Three years ago, when the economy was starting to sag and I was feeling the first jitters about my analog qualifications in a digital world, I signed up for an online course on data science.

The programme cost about US$500 for a series of 10 modules, including a capstone project, but I wouldn't have to pay for all of it.

The Government would subsidise between 40 and 80 per cent of the fees, depending on how many modules I completed, and throw in an extra $500 incentive if I finished the whole programme. It would be another year before every Singaporean was given $500 in SkillsFuture credits for continuing education, but this course would have fit nicely into that budget.

Although I wasn't actually sure what a data scientist did, I was confident the course would make me more marketable. But before I put my money where my mouth was, I asked my brother, an actual data scientist, whether he thought the course was worth taking.

He asked a question in return: "What do you hope to get out of it?"



ST ILLUSTRATION: MIEL



I quipped: "The ability to nod knowingly when people mention data science in conversation."

My answer was half in jest, but it rings unamusingly true now. I completed six of the 10 modules, just enough to qualify for the minimum 40 per cent course fee refund, before I threw in the towel.

It was a fascinating and eye-opening course. But with no computer science background to speak of, I - a former humanities and business student - found it punishing to keep up with the video lectures and weekly coding homework, on top of a full-time job.

Before the course started, I had never even heard of R, the programming language at its centre that is often used for data analysis. As my coursemates bandied around unfamiliar references to online coding resources - such as GitHub, where people can upload their code for others to review, modify and use, or StackOverflow, a furiously participative discussion forum - I sometimes felt like a caveman banging on a typewriter with two fingers.

To say I learnt a lot would be an understatement. But to say I can now put the skills I acquired to serious use - such as to quit my job in media and start looking for one in data science - would also be a lie.

In fact, my main takeaway from the course was this: Just as a baking class doesn't equip you to open a cake shop, or a wine appreciation workshop won't make you a sommelier, a single coding course, however intensive, is inadequate preparation for a career in IT.

No one knows this better than the global tech giants, to whose open-concept offices job-seekers are flocking. A recent report by Bloomberg highlighted the mismatch between graduates of so-called coding bootcamps and the digital jobs they covet, with some firms going on record to say they automatically reject applicants whose qualifications are from coding schools.

"Our experience has found that most graduates from these programmes are not quite prepared for software engineering roles at Google without additional training or previous programming roles in the industry," Bloomberg quoted a Google director as saying. A spokesman for Cisco was more direct: "We generally don't hire from coding schools."

In other words, making a mid-career switch into the tech industry, with no prior experience, is going to take a lot more than $500 in SkillsFuture credits, or learning a programming language.

Just as a baking class doesn't equip you to open a cake shop, or a wine appreciation workshop won't make you a sommelier, a single coding course, however intensive, is inadequate preparation for a career in IT.

It isn't just aspiring coders who face this problem. Dozens of new training companies have sprung up for the sole purpose of offering courses to soak up these funds, from basic sewing to beginner flower arrangement techniques.

As personal enrichment programmes, these courses are perfectly suitable and immensely appealing. But to help workers acquire adequate skills for a new job, they can only be one small part of a much larger plan.

What that larger plan is, though, many of us have no clue, or no time to worry about right now. That may be why only 126,000 Singaporeans so far have made use of their SkillsFuture credits - just 5 per cent of the more than 2 million citizens who are entitled to them.

But as increasing numbers of professionals, managers, executives and technicians (PMETs) get displaced from shrivelling sectors of the economy, a more structured - and smarter - approach will be needed to equip mid-level workers with enough career guidance to plan for a lifelong series of jobs.

For a start, the focus of SkillsFuture should shift from the $500 credit and what you can do with it, to the end-point of what jobs are available, what essential skills they need and then what eligible courses you can use the $500 funds for. Some work in this area has already started. One of the most promising is JobTech, a new online portal that aggregates recruitment ads and uses data analytics to identify the top hirers, top-paying jobs and top skills needed in each industry.

In its current free beta version, it has some limitations - including having only seven sectors on offer - as well as some interesting quirks. In the area of government jobs, for instance, one of the top three skills demanded is meticulousness, but the portal's engine cannot find any suitable SkillsFuture courses to impart that ability.

Also due to start this year is a career guidance and jobs bank database with the rather unwieldy name of Individual Learning Portfolio (ILP). Part of the overall SkillsFuture movement, it would close a major gap in the job search process by first assessing a worker's interests and skills before suggesting possible jobs and, in turn, the necessary training.

Still missing, however, is a mechanism to make sense of the multitude of subsidised courses out there, and to string these bite-sized classes into coherent portfolios that employers will recognise as sufficient capability for a new job.

After all, an undergraduate degree programme comprises building blocks that add up to a certification. A mid-career switch should similarly require a clear progression of training, including a formula to translate work experience in one industry into a concrete set of skills that can be useful in another sector.

On the part of workers, what is needed is a readiness to expect their full-time jobs to be disrupted and to start preparing for their next career well before their current one becomes obsolete.

This entails taking an exacting look at their capabilities, making realistic goals for subsequent jobs and plugging any gaps between the two. Being open to opportunities - such as job rotations, overseas postings or mid-career secondments and attachments - will also help with crafting a convincing skills narrative.

With lifespans extending and retirement ages becoming irrelevant, it is increasingly unsafe to assume that career paths will be rigidly linear progressions, or that a patchwork of ad-hoc self-improvement courses will be sufficient to make the leap into a new career.

Having a detailed next-career plan will make our workers not just job-ready, but also future-ready.