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

Сітка:Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert Індія6 505 Технології та додатки2 375...

📈 Аналітичний огляд Telegram-каналу Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books

Канал Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books (@programming_guide) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 56 140 підписників, посідаючи 2 375 місце в категорії Технології та додатки та 6 505 місце у регіоні Індія.

📊 Показники аудиторії та динаміка

З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 56 140 підписників.

За останніми даними від 12 червня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 106, а за останні 24 години на 11, загальне охоплення залишається високим.

Статус верифікації: Не верифікований
Рівень залученості (ER): Середній показник залученості аудиторії становить 2.74%. Протягом перших 24 годин після публікації контент зазвичай збирає 0.87% реакцій від загальної кількості підписників.
Охоплення публікацій: В середньому кожен допис отримує 1 538 переглядів. Протягом першої доби публікація в середньому набирає 486 переглядів.
Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 4.
Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як algorithm, structure, stack, javascript, programming.

📝 Опис та контентна політика

Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“Everything about programming for beginners * Python programming * Java programming * App development * Machine Learning * Data Science Managed by: @love_data”

Завдяки високій частоті оновлень (останні дані отримано 13 червня, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Технології та додатки.

56 140

Підписники

+1124 години

+287 днів

+10630 день

1 538

Перегляди допису

~ 48624 години

~ 69348 годин

2.74%

Коефіцієнт залучення

~ 1

Дописів на день

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Архів дописів

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Software Engineer: C++ C# Java, Python, JavaScript Web Dev: HTML, CSS, JavaScript, NodeJS Game Dev: Unity, Unreal, Java App Dev: Flutter, Objective C, Java, Swift, Kotlin, React Cyber Security: Python, Linux, Networking AI & Data Science - Julia, Haskell

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Useful Cheatsheets for Programmers 👇👇 Data Science Cheatsheet https://github.com/aaronwangy/Data-Science-Cheatsheet SQL Cheatsheet https://learnsql.com/blog/sql-basics-cheat-sheet/ https://t.me/programming_guide/299 https://www.sqltutorial.org/wp-content/uploads/2016/04/SQL-cheat-sheet.pdf https://t.me/learndataanalysis/442?single Java Programming Cheatsheet https://introcs.cs.princeton.edu/java/11cheatsheet/ PHP and Ruby Cheatsheets https://t.me/programming_guide/300 https://t.me/programming_guide/301 Pandas in 5 minutes https://bit.ly/3EZgNgF Python Cheat sheet https://t.me/pythondevelopersindia/314 UML Cheat sheet https://www.guru99.com/uml-cheatsheet-reference-guide.html. GIT and Machine Learning Cheatsheet https://t.me/datasciencefun/714?single Javascript Cheat sheet https://t.me/programming_guide/623 HTML Cheatsheet https://web.stanford.edu/group/csp/cs21/htmlcheatsheet.pdf ENJOY LEARNING 👍👍

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AI Journey 2024: Glimpse into AI-Driven Future The AI Journey International Conference on Artificial Intelligence and Machine Learning will once again bring together developers, scientists, and AI enthusiasts. With 200+ speakers from more than ten countries, including China, India, UAE, Indonesia, and Iran, the conference will glimpse an AI-enriched future. AI Journey will be held in Moscow on December 11–13, with each day highlighting a different track: Society, Business, and Science. On December 11, the focus will be on Society, where BRICS experts, business, and government representatives will discuss the key role of technologies and AI as a means to address social issues. Attendees will gain insights into various AI-related success stories and how AI supports the sustainable development of the planet. December 12 will be dedicated to Business. This track will feature leading experts such as Jaspreet Bindra, Dr. Aisha Bint Butti Bin Bishr, Janet Sawari, Karuna Gopal , and Hammam Riza, who will elaborate on real-world implementation of AI in business, and how business and industry can benefit from it. December 13 will be all about Science. Sessions will feature international researchers sharing insights into the latest AI technology and the AI’s impact on research and science in general. Swagatam Das, Vladimir Spokoiny, Dedi Darwis, Gonzalo Ferrer, and other international experts will delve into the latest scientific advances ranging from generative models and quantum technologies to cybersecurity, educational tools, and medicine. Speakers from Sber, Moscow Institute of Physics and Technology, Innopolis University, and others will share how AI is transforming learning, development, reading, and art in everyday life. The Science Day will also immerse all AI newbies in the world of artificial intelligence with a special AIJ Junior track. The AI Journey will host the awards ceremony for the finalists of the AI Challenge for young data scientists and the AIJ Contest for experienced AI professionals. Join the live broadcast. Be up to date with the top AI news!

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Coding isn't easy! It’s the art of turning ideas into functional, impactful software that shapes the world around us. To truly excel in coding, focus on these key areas: 0. Understanding the Basics: Learn the syntax, variables, loops, and conditionals in your chosen programming language. These are the building blocks of coding. 1. Mastering Data Structures and Algorithms: These are the backbone of efficient, scalable, and optimized code. 2. Learning Debugging Techniques: Understand how to identify and fix errors in your code using tools and logical thinking. 3. Writing Clean Code: Follow best practices like commenting, indentation, and naming conventions to make your code readable and maintainable. 4. Building Real-World Projects: Hands-on experience is essential. Apply what you learn by building applications, games, or automation scripts. 5. Collaborating with Git: Master version control to work effectively in teams and manage your codebase. 6. Exploring Frameworks and Libraries: Learn to use tools that simplify coding and add functionality to your projects. 7. Understanding Problem-Solving: Focus on logical thinking and breaking down problems into smaller, manageable parts. 8. Adapting to New Technologies: Stay curious and keep learning new languages, paradigms, and tools as they emerge. 9. Practicing Consistently: Coding is a skill that improves with regular practice and perseverance. 💡 Embrace the process, learn from your mistakes, and keep pushing your limits to grow as a developer. Best Programming Resources: https://topmate.io/coding/886839 ENJOY LEARNING 👍👍

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⌨️ MongoDB Cheat Sheet

MongoDB is a flexible, document-orientated, NoSQL database program that can scale to any enterprise volume without compromising search performance.

This Post includes a MongoDB cheat sheet to make it easy for our followers to work with MongoDB. Working with databases Working with rows Working with Documents Querying data from documents Modifying data in documents Searching

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Practice projects to consider: 1. Implement a basic search engine: Read a set of documents and build an index of keywords. Then, implement a search function that returns a list of documents that match the query. 2. Build a recommendation system: Read a set of user-item interactions and build a recommendation system that suggests items to users based on their past behavior. 3. Create a data analysis tool: Read a large dataset and implement a tool that performs various analyses, such as calculating summary statistics, visualizing distributions, and identifying patterns and correlations. 4. Implement a graph algorithm: Study a graph algorithm such as Dijkstra's shortest path algorithm, and implement it in Python. Then, test it on real-world graphs to see how it performs.

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