Get a team

You don't need to do this right at the beginning. You should probably solve at least the first two or three lecture assignments alone to get a feel for it. But later, having a team, always helped me.

Often my friends could come up with better model architecture or improve mine. Sometimes we were doing one assignment for several hours, sitting waxed to one screen and debugging together. I remember one particular occasion when at the end we were just so tired that we started doing round-robin when one of us was debugging and the other two were resting.

Generally, having a team saves time, you can learn from each other, share materials and grind some bonus points by creating bigger ensemble models.

You don't need a team

I feel obliged to say that team isn't needed. I have a friend who did both of the courses alone and always had at least the same amount of points.

Create an account on Pizza

You should do this immedietely. People will often post their inquiries about problems similar to yours. You should also use it to ask questions often. It all saves time.

I also recommend changing notification settings. The default is an email summary every 4-hours. This clutters mail too much and it doesn't add any benefit.

Do the first week assignments during the first week

There are usually two weeks for each assignment. You should do assignments the week they are assigned, not the week they are due. Waiting for the deadline is just stupid.

I can guarantee that there will come a week when you are just too tired or too busy which will make you skip otherwise an easy assignment which will result in you loosing points.

Don't lose easy points!

Easiest bonus points are at the start

If you want bonus points from competitions the easiest time to get them is during the first one or two months of the course. At the beginning a lot of people are just trying to pass baselines and then stop improving their models. You should defeat them rather easily.

Later in the game, tryhards remain but baselines-only folks fall behind.

Watch/attend practicals

It's easy to get into the habit of skipping practicals. And in a way that's alright. They are recorded. But most of the time you will still watch them later because solving assignments without tips Milan Straka gives puts you in unnecessary disadvantage.

My usual procedure for solving an assignment consisted of the following steps (in order)

• understand the problem description
• skim through the template
• code what you know
• watch the relevant part of the practicals
• code the rest
• debug

Neural network $\implies$ ensemble

Whenever there is a competition and you are using neural networks you should ensemble. It will give you a cheap nudge in performance which will probably result in at least one free bonus point. Don't let free bonus points escape.

Nevertheless, if you are doing ensemble of more than $\approx 5$ models it's probably too much. It's always better to have one well-finuted model than an ensemble of garbage.

Become a Grand Pullrequester

You can get up to 10 comunnity points for correcting slides, TODO comments in assignments, etc. It takes at most five minutes to correct a mistake if you have set up a fork of the original repository. On the other hand, solving an assignment can take several hours. Let's say that you need one hour for assignment-point and five minutes for slides-correcting-point. Thus, it is $12\times$ faster to get the slides-correcting-points.

If you've never contributed to public repository on GitHub here is how.

Read papers

Look for resources outside the course. A good start is to use references given during lectures. If you are looking for a reading on some specific topic you can also ask at Piazza. I am sure that somebody will be happy to help you.

Youtube might be also a good try. There are tons of high-quality courses from world-renowned universities that you can use to boost your studies.

The primary reason to study outside resources is that you'll learn much more, howbeit you can also draw inspiration from them. Mr. Straka allows you to use an existing architecture in a competition if you cite it properly.

Extend deadlines

Whenever you are trying to solve an assignment but can't do it in time or you are lost, write to Milan Straka.

Each time I asked for it, he was more than willing to help or extend the assignment deadline.

Doing it all

In the Deep Learning and the Deep Reinforcement Learning courses it is possible to pass by completing all assignments (as of writing this).

Mr. Straka says it's a little trap. It takes more time to do all the assignments than do some and then study for the test. In my opinion, studying for the exam is a nice refresher of all that was done during the semester so you might even learn more if you take it. Nonetheless, doing all assignments is cool, definitely possible, and in my Deep Learning course around a quarter of all students did so.