Running Women Who Code

I’ve helped to run Women Who Code Sydney for about a year (along with Lucy Bain and Peggy Kuo), and it’s been a blast. We organise practical hands-on workshops for a variety of technology like Arduino, Golang, Sass, Scala and Swift.

Participants spend about 1.5-2 hours working through a tutorial or problem set on their laptops, and can ask volunteers for help if needed, so it’s slightly different to a typical user group: the attendees are expected to code at every event.  I know that I personally learn more when I’m forced to do something, as opposed to listening to someone’s experience, and after you’ve done the workshop, everything’s installed on your laptop ready to experiment more at home.

A typical event might be:

  • 6:00pm: Arrive and dinner, chat to others
  • 6:30pm: Announcements and introductions
  • 6:40pm: Speaker topic for the night (e.g. introduction to Reactive Extensions)
  • 7:00pm: Commence hacking
  • 8:45pm: Feedback forms
  • 9:00pm: Finish

Things I’ve learned while running a hands-on user group:

Have a target that people can aim for
Inviting people to “learn some javascript” where there’s no specific learning material makes for a confusing meetup, because there’s no target to aim for. People will ask a variety of questions from all different angles (e.g. “what does var mean?”, “what do you think of angular vs react?”, “can you explain promises?”). If you provide a tutorial or set of exercises, there’s a defined path that is supposed to be followed to learn something, which cuts down lines of questioning and also provides people with a goal.

Designing a tutorial from scratch takes a lot of work (and rework).
You’re not likely to get it right on the first go, so unless you’re aiming for something you can re-use, you are better off going with already published material.

Utilise existing interactive online tutorials
They’re a big win. The tutorials have already been tested by hundreds of people before you, and someone has put a lot of effort into designing them. They explain concepts step-by-step probably better than you will first time.

Always try out the tutorial first
It’s important to gauge difficulty and identify what prerequisites are required. Also, sometimes the instructions change and it’s not the same tutorial any more!

Give people the answers upfront
If you are writing a custom set of exercises or tutorial, give everyone access to the answers. When people start with a working solution, it’s a lot easier to break various bits to see what they do, rather than having broken code and trying to diagnose what needs fixing.

Have some helpers available to answer questions
This is the thing that people don’t have access to at home. It really helps.

Aim to maximise everyone’s learning experience
You won’t actually cover that much material in a two hour window, so try to pick content that people can try at their own pace – that way everyone learns something.

Select an audience for your meetup
Choose either beginners, or people who are already familiar with programming. It is very difficult to cater for both at the same meetup.

Clarify prerequisites
State whether people need to understand simple if/else statements, or something more involved like recursion. If people turn up to an advanced tutorial but only know basic programming, they might start feeling like they don’t know anything and get discouraged – that’s the last thing you want!

Limit the speaker’s time in chunks
A 10 or 15 minute window is a good amount of time to keep people’s attention (especially after they’ve done a full day of work). Talk for a bit, let people experiment and try what you talked about. Repeat. This is difficult to keep in balance with a self-paced set of exercises, because some people will be ready for the next section before others, but it keeps people focused.


Review of Coursera’s Algorithms Part I by Princeton

This is the first in a series of two posts about a study group I organised for learning Algorithms & Data Structures. This post focuses on the content of the course, which is Princeton’s Algorithms I on Coursera.

The course covers a variety of data structures and searching and sorting algorithms from a programmatic implementation angle (as opposed to mathematic proofs; more on that in my second post). Specifically, this one covered union-find, binary search, stacks, queues, insertion sort, mergesort, quicksort, binary heaps, binary search trees and red-black trees, and a lot more.

The course has multiple types of content to help you learn:

  • The major component is the video lectures, which form about 2.5 hours of content each week and present some algorithm theory
  • Detailed lecture slides
  • Exercise questions, which test you understand that theory
  • Assignments, which make you put an implementation of an algorithm in practice
  • Final exam (I haven’t done this yet, but I still have a few weeks.)

Officially, the course is 6 weeks long, and requires 6-12 hours a week of effort. I think most people in our group underestimated how much time this really takes from your life.

Good things about this course

The combination of lectures, exercises and assignments was a really good way to cover the material from different angles. If you appreciate structured approaches to learning, this will tick all the boxes.

Videos: All of the material is professionally shot and edited. The entire series is presented by Robert Sedgwick, who is a very good lecturer. There is a good level of detail and explanation for each algorithm, especially the animated walk-throughs of each sorting algorithm. You have the option of watching the videos at a faster speed on the Coursera website, and I chose to watch it at 1.25x most of the time, as Sedgwick speaks quite methodically but slower than I am used to. (If you download the videos, you can’t take advantage of this feature, and you also miss the interim quizzes in the videos). It’s very helpful watching videos instead of listening to a live person, as you can pause them and rewind whenever you need to.

Slides: The slides are great. Very detailed, well-laid out and with diagrams to illustrate various concepts. The only thing missing from the slides were the animated walk-throughs of how each algorithm works, but you can always re-watch the videos.

Interim quiz: at the end of each video, and sometimes in the middle, you have to answer a question about the content you just watched.

Discussion boards: The Coursera site includes discussion boards where you can post questions. They’re monitored by people at Princeton who are helping to run the course. It’s a great resource when you get stuck.

Auto-marking for assignments: Assignments are all auto-marked for each submission, and the results from marking are really detailed. Each submission is run though lots of tests, and it also analyses your usage of memory & time relative to input (i.e. are you using constant, logarithmic, linear, quadratic time, etc). I found this quite valuable.

Real-world examples: Discussions of practical implementations of algorithms, such as a physics engine for particles, or easily finding whether lines/objects intersect, were really interesting.

Credibility: Sedgwick is a professor at Princeton’s school of Computing Science. You’re hearing from one of the people who has spent a lot of their life studying and working with algorithms – he’s written several books on algorithms, one of which is used as a reference for the Coursera course (the content is available for free on a corresponding book site). He also found a more efficient variant of Red-Black Trees in 2007, which he discusses in the lectures.

Choose your level of participation: You can cut out various parts of the course if you prefer – for example, if you were to only watch the lectures and make your own notes, you could spend 3 hours a week doing this course and still get something out of it. The minimum I’d recommend is watching the lectures and doing the exercises, as the exercises force you to step through the algorithms and work out what they’re doing.

Language-independent: It’s possible to complete these assignments in different langauges, as our study group proved. We had people write solutions in Rust, Python, Golang, C# and Scala. However, the majority of them completed in Java to take advantage of the auto-marker for the assignments.

Things I’d change about this course

Assignments not geared for unit testing: The APIs for the assignments were quite strict – it was almost impossible to test using dependency injection, or trying to refactor one giant (public) method into smaller public methods so you could test them independently. I did write some tests, but I also ended up submitting assignments to the auto-marker to get feedback for some aspects. I’d prefer if the API was less strict so that you can package your own classes, and break things into smaller chunks.

The assignments vary in complexity. Some require only 2 or 3 hours; others could take another 10 hours just by themselves.

Course schedule: The start date and schedule of the course is advertised as fixed, and quite intense. When they say you need 6-12 hours, they do mean it (and more). In reality, all assignments and lectures have “hard” and “soft” deadlines, and can be submitted up to 6 weeks after the lecture is released.  If we had known, we would have built some catch-up weeks into our study group dates to allow people to keep pace. This isn’t Cousera’s fault, but some knowledge that the content would be around for ~3 months would have helped plan a better schedule for our study group.

Some content not as relevant: This is a personal preference, but the course covers a lot of different searching and sorting algorithms in depth; in reality only a handful of them are in use by major languages. I’d prefer to concentrate on the ones in use, and not cover the ones that have been superseded.


The course was intense, but I learned a lot and it helped connect some dots on how to solve particular types of problems. For me, the best moment was an email from Aidan, one of our study group members, in the last week:

I actually used a weighted quick-union at work yesterday! Im as shocked as everyone else.

Proof that it is actually relevant 🙂

As for Algorithms Part II, I’m sadly stretched working on various things in life, including this blog, Women Who Code Sydney and organising a variety of things with my work at the ABC.  However, Caspar Kreiger is continuing the second half starting this week, so get in touch if you’re interested!  I plan to pick up Part II in October when it is run again.

Study Group: Algorithms & Data Structures

Since doing a Javascript study group last year, I’ve been keen to organise a Data Structures & Algorithms study group (partly to brush up on interviewing).

I’m pleased to announce that the study group will start January 28th. If you’re interested and live in Sydney, read on.

What will I learn?

We will be doing the Algorithms I course by Princeton university.

It involves a series of lectures & quizzes you watch at home, followed by a group meeting every Wednesday. At the group meeting you can ask questions about anything you didn’t understand, and start to go through coding exercises.

The course material is presented in Java, however you can choose a language of your choice to complete the problems. If you would like Coursera to mark your assignments and final exam, you would need to complete the course in Java. (Note: Completion certificates aren’t issued for this course.)

If you are unsure of Java syntax, please read up on a quick syntax guide before starting the course.

Where and when do we meet?

Atlassian has kindly agreed to host our meetings. Their office is Level 6, 341 George Street Sydney. The building entrance is off Wynyard St.

We’ll meet on Wednesdays at 6:30pm (please be prompt).

The course is 6 weeks and runs from January 28th until March 4th. There will be an optional week after the course ends to practice answering technical interview questions.

How much will it cost?

The course is free if you attend 5 out of the 6 meetings. You can skip one meeting without a penalty.

Everyone will be asked to pay 6 x $10 per meeting at the first meeting, a total of $60. For every meeting you attend, you’ll be credited $10 back.

For anyone who misses a meeting, their money goes into a pot. At the end of the course, the pot will be divided among the people who attended the most meetings. Nerdery pays 🙂

This is mainly an attempt to identify the people who really want to participate, and to motivate people to stick with the group.


This is not a beginner’s course. You should:

  • Be able to code confidently in a language of your choice
  • Be comfortable with git
  • Understand the concept of a class, objects, functions, arrays, lists, sets, loops, recursion and the core types available in your chosen language
  • Understand what unit testing is
  • Be willing to discuss your approaches to problems, and demo code
  • Be willing to spend 4-12 hours a week watching lectures and completing code assignments

I’m not teaching this content, I want to learn it and would like other motivated people around at the same time.

How can I sign up?

The study group will be limited to 15 people. The first 15 people who contact me (@daphnechong) and bring a refundable $60 to the first meeting will be eligible.

See you there 🙂

Hello, Arduino

Last September, Women Who Code Sydney ran a Learn Arduino event. I’m generally not very keen on hardware, so I hadn’t bothered to investigate Arduino in depth, but this blinking green light from the workshop was one of the most exciting things I’d seen in ages. It was programming in physical form: I’d written the code, sent it to the motherboard, plugged in the wires and resistors to control the current, then seen something in my environment that I could actually touch and change.


Arduino has been around for a while. It is a small version of a computer with very simple inputs and outputs, and that’s what makes them really fun to play with.  There are lots of different input sensors you can use, like temperature sensors, movement, infrared, light.

It’s fairly inexpensive to get a basic Arduino kit, as cheap as $30 depending on where you get it from. Atlassian kindly sponsored our event and donated 20 starter kits which included the basic Arduino board, and a whole lot of extra sensors to play with.

  • 1 x 830pt Breadboard
  • 4 x LED
  • 2 x RGB LED
  • 1 x 9V Plug
  • 1 x 9V Lead
  • 1 x Breadboard Power Module
  • 4 x Tactile Switch
  • 1 x Small Slide Switch
  • 10 x Resistors
  • 1 x pack of jumper wires
  • 1 x Light Dependant Resistor
  • 1 x Small Plastic Servo
  • 1 x Buzzer
  • 1 x Linear Rotary Potentiometer
  • 1 x Ultrasonic Sensor
  • 1 x Hall Effect Sensor
  • 1 x 7 Segment Display
  • 1 x Temperature sensor
  • 1 x IR phototransistor
  • 1 x NPN transistor BC547

Our host, Natalia Galin did a phenomenal job preparing for the event, even down to these cheat sheets with components separated out and nicely labelled, which made it easy to work on our tasks.


First up was a crash-course on electronics, and how the Arduino’s breadboard circuitry works.


Then a series of programming tasks to connect up the wiring so that lights work, and using physical switches to turn lights on and off. It was addictive!

We were limited by how many kits were available, but we had around 25 people attend the workshop, and the atmosphere was great. A huge thanks goes to Google for sponsoring the venue and catering for the night, and Atlassian for the Arduino kits.



Astronomy courses at Sydney Observatory

In November last year we finished our third course at Sydney Observatory run by Paul Payne – two on astronomy, and one on Einstein’s Theory of Relativity.

If you are interested in astronomy or relativity, they’re the perfect way to learn more in-depth concepts. My personal favourite was Astronomical Concepts, but we loved all of them! Paul is a great teacher, and explains a lot of complicated concepts in a clear and straightforward manner. He also teaches Java at TAFE, so he’s developed a set of computerised 3D models to go with his courses, which help enormously. The courses generally run along school terms, so that gives you plenty of time to sign up before the next one starts in February.

In our last night of the course, we spent a lot of time discussing the universe and its size. I’ll just leave this video of a universe fly-through right here, using data from the Sloan Digital Survey. Each one of those dots is a galaxy – there are over 400,000 of them featured in the video.

There is also a fantastic picture taken by the Hubble space telescope of a seemingly black corner of the sky, revealing thousands of galaxies that extend back in time to within a few million years of the big bang.  More information on the Hubble Ultra Deep Field image.

Hubble Ultra Deep Field image

Science is awesome.

Apricot Couronne & Fraisier Cake

There’s been very little baking mentions on this blog, but last weekend was the Labour Day long weekend, and we’ve been watching a LOT of the Great British Bake Off lately.  So we allocated the entire weekend to baking some of their recipes (and a wee bit of poker). It is unpossible to watch that show without wanting to get your hands covered in flour.

Our first target was the Apricot Couronne, a technical challenge from Season 4. As the telegraph says, “the French know that happiness is a circle of cake called a couronne”, and they are totally right. Just look at it.




It was even more delicious than I had anticipated, with citrus tang from the oranges and apricot jam contrasting with the sweet icing. We pan-toasted the walnuts in the filling before adding them, and the flaked almonds for decoration on top. Both are winning strategies.

The other cake on the hit list was the Fraisier Cake from Season 3. Oh. My. It’s a gorgeous, rich cake that looks stunning, and is actually simpler to make than the couronne above. We feared that our creme patissiere wouldn’t stand up to the weight of the cake or strawberries inside, but it was fine. We could have built bricks with this thing. Our genoese sponge was a little flat, but that didn’t detract from the overall deliciousness. It’s decorated with the four suits from a deck of cards, a little tie-in with our poker night.


Thank goodness Christmas is coming up. Moar excuses for moar cake. 😉

Code Sydney – a Javascript study group

I’ve done quite a few random side projects using Javascript, but I’ve never learned it “properly”, and I’ve always wanted to. In a nice coincidence, a fellow geek Lucy Bain started a Javascript study group a couple of months ago called Code Sydney, which uses the Odin Project‘s course material – so of course I signed up.

Course Content

I’ve really been enjoying the course so far.  It doesn’t assume previous knowledge about Javascript, so it starts with the basics – variables, functions and jQuery. It then progresses through objects & prototypes, the DOM, events, callbacks, scope, closures, and popular frameworks like jQuery, Angular and Node.

Every week  you have to do some homework reading about a specific topic, e.g. prototypes.  There will also be an accompanying coding project to build, which uses the knowledge you’ve just read about. We start the coding project as a group during the study group meeting, and complete it at home later during the week.  Nobody is teaching the material for the study group, so it’s up to each participant to do their homework.

My contributions so far are on github as source code and demos (disclaimer: there is almost zero CSS effort put into these). The more fun projects so far have been rebuilding games, including snake and tic tac toe.


We meet in the Atlassian office once a week for around 2.5 hours.  There are 2 or 3 tutors each week who’ve generously volunteered their time to help out, answer questions and review code.

The format of each night is roughly:

  • Check in (5 mins). Attendance is recorded as a motivational factor.
  • Demos (15-20 mins). A few people demo their solutions to the previous week’s project, and people can discuss different approaches.
  • Questions & Suggestions (5-10 mins). People have a chance to bring up any additional questions for the tutors, or the tutors can suggest “best practice” recommendations after the demos.
  • Start practical coding problem (up to 2 hours). We start the week’s coding problem in class, and finish the rest of it at home. If you aren’t sure how to approach something, you can ask a tutor.

Things I love about the study group model

  • There’s a set time and place to focus on learning something new, so there’s a natural deadline for you to achieve something by
  • I’ve learned much more than if I tried to do the course by myself
  • I’m seeing progress and building on my knowledge each week, which is rewarding and motivating
  • I’ve met new people
  • I get the chance to ask experienced people questions if I’m unsure about something
  • I’m building up a portfolio of fun projects (minesweeper this week!)
  • It’s much cheaper, and arguably better quality than an official course run by someone getting paid to teach. We discuss a lot of our solutions and get to see the merits of different approaches.
  • Nothing stops you paying it forward – feel free to organise your own study group, using the same material. All you need is a space to meet up.

I’m so excited about the format that I’m thinking about co-starting one for algorithms & data structures, as I’ve wanted a refresher and the ability to think/learn about them in a non-pressured environment. Part of the challenge is finding existing people who are knowledgable and enthusiastic about the subject to be tutors, or whether to run it without tutors. In any case, watch this space 🙂

GovHack 2014

GovHack, held on July 11-13, was a fun experience. It’s been running for many years, but it was the first time I’d been involved, and the format is quite different compared to other hackathons.

Firstly, it’s huge: over a thousand hackers get together in 11 cities around Australia, and the timing is all coordinated so that everyone starts and finishes at the same time, and has access to the same data to play around with.

Secondly, thanks to the help of some really dedicated campaigning by individuals in government, particularly Pia Waugh, there’s a lot of public data that is released which probably wouldn’t see the light of day for years. This year included taxation data, land satellite geo data, a whole collection of images and newspaper articles by the National Archives,  and a load of census data by the Australian Bureau of Statistics, to name a few. The aim is to build something interesting, useful or fun. Details about the data are released around 6 weeks in advance, and a special session is run where the custodians explain the formats, where to find it, and how to access it.

Thirdly, there are actual cash prizes. Lots of them. It pays to be prepared by looking at the data beforehand, and working out what your hack idea might be. Also, the judging is done after the event, and results aren’t announced until weeks later. The public are also encouraged to get in on the act and vote for their favourites.


Contrary to my own advice, I turned up on Friday night with no specific plan, and no team members. I was initially curious about doing some kind of map visualisation of the ABS census data using Leaflet’s Choropleth Map tutorial, but none of the data I was interested in had enough granularity (it only went down to state level, whereas I was hoping for postcode or council data at least).

After some quick introductions, our new found team of Keith Ng, David Ma and myself attempted to build something with the NSW Education and Training statistics, which we thought might be fun to show with school boundaries. Unfortunately, we still hadn’t found the boundary data by Saturday, and had also found most of the statistics already published on

So we went back to the drawing board, and decided to try an animated visualisation of public transport movements over the course of a day in Sydney. There is a video to go with our presentation, and the mandatory project page which also contains voting, and the source.  The hack was also featured in this Tech World article about GovHack (woohoo!)

About our hack:

  • Each red dot represents a scheduled departure of a train, bus, ferry or light rail service.
  • We used Leaflet, MapBox and D3 to animate the dots on the map.
  • The dataset is large, and difficult to animate on a single map, so we cut it down to a subset.
  • Unfortunately, the timing isn’t quite right – the lifetime of each dot is longer than it should be, so as the animation goes on there are more red dots on the M2 (for example) than you’d find in real life. However, they all start at the appropriate time of day.


Other hacks I enjoyed from the NSW set:

  • The data-by-region comparator which utilises the National Map and allows non-technical people to drag excel spreadsheets with Geo data onto the map, and visualise it instantly.  Fantastic idea.
  • Money money money by fellow girl geek @pyko, which uses graphs to show ATO statistics on income by sex and region. There’s a very clear visualisation that female earnings peak in their early 30s, while men continue climbing until their late 40s or early 50s. (hello, missed opportunities to get women back into the workforce!)
  • Time Machine, a mobile app to show you nearby historical artifacts using data from the National Archives. Developed by a team of 4 people that included two people still in high school.
  • Show the Gap, highlighting differences between indigenous Australians and the general population in a number of benchmarks including health and employment. It’s a sobering view. Top marks for a very polished video and a cohesive message.

I also very much enjoyed working in Optiver‘s offices over the weekend. The only really disappointing thing was the number of no-shows in Sydney. There was a lot of people who had spent time organising food, encouraging mentors to attend, and donating time and effort, and it was sad to see that go to waste. Other cities didn’t look like they’d had anywhere near the same rate of dropouts, so I would support having to pay for your own tickets next year!

Fun With Public Transport Data

I am a transport nerd, and a map nerd, as evidenced by all the previous hackathons I seem to do involving maps.

Thus, when I discovered that Sydney’s public transport system data is available to download, it seemed only logical that I should involve a map somewhere.  The result is a map to show you where you can live if you want to be within “x” minutes of the city by train. I defined the city to be any of the following stations: Central, Circular Quay, Martin Place, Museum, St James, Town Hall, Wynyard.


There are some unexpected results, because the trains don’t stop at all stations for every journey.

For example:

  • The central corridor supported by T2 inner west line and T1 western line has the best density of minimum times across all stations.
  • Getting to the city from Sutherland or Campbelltown is faster than getting to the city from Hornsby or Pennant Hills.
  • Bondi Junction is a measly 7 minutes away!
  • The fastest train to Glenfield is 14 minutes faster than to its neighbouring station, Macquarie Fields.
  • Eastwood station is just 21 minutes to the city, faster than 3 stations on either side of it.
  • Burwood, Ashfield and Petersham – all on the same line – have almost the same minimum travel time at 10 or 11 minutes.

You can explore the map yourself at  I’d like to do a lot more on it, such as adding the bus and ferry timetables and identifying the individual lines, but it’s a work in progress. If you have any ideas, I’d love to hear them!

A Startup Retrospective

A few weeks ago, I started to pull back work on Vine Trails, and committed to just one day a week.

My co-founder Matt and I weren’t able to keep the same schedules – I was full time, while Matt was only available for a day. At the time I thought it would be better to change my hours to suit his, and have everyone progressing on the same page at the same time. But later, I realised that by agreeing to cut down my hours, I had actually declared that my interest was fading. It just wasn’t for me.

Everyone talks about the fact that you need to be really passionate about your startup idea to succeed, because things will get hard at some point. Your passion is what will drive you through the dip to see the other side. As the weeks progressed, and we learned more things, we adjusted the idea and the focus of the product. But Vine Trails was turning into something I was getting less interested in building.  I was running into barriers, and didn’t possess the drive to break through them.

My original idea was purely travel related – a trip itinerary generator. I wanted to build something that could answer this question:

I have three weeks for a holiday, and I want to go to New Zealand.

What should I do while I’m there?

That’s an enormous problem, and difficult to know where to start. So I decided to cut it down to a really focused vertical that was easy to define: wine tourism. Vine Trails was born.

The thing is, I really like wine. I enjoy travelling to wine regions and tasting wine. I would love if a product like Vine Trails existed already, and I would use it.  But there’s a difference between wanting to use a product, and having the drive to turn an idea into something real. I have friends who like to read about new wine releases, participate in forums, research wine regions, and subscribe to winery mailing lists. For them, that’s just fun and they love reading about it. For me, it would be necessary research rather than something I’d choose to do. When we started putting more focus on Vine Trails appealing to wineries, it just got less interesting to build.

I realised that the data element of the product is what I was passionate about – taking information about their wines and making it available in a new format, or letting people search through it in unusual ways.  I find analysing and visualising data really interesting – and it doesn’t really matter whether that information is about wine, or public transport, or economic growth. Making data accessible is where my interest lies.  I am passionate about data at a completely different level than I am passionate about wine tourism.

Lesson learned.

(Along with other things I learned about startups and team composition.)

Vine Trails still exists, in the capable hands of my co-founder Matt and my husband Niall, two of the biggest wine nerds I know. They’re both working on it part time, which means it will take a little longer to mature, but it’s definitely in the pipeline. I will be pitching in occasionally, but I won’t be the principal driver any more.

In the meantime, if you know anywhere in Sydney looking for data nerds, please drop me a line.