Chapter 2 General Advice

There is no one best way to approach the course. This is a theme in the program. There is no template for research, education, or life. Each problem is unique and has multiple possible solutions.

Personalized medicine is a dominant theme in healthcare. Take asthma as an example. Historically, asthma was a single diagnosis but with multiple types of triggers and syptoms (a heterogeneous disease). Recently, a subtype has been identified: eosinophilic asthma. Those suffering from this subtype of asthma has previously been given a treatment that worked for the majority of asthma patients (which are different from). This treatment would not work due to their differing disease causes. A more personalized medicine could then be designed for their new, more precise diagnosis.

Personalized education is a dominant theme in HDA. Not all of the optional courses will be necessary for each student. Due to the wide range of next steps the students take, not all of the course weeks are not directly related where they end up. There may be material we do not cover that is relevant to where a student would like to end up. The program can only be personalized through structural procedure so much - the rest is up to you. Use the program as practice. After this course, you will have to personalize your growth completely. Start your personalized education journey with prep material - identify which areas you need to focus on and design a personal plan up to induction week.

Nothing learned is wasted. This course provides a multifaceted skill set that will help in any future career path. A project manager can better manage their team if they are familiar with programming fundamentals; A data scientist is more efficient if they know project management fundamentals; A data engineer benefits from understanding how to take a rigorous scientific approach; A research scientist needs to understand how to write scalable, reproducible code. We ask that you embrace every element of the course, even if it does not appear to directly relate to your future career. By becoming a multifaceted agile thinker, you will stand out in whatever field you go into. Your task is develop a core competency in all of the subjects while identifying those that you would like to go deeper into for your next step.

Our students have a highly diverse range of backgrounds. There will always be some students with very little experience of each particular subject. Don’t panic if you have a classmate with a PHD in molecular biology and you have never taken a science class. Each module in Term 1 starts with the basics which are built on in Term 2. Being more familiar with the material now will reduce any increases in difficultly throughout the program.

It is hard to learn anything completely the first time. The course is designed to introduce topics, reinforce their practical application with hands on exercises, and provide opportunties to explore specific topics in more depth with large scale real world problems. Seasoned researchers do not know every detail of every possible approach. They understand the theoretical underpinnings of the topic and have a broad understanding of what could be done. When designing a specific project, they will then go into more detail on the correct approach to use. Do not feel that you need to understand every detail of every approach in your courses. Adopt a consistent approach to learning and do not put pressure on yourself to instantly be an expert.

This is a challenging course that is designed to push you to discover your potential. While there may be moments that seem daunting, remember that other cohorts have successfully overcome the challenges and so can you. Here are a few quotes from students to keep in mind:

“One of the most valuable takeaways (personally) this year is just to be able to step into the unknown with confidence and pride” (A student about their excitement over starting their postgraduate role)

“There were times that I didn’t think I would be able to complete the course. Having finished the program I feel like I can do anything” (A student who scored a Distinction)

“If you had told me what I was going to do in my summer project at the start of the course, I wouldn’t have believed you.” (A student reflecting on their AI summer project having come into the program not knowing how to code)

2.1 Advice from the Teaching Team

Be proactive. This is your learning journey. We will provide the structure and support, but you need to take the initiative.

Be engaged. Use discussion board, come to Q&A with questions, engage with your teaching team, come to class and engage with your peers, and give the projects your best effort.

Be purposeful. Try to identify achievable goals. Have study sessions with an achievable target in mind. Be conscious of what research decisions you are making.

Take risks. You have the chance to get detailed, instructive and honest feedback for maybe the last time in your life. Don’t design projects to be as easy as possible or to be safe in order to get a high grade. Explore your research ideas and take on difficult projects so that the first time you have to struggle isn’t when you have no help.

2.2 Advice from previous HDA students

We asked former students of the HDA course what advice they would give their past selves before starting the course. Their responses are below.

2.2.1 Before starting the course

  • If you have questions, ask! Never be afraid of being curious!
  • Don’t be disheartened when you don’t have a clue what’s happening in R or python if you have zero prior coding experience - it’s a steep learning curve but you’ll pick it up. Coding is the sort of thing where there’s a certain level of understanding beyond which everything just seems very understandable, and before that level it just seems super overwhelming. Just the ability to understand the syntax in R and the different nuances etc gives you the ability to understand and search every problem on stack overflow. You don’t need to know a load of functions off by heart.
  • If possible, do some of the data camp courses BEFORE starting the MSc
  • Take an intro linear algebra course and don’t just rely on the math refreshers

2.2.2 Throughout the course

  • Organise and document everything during projects: scripts, data, notes etc. You will definitely revisit old code and old notes
  • Be proactive, ask question and use the resources that are made available to you (the people around you and the lecturers)
  • Keep your notes and code organised, I kept referring back to past tutorials in the project, and having a filing system from the beginning of the project made this so much quicker.
  • Don’t think you’re the only one who doesn’t understand something. There’s a huge range of pre-existing skills and knowledge in the other people in the class and inevitably you’ll know less about some stuff and more about other stuff than your pals
  • Especially with the wide range of skill sets in the program, whenever I didn’t get something I knew at least a quarter of our program did and had to fight my self consciousness to ask the question. Also lecturers are really nice I would have asked a few more questions had I not been worried about looking like an idiot
  • Get to know the people on the course and work with them – everyone has different strengths and will pick things up at different rates and it really helped this year working together to understand things.
  • Capitalise on your classmates’ knowledge! It’s a nice symbiotic relationship
  • Start projects earlier.
  • Revise the second term lectures such that there are some baby steps leading to the big equations
  • Summer quarter advice - make sure they have data you want to work with.
  • Advice for the thesis: get your references and stuff organised and maybe don’t wait too much before writing some stuff.