Tag: ekalavya

Modern Ekalavya Learning Technique 7 – Retrospective Learning

Modern Ekalavya Learning Technique 7 – Retrospective Learning

Losing track of from your learning objectives is easy.

Nothing can be more frustrating than spending time on learning something and not getting good at it. We all fall into this trap. Nothing uncommon.

Imagine you have to cycle from Point A to B. There are multiple routes to the end location. Some are short, some are difficult, some are tricky, some have roadblocks, and some feel pleasing but misleading. You have to choose the optimal route based your skills. Also, you cannot spend endless time exploring all the paths as it will only delay when you reach point B. It will just leave you tired and less motivated to keep going.

Similarly, we have multiple ways to reach our learning objectives. Learning a particular topic is time bound. Also, a smart choice of a leaning path keeps us motivated to keep learning.

Which brings us to the question – How do we know we are in the right direction?

Retrospective learning is the answer.

Whenever you learn something, you must also ensure you keep applying the knowledge as you learn. You can do this by either solving a situational problem or teaching the concept to someone else or hypothetically implement it in another field just like we make jokes. While applying your recently gained knowledge, you will hit possible loopholes in your understanding. Which in turn helps you figure out where you need to focus your effort on learning.

You are very likely to understand and apply few of the topics faster, but some may take longer. You can choose to spend time on the weaker topics, but not for long.

I like to begin by directly applying the topic I want to learn. For example, if I want to learn Machine Learning, I start by implementing a primary method. Naturally, I may suck at the first attempt. Then I discover some topics and apply again. I get better by maybe 1%. I keep doing this till eventually, I gain mastery over it. Not only that I also teach it to others whenever I find the time. It helps me strengthen my hold on the topic.

Do you have any other ways that help you learn faster? Please mention your methods in the comments below.

 

Modern Ekalavya Learning Technique 2 – Selecting a Learning Path

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.

What are you waiting for, choose your learning path on Coursera and create your account on Kaggle and start participating?

 

 

Modern Ekalavyas Learning Technique 1 – Start with Why

Modern Ekalavyas Learning Technique 1 – Start with Why

Coursera has more than 8 million registrations, edX has more than 3 million, and Udacity recently crossed the 2 million mark. While these numbers seem staggering, the course completion rate tells an entirely different story. Across all MOOC platforms, the course completion rate stands at a measly 7%. Much research has been done to identify the reason for this abysmal completion figure, and methods to control the dropout rate. Some research indicates the lack of motivation or a healthy “why?” being the primary reason for the low completion rates. The lack of negative repercussions of abandoning a course midway also contributes towards the dropout.

Think about college. If you quit college midway, you have to enrol again to finish your course. However, with MOOCs, you do not have any penalties for abandoning a course. Enrolling again is easy, and many courses are not even time bound. Even if these courses are time-bound, they are generally spaced out enough for someone to finish them without experiencing a time constraint.

Companies have tried experimenting with various fee structures, but they do not seem to have any impact on the completion rates. This pattern appears to extend to my professional field too. For example, I interact with many professionals who want to switch to analytics, but the average tenure in the field is small. What could they do better? As in the example above, people need to start with their “why?” – Why do they want to switch to analytics? If a better salary is the sole motivation, they might want to reconsider their decision. Anyone who intends to shift to analytics needs to have a love for playing with data, so he or she can use that data to help solve business problems. Simply taking a course does not transform someone into a good fit for a new domain.

Ekalavya had an unshakeable urge to gain mastery over archery, which is why he did not give up even when Dronacharya rejected him, and instead, found his unique way of training himself. Much like Ekalavya, if we are resolute in our determination to complete a MOOC, we will reap benefits quickly, and who knows, we might even master it without having to lose a thumb!

If you want further motivation on starting with “WHY?”, Simon Sinek’s TED talkperfectly explains it. You can also visit his website for further reading. Also, if you like to read his book, you can purchase “Start with Why” on Amazon.