Skip to main content

Self-Learning is the future of Education

With AI looming in the background as a major threat to traditional jobs worldwide, speedily acquiring skills to build a personal portfolio of knowledge will the major way people learn stuff in the future.
The university curriculum is getting bloated. With new disciplines and sub-disciplines emerging very regularly these days, it is hard to say that what one had learnt in her typical university curriculum will always remain relevant for the foreseeable future.

MOOCs (Massively Open Online Courses) will become a worthy alternative for those who cannot afford a regular university or for those who want to supplement their existing education with extra skills to enable them thrive in an extremely dynamic global economy.

Self-Learning or the art of researching a field of interest and drawing up a personal study plan to tackle the field will become increasingly important to tackle most of the educational deficiencies that will be created as our economy requires people with more fragmented skillsets and our universities being unable to dynamically update the curriculum to fit in with these changes.

So, as a modern student you will have to keep learning for the rest of your career and you can do this outside a formal setting through self-learning. There are thousands of courses to choose from out there and most of them are absolutely free of charge. I have been personally taking advantage of this medium with great success in my life. You just need to decide on what you want to study and check out through a web search of the various aspects of it, and proceed to build your curriculum.

At first be prepared to have a fragmented understanding of the subject, but as you go through all the sub heads that you are not familiar with, you will gradually fill up all that is missing and gradually be on your way to becoming an expert with or without any formal system.


Popular posts from this blog

Next Steps Towards Strong Artificial Intelligence

If you follow current AI Research then it will be apparent to you that AI research, the deep learning type has stalled! This does not mean that new areas of application for existing techniques are not appearing but that the fundamentals have been solved and things have become pretty standardized.

At the edge of a cliff - Quantum Computing

Quantum computing reminds me of the early days of computer development (the 50s - 60s) where we had different companies come up with their different computer architectures. You had to learn how to use one architecture then move to another then another as you hoped to explore different systems that were better for one task than they were for another task.

Software of the future

From the appearance of the first programmable computer, the software has evolved in power and complexity. We went from manually toggling electronic switches to loading punch cards and eventually entering C code on the early PDP computers. Video screens came in and empowered the programmer very much, rather than waiting for printouts to debug our programs, we were directly manipulating code on the screen.