection of algorithms and data structures written in Python
โถ๏ธ Project-Based-Learning โ https://github.com/practical-tutorials/project-based-learning
โ learning Python (and not only) through real projects
โถ๏ธ Real Python Guide โ https://github.com/realpython/python-guide
โ a high-quality guide to the Python ecosystem, tools, and best practices
โถ๏ธ Materials from Real Python โ https://github.com/realpython/materials
โ a collection of code and projects for Real Python articles and courses
โถ๏ธ Learn Python โ https://github.com/trekhleb/learn-python
โ a reference with explanations, examples, and exercises
โถ๏ธ Learn Python 3 โ https://github.com/jerry-git/learn-python3
โ a convenient guide to modern Python 3 with tasks
โถ๏ธ Python Reference โ https://github.com/rasbt/python_reference
โ cheat sheets, scripts, and useful tips from one of the most respected Python authors
โถ๏ธ 30-Days-Of-Python โ https://github.com/Asabeneh/30-Days-Of-Python
โ a 30-day challenge: from syntax to more complex topics
โถ๏ธ Python Programming Exercises โ https://github.com/zhiwehu/Python-programming-exercises
โ 100+ Python tasks with answers
โถ๏ธ Coding Problems โ https://github.com/MTrajK/coding-problems
โ tasks on algorithms and data structures, including for preparation for interviews
โถ๏ธ Projects โ https://github.com/karan/Projects
โ a list of ideas for pet projects (not just Python). Great for practice
โถ๏ธ 100-Days-Of-ML-Code โ https://github.com/Avik-Jain/100-Days-Of-ML-Code
โ machine learning in Python in the format of a challenge
โถ๏ธ 30-Seconds-of-Python โ https://github.com/30-seconds/30-seconds-of-python
โ useful snippets and tricks for everyday tasks
โถ๏ธ Geekcomputers/Python โ https://github.com/geekcomputers/Python
โ various scripts: from working with the network to automation tasks
React โฅ๏ธ for more posts like this ๐ | 0 |
| 14 |  ๐ New Edge for Polymarket Traders: Oracle Lag Sniper
A high-performance, open-source strategy repo is making waves right now among serious Polymarket users: the Oracle Lag Sniper.
๐ Why itโs worth your attention:
โข Exploits oracle timing inefficiencies
โข Built for fast execution & precise entries
โข Fully open-source, inspect, modify, and run it yourself
๐ Check out the repo here:
Oracle Lag Sniper GitHub
Want more early signals like this, plus private insights and rising strategies to stay ahead of the curve? Subscribe to Polymarket Analytics for exclusive access:
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๐ Donโt just follow the market, get ahead of it. | 0 |
