Useful Resources for Developers

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📍 Table of Contents

01-Link to Bootcamps, Platforms, Tools etc: Miscellaneous links to Bootcamps, Podcasts, Tools, etc.
- Articles: List of articles on development.
- Bootcamps: List of no upfront fee Coding Bootcamps.
- Podcasts: A range of podcasts covering topics like coding, design, accessibility, JavaScript, and Mindset/Self-Development.
02-How to Contribute to this Repo: Want to contribute to this repo? Check it out to know how!
03-Coding for Kids: Encouraging skills for life.
04-YT Channels for Dev: A list of YouTube channels for learning all about programming, covering topics as broad as web development, design, history, hacking, and Computer Science (CS).
05-Best Free Courses: All top learning courses for free.
06-Hackathons, Events & Competitions: Details of all top Hackathons organized annually.
**07-Interview Coding: A page of resources about preparing for the job market & how to ace an interview.
08-Internships & Conferences: Details on Research programs, Internships & Conferences.
09-Projects: List of projects on every domain.
10-Student Benefits & Programs: Details on all CA programs, Student benefits & packs, Fellowship programs, Scholarships etc.
11-Open Source Programs: List of all Open-Source & Startup programs.

Domains:

API: A list of resources for learning how to use APIs.
App-Development: A curated list of useful resources for mobile app development (for Android, iOS, Windows, or any other mobile system)
Augmented Reality (AR): A complete list of resources on AR.
Big Data: A list of complete resources on Big Data.
BlockChain: A list of complete resources on BlockChain.
Cheat Sheets: Cheat Sheets on various topics.
Cloud Computing: A list of resources on all cloud computing resources.
Cyber Security: Complete list of resources on Cyber Security, Mobile App Security & Website Security.
DBMS: A complete list of resources on Database Management System.
Data Science & Machine Learning: A complete list of resources on Data Science, Machine Learning, Deep Learning with all Cheat Sheets, Documentations & Research Papers.
Data Structures & Algorithms: A list of complete resources on DSA containing notes, cheat sheets, online platforms, books & pdfs.
Design & UI: A complete list of resources on Design & UI from stock photos, web templates, CSS, frameworks, UI libraries, tools and much more.
Game Development: A page which lists out the resources which helps you go from zero to mastery in game development.
Git and GitHub: Resources page on using Git and GitHub.
Hacking: Complete list of Hacking resources.
IQ Tests And Aptitude Tests: PDFs & list of sites for Aptitude Preparation for placements.
IoT: Detailed explaination on IoT with all resources on getting started & project ideas along with resources on Arduino & RaspberryPi.
Marketing: Deep dive into Digital Marketing with all the resources.
Mathematics: A list of resources on different mathematical topics like Calculus, Mathematical Modelling, Probability and Statistics along with Cheat Sheets.
OOPS & OS: A list of resources on Object Oriented Programming (OOPs) & Operating Systems (OS).
Programming Languages: A list of resources on all the programming languages like Arduino, C, C++, C#, Python, Java, JavaScript, HTML, CSS, PHP, SQL, etc. along with Books & Practice Resources on it.
- 01.Books
- 02.Practice Resources
Robotics: A list of resources on Robotics & ROS.
Search Engine Optimization: A list of resources for learning Search Engine Optimization(SEO).
Unix: Resources for Unix systems (Linux, MacOS, etc.).
Web-Development: A page with all free resources for learning web-automation, web-design, web-dev, web-performance, web-working and coding in general.

⚡ Contributing

You are always welcome to contribute to this project, kindly visit our Contributor's Guide before opening a pull request.
First time contributing to open source? Awesome! Read more about the process in Contributing to GitHub.
List of Contributors: A page showing the GitHub usernames of all who have contributed to this open-source project! Make sure to add yourself and submit a pull request if you've contributed.

🔗 Connect with Us

Comments

Can I add my 100 Python Challenges Directory?

This directory contains 100 Python challenges from very basic questions to intermediate level. This will help any beginner to check their knowledge while learning python and also it contains solutions of every challenge.

Also if you approved this then let me know can I add this resource in Resources/Programming Languages/Python/ or any other directory.

opened by kishanrajput23 2
Don't spam discords

Either the main Dev or someone else is spamming discords with links to this on every channel. Frankly that's going to make me actively discourage people to use this repo. Please don't spam.

opened by driscoll42 1
Added 50 JavaScript Challenges

Added 50 different JavaScript Challenges from basic to intermediate level in Resources/Programming Languages/JavaScript/Theory/50_Days_Of_JS Directory.

It contains detailed questions with example and use testcases for checking.

opened by kishanrajput23 0
100 Python Exercises from Basic to Advanced Level

Added one another python course material which contain 100 different types of questions from very basics to advanced level questions with complete explanation and solutions.

This course will challenge a beginner to test their python knowledge while learning and also where he/she is lagging.

opened by kishanrajput23 0
adding cmu's course

Course summary is as follows

This course provides a place for students to practice the necessary mathematical background for further study in machine learning — particularly for taking 10-601 and 10-701. Topics covered include probability, linear algebra (inner product spaces, linear operators), multivariate differential calculus, optimization, and likelihood functions. The course assumes some background in each of the above but will review and give practice in each. Some coding will be required: the course will provide practice with translating the above mathematical concepts into concrete programs.

opened by jaswinder9051998 0
adding cmu's course

Course summary is as follows

This course provides a place for students to practice the necessary mathematical background for further study in machine learning — particularly for taking 10-601 and 10-701. Topics covered include probability, linear algebra (inner product spaces, linear operators), multivariate differential calculus, optimization, and likelihood functions. The course assumes some background in each of the above but will review and give practice in each. Some coding will be required: the course will provide practice with translating the above mathematical concepts into concrete programs.

opened by jaswinder9051998 2