Computer Science Resources

A list of resources in different fields of Computer Science (in multiple languages).

Content

• Getting Started
• Map of Computer Science
• Map of Mathematics
• Map of Physics
• MIT Courses
• MIT 6.00 Intro to Computer Science & Programming
• MIT 6.0001 Introduction to Computer Science & Programming in Python
• MIT 6.0002 Introduction to Computational Thinking and Data Science
• CS50 Harvard
• Audio/Video Courses from Colleges and Universities
• Everything Computer Science
• Computer Science Roadmap

• Computer Fundamentals
• Algorithms & Data Structures
• Computer Architecture
• Operating Systems
• Mathematics
• Regular Expressions
• Physics
• Signals and Systems
• Information Theory
• Cloud Computing
• Quantum Computing
• Computer Networks
• Computer Graphics
• Virtual Reality

• Programming Languages
• Assembly
• C
• C++
• Python
• Java
• Javascript
• Ruby
• Bash
• Go
• PHP
• Haskell
• R
• Julia
• Elixir

• Artificial Intelligence
• Machine Learning
• Artificial Neural Networks
• Natural Language Processing
• Computer Vision
• Cybernetics & Robotics

• Information Security
• Computer Security
• Web Hacking
• Exploits
• Reverse Engineering
• Social Engineering
• Cryptography

• Databases
• SQL
• NOSQL
• Big Data
• Data Mining

How to Use These Resources

To make the most of this extensive collection of Computer Science resources, here’s how to dive in:

1. Identify Your Area of Interest: Check the various fields such as Programming, AI, Databases, etc., and see which areas pique your interest.
2. Access the Resources: Follow the links to YouTube or GitHub repositories provided above. Each resource offers specialized knowledge.
3. Dive Deeper: Don’t just scratch the surface. Use the resources to engage with hands-on projects, coding exercises, and more.

Analogizing the Learning Process

Think of learning computer science like planting a garden. Each resource is akin to a different seed. If you just toss seeds on concrete, they may never grow. But, if you plant them in prepared soil, ensure they get the right amount of water, sunlight, and care, they can blossom into something meaningful. Similarly, approaching each resource systematically allows you to cultivate your knowledge effectively.

Troubleshooting

If you encounter issues accessing the resources or understanding the content, here are some troubleshooting steps:

• Check Your Internet Connection: Ensure that you have a stable internet connection as most resources are available online.
• Explore Alternative Links: If a link is broken, look for alternative resources or fresh links on the GitHub repository.
• Engage With Communities: If you’re stuck, reach out to online forums or communities focused on computer science for additional help.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.