One-Third of the Track


Prior to my decision to temporarily suspend all simultaneous and unrealistic activities for 2015, I got to reap a bit from my hard work through this certificate. It really means a lot to me that I managed to crawl through this course during January. It was super challenging to balance it with other things but somehow I knew that this is really something that I want to accomplish.

Tidying data is not exactly a glamorous course. It had this rigorous coursework that I had to spend hours and hours trying to make sense of. I already have some basic ideas on where to use what I learned from this course. Just the potential of the knowledge learned to mix with the other things I know from my other intellectual pursuits fills me with excitement beyond words. It is a lifetime of exploration. I may not necessarily leave my computer for a long time for this, but it’s worth it.

Somehow, the pursuits I have laid out for myself for the last two years are taking shape slowly but surely. I know that I started from a completely different industry professionally, but recent events have shown me that this actually might work for me and it’s worth giving a second look. Heck, I really gave it more than a second look! I am transitioning into whole new realms altogether, a joint output of circumstances and my personal preferences. A lot of people look down on my decisions for work. I met one of them before Christmas and I swore not to subject myself to that kind of company again. Since the year kicked in, I have relieved myself of the need to “CONFORM” to what people call as acceptable or normal work. I am carving out something new and if it doesn’t work, I can just wing it til I make it.

There are so many things I realized about life since last year and one of them is that time is a non-renewable resource. I keep writing about this because it can never be emphasized too much anywhere.

So with three subjects down in this signature track course of John Hopkins, there are six remaining demanding subjects that will claim for my attention in the latter part of the year. I am psyched! I am really looking forward to doing more of my adventures in Python and R this 2015. I cannot see myself thriving in any other way. 🙂




Data Janitress

Ever since I started working with data, I had this feeling that I am really more of a janitress of dirty data than an engineer. Really! So much time is devoted to cleaning data than making awesome visualizations out of it. And there are actually two modules in my online education that attest to the fact that I am meant to help sweep the digital debris into more sound data analysis.

There is so little use to deriving and making algorithms pop on your PC if your input data is garbage or cluttered.

My most recent “Data Sayangtist to Data Scientist” project’s exploit is the Data Cleaning course at Coursera.

Getting and Cleaning Data at Coursera

Getting and Cleaning Data at Coursera


A week before the new year kicked in, I had a non-technical primer from Data Journalism module on dealing with messy data for making compelling stories:

Data Cleaning from European Center for Journalism's Canvas Course

Data Cleaning from European Center for Journalism’s Canvas Course

Apparently there are so many people harnessing the ease of using the Internet and a few souls are committed to keeping it clean and tidy on the backend or at least on the analysis end. 🙂 It’s a good place to work on because few people are willing to do it. That’s always my thing; I like going to places that nobody wants, work-wise. I took a course not familiar to many people my age. I engaged in projects that few people think as a suicide mission. And I make unconventional choices. It has never failed me. Being thrown on the deep end of the learning curve is high stress, but the returns are fantabulous!

On the practical side, I tried working on a disaster management information management system project and most of my time was spent scripting primitively encoded Excel sheets into database-friendly, geocoded csv format. I also did some work on exploring or researching standardization options in government datasets and BOY, this continues to consume much of my time this year. It will continue to eat my life as we speak. Yep, janitress life, hello hello!

Cleaning is not fun in itself but the possibilities that happen after you clean the data are reason to keep myself motivated. 🙂

And there is so much data worth cleaning online and offline. My wish list is really bordering on storing huge amounts of analyzable data than expensive objects or frequent out of town trips. I am actually content staying behind my computer and studying these things 80-90% of my time this year. Of course, having a vacation occasionally won’t hurt. 😉 That’s why I am also cooking some travel things up to balance my innate introverted nature compounded by my choice of work.

Data cleanliness is really next to data analysis godliness! 😀

Your Nerdom Come

A Sample Awesome Free Online Course

A Sample Awesome Free Online Course – Data Journalism


I cannot really imagine the immense changes that I have undergone this year. It’s like I am entering a new realm. I can no longer recognize my old self because of the changes. It’s so amazing and filled with exciting prospects that provide personal and professional enrichment for me and the target beneficiaries of my personal advocacy.

I have been volleying emails with successful techno-preneurs in the last few weeks.  And on top of my usual work grind, I have been working on simultaneous industries or tracks. It’s practically insane, yes. It has the price of giving up my social life temporarily but it’s all WORTH IT. 🙂

One of the late (sobs!) discoveries of this month is the data journalism course at Canvas. They were issuing certificates until July 2014 of this year and I am catching to watch most of the videos before the remaining read only course access closes this December 31st.

I had initial failed attempts to finish an MOOC or online course. I think I signed up for around 6 subjects in Coursera before but I never got beyond the first week.

But this year, I have finally surmounted the failures of the past. As of this date, I have earned two certificates for two data science courses. I had no prior background in R programming but I managed to crawl through it in the midst of all my work and personal obligations. It would have cost me Php 95,000 to enroll in those subjects here in Manila. I got to study them for free in the comforts of my home while drinking pineapple juice and streaming inspirational TED talks in between videos.

These days, with a simple android device and a fairly fast internet connection, you can do ANYTHING online. You can learn so many things. Google is full of golden things that can be harnessed to do some positive change. The only challenge is not to succumb to information overload and prioritize which courses are worth gold and which can be delayed or rejected.

I think that these days, being a Renaissance Man is no longer limited to the elite people who can afford expensive education. If you have a strong mind, a good internet connection, and an optimized life plan, you can be a hell of a polymath. The possibilities are immense and exciting.

I must admit that balancing my goals or pursuits is extremely difficult. I have this master game plan in my head and I need around 10 to 15 arms to do them daily.

Here is a very salient piece of advice that I got just this morning from one of the successful techno-preneurs that I have the privilege of talking with:

‘I think this is only very overwhelming because you want to see the results soon. But that’s not how expertise works, as far as I can tell. First, it’s important to narrow down the things you couldn’t live without, plus all the costs you are willing to pay for them (time, money, energy, psychologically, and other non-quantifiable costs). The things you’re willing to give up for each of these “tracks.”‘
This is my food for thought this Christmas as I sit beside the Christmas tree and think of 2015.
“When some things don’t feel right to you or if you’re not willing to commit any deeper, be quick about dropping them.” THIS is another golden piece of advice. I was reading a book of a father and son entitled Wisdom Meets Passion and in the latter chapters, they discussed this too. I think my life goals need a lot of pruning so that I can realize all those dreams one by one. It’s just amazing and exciting and beyond words.
I dropped certain things, including a huge percentage of time I use for socializing with people. I actually found my return to Facebook too noisy. It’s difficult to explain this to people when they ask me why I deactivated and returned to my shell. This shell has been PARADISE to me, nerdgasm-wise. And yes, nerdom has really come full circle this time around. And I do not have to apologize or feel sorry for it.


A very successful friend who is now the regional director of one of the biggest freelancing websites in the world encouraged me to try R and Hadoop in addition to my Python and Drupal pursuits. He says that with the boom of big data, these skills will become like wine over time. This is what has been eating up all of my time and my life lately. This thing he recommended is probably the best advice of 2014 for Helena.

I was deeply inspired by how he (friend) managed to make things work on his end, so I took his advice and I embarked on a different course of intellectual exploration. I do it during my free time (FYI, I don’t really have one so I am hacking my life to fit it all in! Good luck to my optimization efforts!)

Now, I shall name this post Fo-R-sight, because my attempts to learn R programming is exactly that: a foresight into the future with the data of today.

Forgive the pun; I have been rushing all weekend to finish my basic data science course work.  My eyes are all bleary from the information overload and I am just sitting here, thinking about the marvels of learning from an international university from the comforts of my home.

This month, I believe I hit a personal development milestone when I started learning the basics of R while learning everything else. It’s not yet at par with the world-shaking levels of data that the world’s awesome data scientists are able to manage now. I’m just a tiny mole in the computing universe, and I will always be so. But I’ll be the most awesome  mole I can be, for sure. 

It’s just good enough to make me happy and I find myself very willing to sacrifice a lot to do this. I just know how much I wanted it when I fought to make time for it despite the fragile nature of my schedule.

And now I have new people I want to emulate, career-wise. Years ago, people would ask me who I would like to peg myself as becoming. I have no answer. Now, I have people I look up to, blogs I am subscribed to almost religiously, and things that I want to do with my time. I now view time differently, not as something to be used for lounging around, but something that I should maximize so that I can do as much positive change to the world as humanely and digitally possible.

I used to be so lost. I went to different jobs, swam in office politic shark-infested waters, waded in the worst of my personal issues about myself… And finally, I got to this peaceful and stable point where I can say that I know my game plan for the next five to ten years. I am actually happy at where I am now, professionally. It’s not even about the position; it’s more on the research problems that I am assigned to solving.

Additionally, I thought I was already smart enough with math from engineering, only to find out in my current job that I know nothing and I am such a huge and dumb ape all this time.

LiDAR data makes use of higher-than-vector math and I need to up my game, sharpen my saw, and hit those books. I love it. I love the rush, that adrenaline-boosting intellectual rush that comes when I discover new things to develop from my computer… I hate the tiny things that take me away from my exploration like the usual work politics and inefficiencies, but it’s a painful part of the package and I have to accept that, nay, embrace that on a daily basis so that I can keep doing what I am really doing.

Another prolific friend once told me: “we have our day jobs, and we have the real second job that goes beneath what people see.” I totally agree.

In my job, I had to handle a great amount of high-level matrices to automate certain processes. So learning R for my pet project is like a cherry topping to a wide cake of learning.

R is quite adept at handling matrices. It can do so many things. It’s so powerful that sometimes it scares me. Python also has its own suite of awesome things like Geopandas and other data science-related libraries and I have more than enough to play with at this point in time.

I missed writing so much and there is an overflow of things I wanted to write about. I just could not consolidate them as neatly as those R data frames so it’s a giant dump of things on a blog post before the work grind eats me up again on weekdays.

There’s a bright data-driven future up ahead. 🙂

Day 51: #100HappyDays
Python Data Science

The Python Logo

The Python Logo


In college, I did not really understand the guys who loved programming and loves diving in the internet at the backend side. But I had such friends. I just did not understand them as much as I do now.

It was only recently that I learned to appreciate the beauty and magic of it all.

For a previous project I handled, I was privileged to learn Python scripting basics. It was amazing! In college, I had C++ basic lessons and some Java but that’s it. I only really learned to love it when I started working as an engineer, although I did get a good mark on C++ course.

Python is quite special since it had that shocking quality to it. The syntax is so simple yet so powerful. It does not need terminating semi-colons that can wreak havoc on your code.

For May, there was this meetup of Python experts today and I decided to attend with my good friends. It was a very nice way to spend Friday night, have a bit of pizza, and have a lot of Python pizzazz for the head. The speaker was no less than Miss Stef Sy, Stanford graduate and ex-Googler, who works as a data scientist.

You can check out the slides by clicking here. To know more about Data Science, I think this nice online course on Data Science Masters will really help you. <3 <3 <3

What can I say? I am the reformed crawlie hater who now loves the crawling code of Python…