Motiv8.asia

Does the future of learning need to be reimagined? Understanding the past gives us a flavour of what to expect in the future... yet again, we are faced with this ever-deepening puzzle of preparing our youth to contribute to the global economy. Right here, right now is our answer to reimagining education... but how?

From my unique perspective of joining the corporate world when I was barely 18 years of age, 3 areas will need to be focused to revolutionise learning:

1. Value creation In our increasingly digital economy, value creation has become less of a priority as opposed to higher number of "likes" gathered & exam scores. As such, the focus will need to be reemphasised on human-centricity & building lasting value. Principles of value creation apply everywhere, from having a friendly tone at a call centre all the way to providing sound advice as a chartered accountant. All businesses including not-for-profits are in the business of creating value, towards making our…

Being lucky is about being at the right place at the right time with the right people. However, without the right energy levels… we could end up letting our defining moment slip as we are not physically & mentally prepared for the opportunity in our face.

Increasingly, the world is open for business 24/7/365. As such, time management may no longer be critical in prioritising our actions to meet our goals as compared to energy management. To illustrate this point:

Jack wants to get fit. Hence, he sets a goal of losing 10 kg as part of his 2019 resolutions to be completed. As February 2019 came to an end, Jack realised that he was not meeting his goal & instead had put on 1kg. Jack is now contemplating 2 options:

Time management: Extend his goal by adding 2 more months & meet it by February 2020; or

Energy management: Mustering all his energy & work harder than planned to meet the initial goal of losing 10 kg, adjusting different workouts & trying a variety of diets. …

"Hello, World!" was my 1st computer program, 10 months ago as I began my journey in data science. Learning from online & offline resources, I grew exponentially as a professional to face digitalisation.

For your benefit, I’ve written 10 key-takeaways on insights I gained from being a data scientist:

1. Never too old to code, never too smart to code

Coding (a.k.a. programming) is prerequisite to be a data scientist. The good news is, learning to code is easier now than it was 1 nor 10 years ago. There’s plenty of programming languages to choose from, plus the newer ones are simpler yet feature the powerful capabilities of older complex languages. Python (most popular language) would take you just a couple of hours to grasp the basics. Heck you don’t even need a computer - I learnt Python on the SoloLearn App on my iPhone during my commutes to work. If you can afford classes to learn programming, by all means go ahead. Only ignorance is bliss, which will result in you blami…