My journey with coding in python and R started with the code-along-with-me sites like CodeAcademy, Datacamp, Dataquest,

But Cindy built a loving community and then obliterated it, almost as if she felt she had no other choice or nothing to lose. And that’s symptomatic of something so utterly broken I can’t envision ever being able to put it back together.

But Cindy built a loving community and then obliterated it, almost as if she felt she had no other choice or nothing to lose. And that’s symptomatic of something so utterly broken I can’t envision ever being able to put it back together.

In this series of blog posts, I would like to highlight some of the classes that I have taken along the journey, along with their pros and cons. Through that, I hope to help people who were in my shoes in planning their self-learning journey in data science. These posts are:

This is close to what we encounter at work as an analyst — we use different techniques that we’ve learnt to extract information from the same database. The following is the entity-relationship diagram of the SQLZoo question ‘Help Desk’. Given this, you’re asked to show the manager and number of calls received for each hour of the day on 2017–08–12. (Try it yourself here!)

To learn the very basic concepts (the words or sentences of SQL), I used Datacamp (Introduction to SQL) and Dataquest (SQL Fundamentals). (I will go through the pros and cons of Datacamp and Dataquest later.) In general, these sites go through the essential SQL skills with illuminating exercises and examples. Some concepts covered are:

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f movement. Even in still moments, leaves tremble and lungs expand. In the realm of digital product design, it would seem that motion is second nature, an extension of the everyday to be leveraged with little effort. If only that were true.

SQL is the language to communicate with a database where the data lives. If the data is a treasure buried underground, then SQL is the shovel to dig up the raw form of the treasure. More concretely, it allows us extract information from one or a combination of several tables in the database.

To learn these skills, I mainly focused on using SQLZoo.net, which is free and provide very challenging exercises for each concept. My favourite feature of SQLZoo is the fact that it has exercises that test the different concepts in one integrated question. For instance, one is provided with the following entity-relationship diagram and is asked to create complex queries based on it.

There was something so fundamentally sound and well-adjusted about the unquestioning generosity of those who rallied around Cindy, and about the groundswell of financial and emotional support she received even from people who appeared to be short on both. I knew how awful it was to learn that you can’t save someone, and how extraordinary it was to watch people try. Cindy’s friends were stung, and badly, but would hopefully shake off their distrust and continue to take care of those closest to them.

However, being able to complete these exercises did not sufficiently prepare me as an analyst. I was able to understand words and sentences, but I was nowhere near writing a full paragraph. In particular, some salient intermediate and advanced concepts like sub-queries and window functions are either absent or not extensively covered, though they had been tested in several technical interviews and is essential for my current role as an analyst. These skills include

Pat died in June 2015, just days before his 35th birthday, and the unstoppable tragedy forced some of us into rueful reflection about how things could have been different, and many more of us into therapy. Five years later, I’m still not sure how to react.

There are many different ‘flavours’ of SQL, like SQL Server, PostgreSQL, Oracle, MySQL and SQLite. Each of these differs slightly, but the syntax remains largely similar and you need not worry about which flavour of SQL you’re learning.

The challenges of my grief and that of my friends in the aftermath of Pat’s death, a time when we hung on each other like every bone was broken, made it doubly hard to watch Cindy blow up so many of her close relationships for an unnecessary lie.

And yet, once I realized Cindy had been lying, all of the compassion I had been cautiously withholding came flooding in — even more for her than for those who had been victimized.

To start learning about the programming and the tools needed for data science, one cannot run away from R and/or Python. They are very popular programming languages which are used for data manipulation, visualization and wrangling. The question or R vs Python is an age-old question that deserves another post on its own. My take?