Top Free Online Computer Science Courses
Written by Sue Gee   
Friday, 06 September 2019

September is widely considered the "back to school month". If you are considering enrolling in an online class the problem is there are so many options to choose from. We've rounded up the top best free courses that we've covered over the past years, all of them still available.

Since they burst across our radar in 2012, MOOCs have become a popular way for developers to keep their skills up to date, fill in gaps in their education and widen their horizons. The 2019 Stack Overflow Survey reported that about 60% of professional developers had taken an online course like a MOOC, a proportion that had risen significantly from the previous year's 49%. Figures from HackerRank's survey showed that MOOC's were used for learning to code by 45% of student developers and 51% of professional developers.

The attraction of MOOCs, a word that was added to the Oxford Online Dictionary in 2013 as:

‘massive open online course’: a course of study made available over the Internet without charge to a very large number of people

is obvious. You can fit in your study time around your job and other commitments but still be part of a group of learners via discussion forums. Even so some MOOCs are more attractive than others, either because of the subject matter or due to the quality of the materials and their presentation. Two measure of popularity have been used. Online Course Report relates "top courses" to the number of enrollments. Even though the number of students enrolled on a free course generally far exceeds the number who actually complete it, the number who sign up can be considered a gauge of the "pull" of the topic being covered and the university behind it.

top100banner

The alternative way to identify top courses is the number of stars awarded by people who submit ratings and reviews - and since it is unusual for people to rate courses they haven't tried the number of ratings - these ratings reflect satisfaction of those who have engaged in them. Class Central's rankings of the Top 100 Online Courses includes only courses that are available for free and the 2019 edition is based on 60,000 user reviews. Admittedly  this is a small proportion of the actual number of participants, given that, according to  Dhawal Shah, who created and maintains Class Central, there are now 13,000 MOOCs from around 1,000 universities. Even so the number of reviews is big enough to provide a meaningful ranking. The annual exercise of selecting the top 50 free online courses was started in 2015 and this year has been expanded to 100. To generate the list, the courses in Class Central were sorted by the Bayesian average of their ratings, then courses had been discontinued or had few reviews were removed. 

Class Central's key findings were: 

  • Coursera is the top course platform with 45 courses, followed by edX (24). 
  • The Top 100 List features courses from 53 universities in 18 countries with the top universities including:

    Massachusetts Institute of Technology (US)
    Stanford University (US)
    University of Michigan (US)

  •  The breakdown by category was: 

Technology (23)
Business (16)
Humanities (16)
Sciences (14 )
Personal Development + Self Improvement (11)
Health & Medicine (10 )
Engineering (5 )
Language Learning (5)

Counting courses we consider relevant to the I Programmer audience, that is ones covering a programming language, coding, computer science, data science, mathematical thinking, electronics and complexity, resulted in a total of 28 courses, all but 6 of them already on I Programmer's radar by virtue of having reported on them or even participating in them - members of the team have completed over a quarter of the MOOCs in table below - and there was also an overlap with the Online Course Report's The 50 Most Popular MOOCs of All Time

Back in 2015, when we covered the first edition of this ranking which is based on the number of enrollments (see Top CS MOOCs By the Numbers) we discovered that half, i.e. 25 of them, were I Programmer-relevant. Given that the range of MOOCs available has widened over time now only 16 of those listed fall within our remit. A total of 11 courses were in both the Top 100 by star-ratings and the Top 50 in terms of numbers and a further 5 courses in OCR's Top 50 list had rankings of 4 stars from Class Central reviewers, one of them which would have been ruled of of the Top 100 for no longer being available for free. While the OCR list only included courses from Coursera, edX and Udacity, Class Central's also extends to Kadenze and Complexity Explorer, plus the University of Helsinki's platform.

So here is the table of Top Free Online Courses for Programming, Computer Science etc, a title which needs to be loosely interpreted to mean the same as "of interest to the I Programmer team and our followers". The ratings in the left-hand colum are the ranking in OCR's Top 50 and the number of stars from Class Central's Top 100. Follow links on the course title for its coverage on our site and the link on the name of the platform (Coursera/edX etc) to jump to its enrollment page. Many of the courses are self paced and you can start them as soon as your enrol. Others have a start date so that cohorts of students go through at the same time. If  when you read this the start date has already passed there's likely to be a new date in the near future.

 

Top Free Online Courses For
Programming, Computer Science
   

Rating
Year

Title
(included in certification
University/
Platform
Next start
2/5
2011
Machine Learning Stanford
Coursera

 Started
 Sept 2 

11/5
2012

Cryptography Stanford
Coursera
 Self paced
12/5
2014

Programming for Everybody with Python (1 of 5 of Specialization) Michigan
Coursera
Self paced
15/5
2012
Model Thinking Michigan
Coursera
 Self paced

16/5
2013

An Introduction to Interactive Programming in Python (Part 1)
(1/7 of Fundamentals of Computing Specialization)

Rice
Coursera

 Self paced
18/5
2012
Divide and Conquer, Sorting and Searching, and Randomized Algorithms (1 of 4 in Algorithms Specialization) Stanford
Coursera
Sept 9 

26/5

2012

Introduction to Computer Science CS50x (Professional Cert Programs) Harvard
edX
 Self paced

31/5
2012

Circuits and Electronics
(1 of 3 in XSeries) 

MIT        edX

Self
paced

35/5
2012
Learn to Program: The Fundamentals Toronto  Self paced
50/-
20
Introduction to Mathematical Thinking Stanford  Self paced
-/5 Gamification

Penn
Coursera

 Self paced
-/5 Introduction to Real-Time Audio Programming in ChucK California Inst Arts
Kadenze
Sept 9 
-/5 Internet History Michigan  Self paced
-/5 Introduction to Complexity Santa Fe Institute
Complexity Explorer
10/01/19
-/5
2013
Functional Programming Principles in Scala (1 of 4 in Specialization)

EPFL
Coursera

Self paced
-/5 Introduction to Dynamical Systems and Chaos

Santa Fe Institute
Complexity Explorer

10/01/19
-/5 Machine Learning for Musicians and Artists

Goldsmiths

Kadenze

09/09/19
-/5 Creative Applications of Deep Learning with TensorFlow  Kadenze

-/5

2018

Elements of AI

Helsinki

Moocfi

Self paced

-/5

2015

Computing in Python I: Fundamentals and Procedural Programming Georgia Tech Dec 23
-/4.5
2015
Intro to Programming with MATLAB Vanderbilt

-/5
2016

Applied Scrum for Project Management
(Prof Cert Program)
Maryland
edX
 self paced
45/4.5
2013
Introduction to Computer Science and Programming Using Python 6.001x (XSeries)

MIT
edX

-/4.5
2015
How to Use Git and GitHub Udacity
-/4.5
2016
Intoduction to HTML5
(1 of 5 Web Design Specialization)
Michigan
Coursera
  Self paced
-/4.5
2016
The Analytics Edge MIT
edX

 Oct 15

-/4.5
2016

Python for Data Science

(Data Science MicroMasters)

UC San Diego/edx  Self paced
-/4.5
2016
Python and Statistics for Financial Analysis

Hong Kong

Coursera

7/-
2012
Algorithms 1 Princeton Started
Sept 2 
10/-
2014
Programming Mobile Applications for Android Handheld Systems: Part 1 Maryland
Coursera
09/09/19

21/-

2012

Game Theory Stanford
Coursera

40/-

2013

Introduction to Artificial Intelligence

Stanford

 

44/-
2013

Data Analysis

(superceded by Specialization)

Johns Hopkins

 

Key points emerging from this include: 

  • Python is the language of choice - in fact no other language is represented 
  • Coursera is the top course platform with 21 courses, followed by edX (6)
  • The top universities are Stanford (6 ), Michigan (4) and MIT (3)
  • The initial crop of MOOCs are well represented with 12 courses dating from 2011-2012  plus the original AI class revised in 2013.

The one free MOOC that bucks the trend of being hosted on a he big platform and having stood the test of time is Elements of AI which dates from 2018 and is based on an introduction to AI taught for some years at the University of Helsinki and intended to make make Finland the world's most educated country in the field of artificial intelligence - in fact as soon as it was available online it attracted a, large, global audience.

Trawling through the I Programmer archive of MOOCs and online training courses hundreds of courses are mentioned - including ones on Java and JavaScript. A small proportion of the ones we've reported in have fallen by the wayside, including one whole platform, the Australian Open2Study. Other courses that we've reported on but are missing from the table have ceased to be free and are now only presented as part of a Coursera Specialization - in which you gain certificates in a linked series of courses, culminating in a Capstone project.

The edX courses in the table now have a free version and a paid-for, value added version as part of an XSeries (similar to a Specialization), MicroMasters (at postgraduate level and can be counted towards a Masters degree) or a Professional Certificate Program, aimed at those already extablished in their careers.

If you are doing an online course to further your career choosing the paid-for option is likely to be well worth it as successful completion will gain you a certificate which are increasingly recognized as valuable.  

 

 

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