If you have ever discussed Cognitive Science with me for extended periods of time, then you’d know that I have often lamented about the need for a 10 year cognitive science “pre-graduate” program. However true it may be that acquiring relevant knowledge from all the different subdisciplines of Cognitive Science – Psychology, Computer Science, Neuroscience, Philosophy, Linguistics, and Anthropology – takes a long amount of time, such a program would be impractical for at least two main reasons:

1. Impracticality of long-term planning: To be employable by mid-20s at the latest requires starting by the age of 14 or 16. No sane person in this age group commits to a program so long, that too, with questionable financial or employment utility, especially in the 21st century.
2. Inclination towards financially-wise choices: It cannot be denied that everyone is trying to find a way or two to earn money by doing activities that aren’t so unpleasurable. In particular, people usually choose undergraduate (or even graduate) programs by the extent of their financial utility they generate. That’s not to say interests have no role. But given two things that look equally enticing in non-monetary terms, one is inclined to choose one that yields them better money.

Time and again, almost all the (senior) researchers I have come across in the field of Cognitive Science over the last 4 years have expressed that mathematical maturity goes a long way in any field of research including Cognitive Science. Interestingly, a related skill concerning programming is also an immensely useful skill in the 21st century in terms of its financial utility. Putting these two together, it seems that it might actually be possible to propose a standard 3- or 4-year undergraduate program that has both utilities (i) financial/employment (ii) research/higher-studies.

As a doctoral student of Cognitive Science, I still lack any background in Linguistics, Neuroscience, or Anthropology. Whatever little I might have gained through occasional exposure is lost through time. So, it’s difficult to judge the below resources by myself. I invite readers to either leave comments below, or on the public post from which you found this page, or email them to me.

By labeling the program as “Computation and Behavioral Sciences”, I have already split the curriculum into two parts. Thus, anyone with a sufficient exposure from these other disciplines of Linguistics, Neuroscience or Anthropology might be able to suggest the appropriate changes to the second part to come up with a corresponding “Computation and XYZ”. In fact, MIT itself has a curriculum focusing on Neuroscience. My own preference for the curriculum comes from my exposure to Cognitive Science at IIT Kanpur and my ongoing PhD at CEU.

The nice thing about the above is even if one drops out by year 1 (semester 2) or year 2 (semester 4), they would already be familiar with numerous topics that are part of the computer science curriculum or its prerequisites. As teachyourselfcs.com says: There are 2 types of software engineer: those who understand computer science well enough to do challenging, innovative work, and those who just get by because they’re familiar with a few high level tools. The courses listed above are motivated for the later kinds of programmers.

One objection to this curriculum can be that this is too heavily focused on Computer Science and Mathematics. The reasons are two-fold: Firstly, because many students opting for Behavioral Science due to a spite with Mathematics. Unfortunately, Mathematics comes back to bite people during their Graduate Studies, if not eventually in life. Secondly, an exposure to Data Structures, Discrete Structures, and Databases serves to provide more examples of “structures that the mind might use for computation”, thus helping the student and the eventual researcher keep an “open mind” once out of college.

With that said, let me now list some resources that may be used for the courses themselves. This is still a work in progress, and is the most time and effort consuming part of this page. Reader discretion is advised for improved suggestions. The audience in mind is a class 12th graduate who may not be good with mathematics; or who may be good with mathematics at the expense of other topics: