Finally...

After a year, the final results were up. The course was above my station. Anyways, am happy it’s over. I am not sure though if I am relieved. The course kept me on my toes, there was knowledge gain and self-discovery, there were challenges and deadlines… I will miss them. So here are the main take outs from the perspective of a middle-aged person after doing a full-time course away from home. Note: I believe that retrospective stories, specially of successes, are over rated. Most of them are dramatized and would be very different if they ended in a disaster. Those stories inspire many but I cringe at them. So, I will try to be as realistic when I am narrating mine:  

• I had not imagined getting As in all subjects but I think there was some leeway in marking owing to Covid.
• From the age POV, there was no stigma, at least in NZ or in my course. Few students were older to me and everyone got interesting skills on board. Some excelled in coding and software and others in application and presentation. All of us have a skill.
• I realised I am not good at retention. 
• All of us should take a break and reskill. If we want to be continuously employed. Over time the trend will move to frequent breaks and shorter courses.
• Indian style of education is prescriptory while NZ is exploratory. Both have their advantages. A blend would have been nicer.
• If you intend doing a course,
• Choose a course that interests you rather than the one that is trending
• Spend time reading the extra material (white papers, books etc.) rather than just finishing the course topics. I wish I could do this more. I am not confident of even a single topic I studied.
• Preference should be to undertake full time course. It is the only way to do justice. Else your work will always take priority.  
• Choose a course which you are able to practice else you will forget what you studied and the skill will be outdated soon. Many skills will be outdated soon.
• But the mind will not be. Unlike penis, once stretched by a new idea, the mind at least never regains its original dimensions.
• We usually excel when the ass is on fire. And when there are no alternatives.
• Data Science, AI, ML are all overrated and have limited business application and proven success stories. The companies that are able to make good use of it have tons of good data. Most companies don’t have good data. Therefore the answer to all data problem is not a machine learning model.
• Python, R and all such languages are over rated too and are probably regressive. Very soon most of what we do writing laborious codes paying attention to CAPS, joins, data cleaning etc. will all be drag, drop, click based. Knowing which model to use and its application in business will be more critical than coding.  
• No matter the pressure or deadlines, I always watched Netflix in the night.  And took frequent walks. They were highly cathartic.
• From the course point of view, it helped that the loved ones were not around.

-    But I missed them. Sorely. After the first sem when things started to look easier, and I had time at hand, I missed them more and often. Gradually, without my noticing, I was able to lock such thoughts away at the back of my mind and able to pretend that everything was quite all right.

Post the results I got my work visa and I accepted Spark’s offer for a full-time role as a Business Analytics Specialist. Most of our batch is still looking. Yes, I did well during internship but more importantly I was at the right place at the right time. Luck played a bigger role than skill to grab this offer. Meanwhile it is critical for permanent residency application. This means I will not be able to return to India anytime soon.

If you always get what you want, there will be no difference between life and dreams. (copied from somewhere)

So, the journey of the business school as a student ends here. At least for now.

This is therefore the last entry of this blog. 

I will hopefully be updating my other blogs Global Gamboler and Thoughtsnfantasies