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Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books

Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books

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Everything about programming for beginners * Python programming * Java programming * App development * Machine Learning * Data Science Managed by: @love_data

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๐Ÿ“ˆ Telegram kanali Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books analitikasi

Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books (@programming_guide) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 56 111 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 2 375-o'rinni va Hindiston mintaqasida 6 527-o'rinni egallagan.

๐Ÿ“Š Auditoriya koโ€˜rsatkichlari va dinamika

ะฝะตะฒั–ะดะพะผะพ sanasidan buyon loyiha tez oโ€˜sib, 56 111 obunachiga ega boโ€˜ldi.

09 Iyun, 2026 dagi oxirgi maโ€™lumotlarga koโ€˜ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 105 ga, soโ€˜nggi 24 soatda esa 12 ga oโ€˜zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya oโ€˜rtacha 2.63% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 0.84% ini tashkil etuvchi reaksiyalarni toโ€˜playdi.
  • Post qamrovi: Har bir post oโ€˜rtacha 1 473 marta koโ€˜riladi; birinchi sutkada odatda 470 ta koโ€˜rish yigโ€˜iladi.
  • Reaksiyalar va oโ€˜zaro taโ€™sir: Auditoriya faol: har bir postga oโ€˜rtacha 3 ta reaksiya keladi.
  • Tematik yoโ€˜nalishlar: Kontent algorithm, structure, stack, javascript, programming kabi asosiy mavzularga jamlangan.

๐Ÿ“ Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida taโ€™riflaydi:
โ€œEverything about programming for beginners * Python programming * Java programming * App development * Machine Learning * Data Science Managed by: @love_dataโ€

Yuqori yangilanish chastotasi (oxirgi maโ€™lumot 10 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli boโ€˜lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim taโ€™sir nuqtasiga aylantirishini koโ€˜rsatadi.

56 111
Obunachilar
+1224 soatlar
+527 kunlar
+10530 kunlar
Postlar arxiv
๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ ๐—ฆ๐—ค๐—Ÿ ๐—ถ๐—ป ๐—๐˜‚๐˜€๐˜ ๐Ÿณ ๐——๐—ฎ๐˜†๐˜€: ๐—ง๐—ต๐—ฒ ๐—จ๐—น๐˜๐—ถ๐—บ๐—ฎ๐˜๐—ฒ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—ฅ๐—ผ๐—ฎ๐—ฑ๐—บ๐—ฎ๐—ฝ ๐˜๐—ผ ๐—š๐—ฒ๐˜ ๐—๐—ผ๐—ฏ-๐—ฅ๐—ฒ๐—ฎ๐—ฑ๐˜†๏ฟฝ
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Oldest Programming Languages Still in Use Today ๐Ÿ•ฐ๏ธ ๐Ÿ“œ Fortran (1957) โ€“ Still used in scientific computing ๐Ÿค– Lisp (1958) โ€“ Powering AI since the start ๐Ÿ’ผ COBOL (1959) โ€“ Running banks & ATMs ๐Ÿ–ฅ C (1972) โ€“ The godfather of modern languages ๐Ÿ—ฃ Prolog (1972) โ€“ Logic programming OG React โค๏ธ For More!

Roadmap to become a Programmer: ๐Ÿ“‚ Learn Programming Fundamentals (Logic, Syntax, Flow) โˆŸ๐Ÿ“‚ Choose a Language (Python / Java / C++) โˆŸ๐Ÿ“‚ Learn Data Structures & Algorithms โˆŸ๐Ÿ“‚ Learn Problem Solving (LeetCode / HackerRank) โˆŸ๐Ÿ“‚ Learn OOPs & Design Patterns โˆŸ๐Ÿ“‚ Learn Version Control (Git & GitHub) โˆŸ๐Ÿ“‚ Learn Debugging & Testing โˆŸ๐Ÿ“‚ Work on Real-World Projects โˆŸ๐Ÿ“‚ Contribute to Open Source โˆŸโœ… Apply for Job / Internship React โค๏ธ for More ๐Ÿ’ก

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Clean code advice for Python: Do not add redundant context. Avoid adding unnecessary data to variable names, especially when
Clean code advice for Python: Do not add redundant context. Avoid adding unnecessary data to variable names, especially when working with classes. Example: This is bad:
class Person:
    def __init__(self, person_first_name, person_last_name, person_age):
        self.person_first_name = person_first_name
        self.person_last_name = person_last_name
        self.person_age = person_age
This is good:
class Person:
    def __init__(self, first_name, last_name, age):
        self.first_name = first_name
        self.last_name = last_name
        self.age = age
๐Ÿ‘‰ @DataScience4

If you want to Excel as a Data Analyst, master these powerful skills: โ€ข SQL Queries โ€“ SELECT, JOINs, GROUP BY, CTEs, Window Functions โ€ข Excel Functions โ€“ VLOOKUP, XLOOKUP, PIVOT TABLES, POWER QUERY โ€ข Data Cleaning โ€“ Handle missing values, duplicates, and inconsistencies โ€ข Python for Data Analysis โ€“ Pandas, NumPy, Matplotlib, Seaborn โ€ข Data Visualization โ€“ Create dashboards in Power BI/Tableau โ€ข Statistical Analysis โ€“ Hypothesis testing, correlation, regression โ€ข ETL Process โ€“ Extract, Transform, Load data efficiently โ€ข Business Acumen โ€“ Understand industry-specific KPIs โ€ข A/B Testing โ€“ Data-driven decision-making โ€ข Storytelling with Data โ€“ Present insights effectively Like it if you need a complete tutorial on all these topics! ๐Ÿ‘โค๏ธ

๐—ง๐—ผ๐—ฝ ๐—ฃ๐˜†๐˜๐—ต๐—ผ๐—ป ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐—ค๐˜‚๐—ฒ๐˜€๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—”๐˜€๐—ธ๐—ฒ๐—ฑ ๐—ฏ๐˜† ๐— ๐—ก๐—–๐˜€๐Ÿ˜ If you can answer these Python questions
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Complete Python Roadmap ๐Ÿ๐Ÿ‘‡ 1. Introduction to Python - Definition - Purpose - Python Installation - Interpreter vs Compiler 2. Basic Python Syntax - Print Statement - Variables and Data Types - Input and Output - Operators 3. Control Flow - Conditional Statements (if, elif, else) - Loops (for, while) - Break and Continue Statements 4. Data Structures - Lists - Tuples - Sets - Dictionaries 5. Functions - Function Definition - Parameters and Return Values - Lambda Functions 6. File Handling - Reading from and Writing to Files - Handling Exceptions 7. Modules and Packages - Importing Modules - Creating Packages 8. Object-Oriented Programming (OOP) - Classes and Objects - Inheritance - Polymorphism - Encapsulation - Abstraction 9. Error Handling - Try, Except Blocks - Custom Exceptions 10. Advanced Data Structures - List Comprehensions - Generators - Collections Module 11. Decorators and Generators - Function Decorators - Generator Functions 12. Working with APIs - Making HTTP Requests - JSON Handling 13. Database Interaction with Python - Connecting to Databases - CRUD Operations 14. Web Development with Flask/Django - Flask/Django Setup - Routing and Templates 15. Asynchronous Programming - Async/Await - Asyncio Library 16. Testing in Python - Unit Testing - Testing Frameworks (e.g., pytest) 17. Pythonic Code - PEP 8 Style Guide - Code Readability 18. Version Control (Git) - Basic Commands - Collaborative Development 19. Data Science Libraries - NumPy - Pandas - Matplotlib 20. Machine Learning Basics - Scikit-Learn - Model Training and Evaluation 21. Web Scraping - BeautifulSoup - Scrapy 22. RESTful API Development - Flask/Django Rest Framework 23. CI/CD Basics - Continuous Integration - Continuous Deployment 24. Deployment - Deploying Python Applications - Hosting Platforms (e.g., Heroku) 25. Security Best Practices - Input Validation - Handling Sensitive Data 26. Code Documentation - Docstrings - Generating Documentation 27. Community and Collaboration - Open Source Contributions - Forums and Conferences Resources to Learn Python: 1. Free Course - https://www.freecodecamp.org/learn/data-analysis-with-python/ 2. Projects - t.me/pythonfreebootcamp/177 - t.me/pythonspecialist/90 3. Books & Notes - https://t.me/dsabooks/99 - https://t.me/dsabooks/101 4. Python Interview Preparation - https://t.me/PythonInterviews - t.me/DataAnalystInterview/63 Join @free4unow_backup for more Python resources. Like this post if you want more content like this ๐Ÿ˜„โค๏ธ ENJOY LEARNING ๐Ÿ‘๐Ÿ‘

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How to Learn Java in 2025 1. Set Clear Goals:    - Define your learning objectives. Do you want to build web applications, mobile apps, or work on enterprise-level software? 2. Choose a Structured Learning Path:    - Follow a structured learning path that covers the fundamentals of Java, object-oriented programming principles, and essential libraries. 3. Start with the Basics:    - Begin with the core concepts of Java, such as variables, data types, operators, and control flow statements. 4. Master Object-Oriented Programming:    - Learn about classes, objects, inheritance, polymorphism, and encapsulation. 5. Explore Java Libraries:    - Familiarize yourself with commonly used Java libraries, such as those for input/output, networking, and data structures. 6. Practice Regularly:    - Write code regularly to reinforce your understanding and identify areas where you need more practice. 7. Leverage Online Resources:    - Utilize online courses, tutorials, and documentation to supplement your learning. 8. Join a Coding Community:    - Engage with online coding communities and forums to ask questions, share knowledge, and collaborate on projects. 9. Build Projects:    - Create simple projects to apply your skills and gain practical experience. 10. Stay Updated with Java Releases:     - Keep up with the latest Java releases and updates to ensure your knowledge remains current. 11. Explore Frameworks and Tools:     - Learn about popular Java frameworks and tools, such as Spring Boot, Maven, and IntelliJ IDEA. 12. Contribute to Open Source Projects:     - Contribute to open source Java projects to gain real-world experience and showcase your skills. 13. Seek Feedback and Mentoring:     - Seek feedback from experienced Java developers and consider mentorship opportunities to accelerate your learning. 14. Prepare for Certifications:     - Consider pursuing Java certifications, such as the Oracle Certified Java Programmer (OCJP), to validate your skills. 15. Network with Java Developers:     - Attend Java meetups, conferences, and online events to connect with other Java developers and learn from their experiences.

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Python - โค๏ธ Javascript - ๐Ÿ˜‚ Java - ๐Ÿ‘
Python - โค๏ธ Javascript - ๐Ÿ˜‚ Java - ๐Ÿ‘

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