Modern Ekalavya Learning Technique 2 — Selecting a Learning Path
With an attention span of a fish, we can hastily abandon the course we have selected. It’s not a surprise that just one course would not suffice for learning that skill. We would not require a 4-year bachelor’s degree otherwise.
Many of the MOOC platforms have already started curating individual courses into learning paths. These learning paths help you master the skill in a much more comprehensive manner. I have tried out Lynda’s and Coursera’s learning, and they seem to be good enough to pick any skill. We could even apply those skills immediately after we have completed the learning path. Even Marketing guru in his article talks about the importance of MOOCs not just only for adults but for children too.
Suppose you want to learn Machine Learning. Without a doubt, Andrew Ng’s Machine Learning course is good to start. However, when you register on Coursera, you will notice that it will ask you about your learning goals and suggest you a learning path accordingly. In the learning path I have chosen, there are three courses I need to complete. You can select Python or R Machine Learning paths depending on the skill you want to specialise.
Ekalvya was clear he wanted to become the best archer in the world, and he would not have done it without setting up strict learning path. He stuck to his path no matter what for years together.
In today’s world, the learning paths should not only contain courses with skill you want to learn. You also need to keep yourself updated with where all you can apply this skill you have acquired. For example, if you are want to become a data scientist, you also need to improve your visualisation skills or presentation skills.
Once you have completed a course, you need to apply them. Platforms such as Kaggle or KD nuggets help us with that. May real life problems are put up as competition on these platforms. Also, Kaggle now has Kernels and forking which can help you get started quickly.
Originally published at F X NIKEE.