Learn in 5 Minutes YouTube Series

Introduction & Objective

Learn in 5 Minutes is a YouTube series consisting of two tracks: algorithms and software engineering.

Every week on Friday @12:00pm EST, one video covering a unique topic. The objectives are:

• Introduce areas of the respective field that are not widely known or understood
• Provide suitable background to have basic familiarity with the topic
• Spark interest in new areas and share an appreciation of mathematics, computer science and software engineering :)

Playlist Links

• Algorithm Series
• Software Engineering Series

Video Links

Algorithms	Software Engineering
Fast Exponentiation	Localhost vs 0.0.0.0
Fast GCD Computation	Linux Signaling
Fast Primality Testing	HTTP Status Codes
Fast Euler Phi Function	HTTP Request Methods
Fast Modular Multiplicative Inverse	HTTP Versions
Fast Modular Combination Functions	HTTP Headers
Image Scaling (Part 1)	HTTP CORS
Image Scaling (Part 2)	HTTP/2
Image Blurring	HTTP/2 HPACK
Image Edge Detection	HTTP/3
Rating Systems	HTTP/3 QPACK
Lossless Compression	HTTP Cookies
LZ77 Compression	JSON Web Tokens (JWT)
Decision Trees	Single-Leader Replication
Locality Sensitive Hashing	Multi-Leader Replication
MinHash Nearest Neighbor	Leaderless Replication

Presentation Links

Algorithms	Software Engineering
Fast Exponentiation	Localhost vs 0.0.0.0
Fast GCD Computation	Linux Signaling
Fast Primality Testing	HTTP Status Codes
Fast Euler Phi Function	HTTP Request Methods
Fast Modular Multiplicative Inverse	HTTP Versions
Fast Modular Combination Functions	HTTP Headers
Image Scaling (Part 1)	HTTP CORS
Image Scaling (Part 2)	HTTP/2
Image Blurring	HTTP/2 HPACK
Image Edge Detection	HTTP/3
Rating Systems	HTTP/3 QPACK
Lossless Compression	HTTP Cookies
LZ77 Compression	JSON Web Tokens (JWT)
Decision Trees	Single-Leader Replication
Locality Sensitive Hashing	Multi-Leader Replication
MinHash Nearest Neighbor	Leaderless Replication

Questions or feedback?

Feel free to leave questions as comments in the associated video. If you have any recommendations for topics, please leave an issue on GitHub or comment in one of the videos.