Python Projects for beginners

Essential programming language for Android app development 👇👇

1. Java: Java has been the traditional and most widely used programming language for Android app development. It is the official language for Android development and provides a robust set of tools and libraries for building Android apps.

2. Kotlin: Kotlin is a modern, concise, and expressive programming language that has gained popularity among Android developers. It is fully interoperable with Java and offers many features that make Android app development more efficient and less error-prone.

3. C++: While not as commonly used as Java or Kotlin, C++ can be used for developing performance-critical parts of an Android app, such as game engines or graphics-intensive applications.

4. Python: Although not typically used for building full-fledged Android apps, Python can be used for scripting, automation, and data processing tasks in Android development.

5. JavaScript: JavaScript can be used in combination with frameworks like React Native or NativeScript to build cross-platform mobile apps that run on both Android and iOS devices.

Overall, Java and Kotlin are the most essential programming languages for Android app development, with Kotlin gaining popularity as a more modern and efficient alternative to Java.

Free Resources to learn App Development 👇👇

Developing Android Apps with Kotlin

Udemy

Android Basics in Kotlin

Advanced Android with Kotlin

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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.

Spend $0 to master new skills in 2024:

1. HTML - w3schools.com
2. CSS - css-tricks.com
3. JavaScript - learnjavascript.online
4. React - react-tutorial.app
5. Tailwind - scrimba.com
6. Vue - vueschool.io
7. Python - pythontutorial.net
8. SQL - t.iss.one/sqlanalyst
9. Git - atlassian.com/git/tutorials
10. Power BI - t.iss.one/PowerBI_analyst

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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

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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.iss.one/programming_guide/299

https://www.sqltutorial.org/wp-content/uploads/2016/04/SQL-cheat-sheet.pdf

https://t.iss.one/learndataanalysis/442?single

Java Programming Cheatsheet

https://introcs.cs.princeton.edu/java/11cheatsheet/

PHP and Ruby Cheatsheets

https://t.iss.one/programming_guide/300
https://t.iss.one/programming_guide/301

Pandas in 5 minutes

https://bit.ly/3EZgNgF

Python Cheat sheet

https://t.iss.one/pythondevelopersindia/314

UML Cheat sheet

https://www.guru99.com/uml-cheatsheet-reference-guide.html.

GIT and Machine Learning Cheatsheet

https://t.iss.one/datasciencefun/714?single

Javascript Cheat sheet

https://t.iss.one/programming_guide/623

HTML Cheatsheet

https://web.stanford.edu/group/csp/cs21/htmlcheatsheet.pdf

ENJOY LEARNING 👍👍

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

15 steps to master Python Programming

🚀 7 Tips for Programmers:

1. 📚 Master Basics: Learn data structures, algorithms, and programming fundamentals.

2. 🌐 Stay Updated: Explore new tools and trends in tech.

3. 🧩 Solve Problems: Practice coding on platforms like LeetCode or HackerRank.

4. 💻 Build Projects: Gain real-world experience with personal projects.

5. 🤝 Network: Join communities, attend hackathons, and collaborate.

6. 🔄 Embrace Feedback: Improve through constructive criticism and refactoring.

7. 🛠️ Develop Soft Skills: Sharpen communication, teamwork, and time management.

🔥 Keep learning, keep growing! 🚀

Essential Tools & Programming Languages for Software Developers

👉 Integrated Development Environments (IDEs):
- Visual Studio Code: A lightweight but powerful source code editor that supports various programming languages and extensions.
- IntelliJ IDEA: A popular IDE for Java development, also supporting other languages through plugins.
- Eclipse: Another widely used IDE for Java, with extensive plugin support for other languages.

👉 Version Control Systems:
- Git: A distributed version control system that allows developers to track changes in their codebase, collaborate with others, and manage project history. GitHub, GitLab, and Bitbucket are popular platforms that use Git.

👉 Programming Languages:
- JavaScript: Essential for web development, with frameworks like React, Angular, and Vue.js for front-end development and Node.js for server-side programming.
- Python: Known for its simplicity and versatility, used in web development (Django, Flask), data science (NumPy, Pandas), and automation.
- Java: Widely used for building enterprise-scale applications, Android app development, and backend systems.
- C#: A language developed by Microsoft, primarily used for building Windows applications and games using the Unity engine.
- C++: Known for its performance, used in system/software development, game development, and applications requiring real-time processing.
- Ruby: Known for its simplicity and productivity, often used in web development with the Ruby on Rails framework.

👉 Web Development Frameworks:
- React: A JavaScript library for building user interfaces, particularly single-page applications.
- Angular: A TypeScript-based framework for building dynamic web applications.
- Django: A high-level Python web framework that encourages rapid development and clean, pragmatic design.
- Spring: A comprehensive framework for Java that provides infrastructure support for developing Java applications.

👉 Database Management Systems:
- MySQL: An open-source relational database management system.
- PostgreSQL: An open-source object-relational database system with a strong emphasis on extensibility and standards compliance.
- MongoDB: A NoSQL database that uses a flexible, JSON-like format for storing data.

👉 Containerization and Orchestration:
- Docker: A platform that allows developers to package applications into containers, ensuring consistency across multiple environments.
- Kubernetes: An open-source system for automating deployment, scaling, and management of containerized applications.

👉 Cloud Platforms:
- Amazon Web Services (AWS): A comprehensive cloud platform offering a wide range of services, including computing power, storage, and databases.
- Microsoft Azure: A cloud computing service created by Microsoft for building, testing, deploying, and managing applications.
- Google Cloud Platform (GCP): A suite of cloud computing services provided by Google.

👉 CI/CD Tools:
- Jenkins: An open-source automation server that helps automate the parts of software development related to building, testing, and deploying.
- Travis CI: A continuous integration service used to build and test software projects hosted on GitHub.

👉 Project Management and Collaboration:
- Jira: A tool developed by Atlassian for bug tracking, issue tracking, and project management.
- Trello: A visual tool for organizing tasks and projects into boards.

Programming & Data Analytics Resources: https://t.iss.one/free4unow_backup/796

Best Programming Resources: https://topmate.io/coding/886839

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Age of Programming Languages👨🏻‍💻

🦅 Swift (10 years old) (2014)
🔷 TypeScript (11 years old) (2012)
🚀 Kotlin (12 years old) (2011)
🎯 Dart (13 years old (2011)
🦀 Rust (13 years old) (2010)
🐹 Go (14 years old) (2009)
🎸 C# (23 years old) (2000)
💎 Ruby (28 years old) (1995)
☕ Java (28 years old) (1995)
🌐 JavaScript (28 years old) (1995)
🐘 PHP (29 years old) (1994)
🐍 Python (33 years old) (1991)
🐪 Perl (36 years old) (1987)
🚀 C++ (38 years old) (1985)
📱 Objective-C (39 years old) (1984)
🔍 Prolog (51 years old) (1972)
🗣️ Smalltalk (51 years old) (1972)
🖥️ C (51 years old) (1972)
📝 Pascal (53 years old) (1970)
🎓 BASIC (59 years old) (1964)
💼 COBOL (64 years old) (1959)
🤖 Lisp (65 years old) (1958)
📜 Fortran (66 years old) (1957)