The amateur

In French, amateur means love.

A person who loves what they're working on.

But you know it means elsewhere. The rookie. The beginner. The one who doesn't know much.

It's easy to be afraid to share your work because you think it fits this form of the word.

It's easy to forget an expert doesn't start out as an expert. They had to begin somewhere. And it's dangerous if an expert ever forgets how to be an amateur. Forgets how to see the world through the eyes of a beginner.

While the expert is busy trying to do things how they've always been done, the amateur is figuring out how not to do things. Soon enough, they'll realise the way it's always been done eventually becomes wrong too.

As always, the value is in the crossover. Being an expert and an amateur at the same time. Having a foundation of knowledge of the world but still looking at everything through the eyes of love.

It's okay if you're not an expert yet. In the meantime, you can strive to be comfortable being an amateur (the French version) forever.

How to write a good resume

I haven't had to update my resume for a while. When I started at Max Kelsen, I never sent in a resume.

And when I applied for a teaching role at DataCamp, instead of attaching a resume form, I typed a few sentences about my recent and relevant experiences.

I've never been a fan of resumes. I found them hard to write and always wanted to put more than was necessary.

And more importantly, an A4 sheet of paper is hardly the best way to evaluate someone's abilities.

But for some roles, like the one my brother is applying for, they're required.

So how do you make a good one?

1. Keep it short

No more than one page. Respect the time of the person who's going to be reading it. Anything more than a page is overkill.

2. Tailor it for the role

If you've got plenty of experience, cut out what's not related to the role you're applying for. Keep it short.

If you don't have much experience, list other projects you've worked on.

If you haven't worked on other projects, start working on some other projects or be honest about where you're at in a custom cover letter.

'I don't have any completed projects as of yet but am applying to this role to show my interest.'

'Over the next X months, I'll be working on Z project. Once I've completed it, I'll report back with my progress.'

3. Be honest

This is obvious. Don't list anything you wouldn't be able to talk about in length during an interview.

If you haven't got the relevant experience, address it, address how you would handle it, address what you're going to do about it (see the bottom of 2).

4. Be specific

Not good: Worked with customers every day.

Good: Served an average of 3000 customers per quarter with an 88 NPS score.

Not good: Worked on data science projects.

Good: Built a data science pipeline which saved a clients business an average of $10,000 per month in 6-weeks.

What have you worked on?

How much?

How many?

How often?

Include the details. 2-3 dot points per major experience.

5. What are you interested in?

Some are on the fence about this. But I'm for it. You can make your own decision.

Add a little human to it.

What's been getting you excited lately?

What's something non-role related you've been enjoying?

After all, if you're successful, there's a chance you will have to spend time with the people who are reading your resume.

Give to a reason to want to know more. This could be under a hobbies/interest section. Or in a custom cover letter.

6. No spelling mistakes. Ever.

Modern resume filters will discard anything with a mistake.

When you think it's ready to send off, read it again. Show it to a friend to read. Read it out loud. Does it make sense?

Use a tool like Grammarly to make sure your words are spelled correctly and are in order.

7. Have a little more

'Where can I go to see more?'

Have a presence online. A website, a blog, a portfolio, a GitHub account, a LinkedIn, a place to see that project you've worked on. You don't need them all but at least 2 would be good.

I don't plan on ever having to send another resume to someone, I've got a full LinkedIn for that. Or if they want to know a little more, I'm not hard to find online.

In a resume filtering world, having the little bit extra is what will set you apart.

My resume is below. You can copy it if you like. It's out of date but it hits the points above.

If you're looking for a guide on how to fill a LinkedIn profile, you can copy mine too. It's not the best but it's full of information.

Looking for a place to make a resume? If I had to do mine again, I'd go to, I haven't used it but it looks slick. Otherwise, there's a free template on Google Docs, Josh an I used that to make his.

All the best with the next application!

My resume for April 2018.

My resume for April 2018.

Some thoughts on university versus learning online for data science

Zac emailed me asking a question.

Keep on working and keep looking for new opportunities in the field…
Go back to uni and finish the last 18 months of my degree.

He just finished an internship and has about 18-months left at university before he finishes his computer science degree.

It’s a tough choice.

I sat and thought about it for a while. Then replied to the email with some unedited thoughts.

And I’m sharing them here, also unedited. Bear in mind, I’ve never been to university to study computer science.


Here’s how I see it, I’m gonna write a few thoughts out loud.

Where do you want to be/see yourself in 3-5 years? 

It sounds like you’re pretty switched on to where your skillset lies (aka, teaching yourself, working on things which interest you).

Might be worth having a think about which one better suits the ideal version of you in 3-5 years.

Does that ideal version of you require a university degree? Or could that version of you get by without one?

Which one is the most uncomfortable in the short term?

I’m very long term focused (I have to remind myself of this every day). So whenever I come up to a hard decision, I ask myself, ‘Which one is hardest in the short term?’

I treat short term as anything under 2-3 years (the starting era of the ideal version of yourself).

18-months isn’t really the longest time

How much of a rush are you in?

Could you stick out the 18-months, share your work online through an online portfolio, upskill yourself through various other courses (and jump ahead of others) and come out with a degree AND some extra skills.

Get after it

This is countering the above point.

If you think you have the balls to chase after it (sounds like you already do), why do you need university to be a gatekeeper?

Sure, not having an official degree may shut you off from some companies, but to me, a piece a paper never really meant much. Especially when the best quality materials in world are available online.

I have a colleague doing a data science masters at UQ and he said he has learned way more since working with Max Kelsen than at university.

Put it this way, I was driving Uber this time last year. But I followed through with my curriculum, shared my work online and got found by an awesome company.

Share your work

Whichever path you choose, I can’t emphasis this enough. Make sure people can find you online.

If you’re not going to get a degree. Be the person who’s name comes up on others LinkedIn feeds for data science posts. Have some good Medium articles, share what you’ve been doing.

It’ll feel weird in the start. Trust me. But then you’ll realise the potential of it.

All of sudden, you can become an expert in your field by being the one to communicate the skills you’re learning.

How did I do?

What would you do in Zac’s situation? Learn online and look for more work experience? Or stick out the 18-months of computer science?