Cheap, fast but needs persistence: My experience of a … – The Australian Financial Review

A journalist’s success arguably rests on the quality of facts they uncover and the words they use to communicate them. Which is what came to mind when my editor asked me to enrol in a microcredential course and write about my experience.
Given I have no plans to change careers, I wanted to learn something that could help me become a better journalist. So, I figured I could either learn how to use my words more effectively, or pick up new ways to discover more compelling facts.
I settled on the second option and decided that learning how to better wrangle data would be a good place to start.
Some of the e-learning courses from Coursera are from prestigious universities. Getty
I started by searching “data” on the learning marketplace Coursera – partly because I knew the platform offered many free courses and partly because I had enjoyed using it previously. Plus, I liked that the course providers were typically prestigious universities or well-known employers.
After filtering the search results on Coursera to show only “beginner” level courses that lasted between one and four weeks, I was left with 743 options to choose from.
They ranged from Corporate Strategy by the University of London to AI for Everyone by DeepLearning.AI. An IBM course entitled What is Data Science? promised to tell me “why data science has been labelled as the sexiest profession of the 21st century”. I was drawn to the recognisable brand, accessible title and 4.7 star rating across 63,200 reviews. Plus, who wouldn’t want to improve their sex appeal?
The course would take only nine hours to complete, but it was too theoretical for my liking (perhaps because it was meant to be studied as part of a broader professional certificate). At the end of it, I would be able to “define data science and its importance in today’s data-driven world”. Which didn’t exactly get my pulse racing. I wanted to pick up practical skills to help me analyse data – not be told why that was an admirable aim.
A more promising course from IBM – Tools for Data Science – and another from Google – Analyse Data to Answer Questions (one of eight courses in the Google Data Analytics Professional Certificate) – were more what I was looking for.
I enrolled in the Google course but didn’t last long. After watching a three-minute video and reading a few hundred words about what I would learn in the course, I was asked to write 60-100 words about an organisational system I already use in my life, what I think is involved in the process of organising data and what I want to better understand about organising data.
A screenshot from Google’s data course, which included many instructional videos and was part of a broader professional certificate. YouTube
A hundred words is not much, but given the next part of the course was a “meet and greet” encouraging me to write in a forum about what I was most excited about learning, I decided to jump ship and look elsewhere. With a deadline looming, I was impatient to get stuck into some practical training.
So I turned my attention to Codecademy, a US-based website teaching people how to code since 2011. After searching for free courses in the data science section of its catalogue, I decided to enrol in the platform’s Learn SQL course. (I signed up for a seven-day free trial to get the same access as a paying subscriber.)
SQL – or “sequel” – stands for structured query language. It is a programming language used to manage and retrieve data from relational databases.
The course was aimed at beginners and slated to take only eight hours to complete, so I signed up and got started.
I was immediately impressed by Codecademy’s learning interface. It was slick and easy to use, and more engaging than the Coursera platform as it invited my active participation from the start.
After reading just three paragraphs about SQL, I was asked to enter some text – “SELECT * FROM celebs;” – into a live code editor so that I could see first-hand what information that code would retrieve from the database. (In this instance, it retrieved all columns and all rows from the celebs database used in the course, which comprised the names and ages of four celebrities.)
The next slide offered more background information about SQL, before the third returned to the initial code I was asked to put into the live code editor. It explained that the line of code was known as a “statement”; that SELECT and FROM are “clauses” or “commands” that perform specific tasks in SQL; and that all statements in SQL end in a semicolon.
Each slide introduced a new command and explained what it could be used for – whether it be finding the average value in a column, or only showing apps with more than 30,000 downloads – before issuing a series of instructions that required me to perform increasingly complex tasks using the information I had just learnt.
I started off by creating new tables and updating existing records in a database. But after a few hours of learning, I could write the code required to find out the average size of a start-up in a database in each given location.
Soon afterwards, I could use SQL to work out the best time for a journalist to publish a story on the Hacker News website if they wanted to maximise their readership – something that could certainly prove useful in my day job.
Each of the course’s four lessons, which comprised 10 or more slides, ended with a multiple-choice quiz and a separate project that involved me answering questions by inputting the correct text into the live code editor. Sometimes the questions came with useful pointers, and at other times I was left to my own devices. And if I got stuck, I could find out the correct answer by clicking “Stuck? Get a hint.”
I enjoyed the course and finished it in about eight hours. It felt good to do something mentally challenging that had nothing to do with writing and I enjoyed how hands-on it was.
But I also knew I would forget almost everything I had learnt and find virtually no practical use for the little I did retain, unless I found time in my weekly schedule to put my newfound knowledge to the test. Which perhaps gets to the nut of it.
Microcredentials like the one I completed are clearly a fantastic way to test-drive a new subject or to top-up knowledge in an existing area of expertise.
They are cheap, fast and typically have a practical bent to them.
But if this process taught me anything long-lasting, it is that learning a new skill to any meaningful degree cannot be achieved by completing a single microcredential. Learning something new requires persistence and regular practice. Which leaves me with a conundrum. Either I sign onto another class, or I let my data analysis ambitions wither and die.
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