Free Online Courses

I decided to post some comments about some excellent online courses related to computing and engineering that I’ve started to take during Covid-19 self-quarantine. Literally all of them are available for free on YouTube.


Weighted Finite-State Transducers

📆 Enrollment: March 2020

This is of particular interest for those who are dealing with ASR (speech recognition). Working with Kaldi, for example, one might bump into a HCLG.fst file, which is, in an oversimplified way, the composition of the three main resources for ASR: the lexicon L, the language model G, and the acoustic model H with context-dependency C. Nanyang Technological University’s Lim Zhi Hao provided a 13-video lecture series which gives a nice picture of the theoretical foundations of WFSTs and semirings notation.

Semirings and WFST, 2015

Linux Basics for SysAdmins

📆 Enrollment: Apr 2020

This is a phenomenal overview course on Linux of about 60 videos that as a beginner-intermediate you can really learn a lot from. I work with command line tools for about 8 years and some of the things it provides I haven’t actually even heard about (e.g., the “script” command). Thanks to tutoriaLinux channel by Dave C!

The Linux Basics Course: Beginner SysAdmin, Step by Step, 2014-today

Computer Networking Crash Course

📆 Enrollment: May 2020

This was a fortunate attempt to fill the huge gap from by my undergrad years. This five-hour, single-take course is composed by six modules that provide a solid foundation in computer network. The course is provide by Geek’s Lesson channel, and was migrated from Coursera’s original course “IT Support Professional Certificate”. This module is ministered by Victor Escobedo, an engineer at Google.

Computer Networking Complete Course - Beginner to Advanced

Probability and Stochastic Processes

📆 Enrollment: June 2020

This is the best course I’ve found online so far on the topic. University of Calgary’s Professor Geoffrey Messier did a remarkable job on his thorough explanations regarding random variables and random processes in a 14-module, crash-course-like lecture series.

Probability and Stochastic Processes, 2018

Prior knowledge on signals and systems is advised.

Introduction to Probability

📆 Enrollment: July-Aug 2020

It is not a secret that MIT provides most of its in-place courses online via its OpenCourseWare platform. The course on probability ministered by Professor John Tsitsiklis is another gem provided by MIT. I actually found three distinct playlists on YouTube: the original for 6.041 “Probabilistic Systems Analysis and Applied Probability” course; the most up-to-date version, RES-6.012 on “Introduction to Probability”, which was developed specially to be taken as online classes; and the third one, 6.041SC, which contains the very same videos as the original, plus some recitation videos where student TAs solve some exercises in between lectures.

MIT 6.041 (original 2010)
MIT RES-6.012 (edX 2018)
MIT 6.041SC (original 2010 plus examples solved by TAs 2013)

Introduction to Reinforcement Learning

📆 Enrollment: May-Aug 2020


The couse is ministered at University College London by David Silver, DeepMind’s genius.

Prior knowledge on probability and random processes is advised.