University of Edinburgh

Credit where it’s due, UoE has taught me a lot.

How To Do Well at Uni (Academically):

• Learn how to learn as soon as possible.
  • Eg: Watching lectures in person is a waste of time. I absorb ~40% of information. Instead watch recordings. Take detailed notes. Ask ChatGPT for clarification on topics. Watch YouTube videos.
• Take Atomic Notes (at least this works for me.)
  • Don’t stop writing until it could explain a topic to you if you completely forget it.
• Take advantage of compound effects. Pick small things to improve (eg: notetaking method, gym routine etc.). Eventually, this all compounds positively.
• Track your time. Constantly reflect where you spent most of your time. You’ll find a lot of it is spent not actually productively working.
• Don’t charge your phone by your bedside. Don’t look at it the hour after you wake up.
• Sleep well.
• If you can take electives in your earlier years outside of your discipline, take them. I wholeheartedly regret not taking philosophy and history lectures. The best ideas come from interdisciplinary thinkers (Steve Jobs took calligraphy classes at Uni).
• Uni’s going to be tough.

Advice if I were just entering Uni:

• Locally optimise. Don’t globally optimise.
• Do things you enjoy. Join / make spaces where you’re with people who enjoy the same things. (Eg: EdinburghAI)
• You make the best friends through shared collective experiences. Go on as many trips as possible. Nights out count as ~$\frac{1}{3}$ of the equivalent time on trips.
• Avoid like the plague people who actively drain your energy. Try and be someone who energises others.
• Build as much as you possible can, and do it in public. Join groups (or start one!) that show off these sorts of projects.

University Modules:

My notes are scattered across my vault (by definition of atomic notes lol). Some have some starting points (Calculus, Computer Systems), but even they’re incomplete. The best way is just to search and click around.

Some Starting Point for Notes:

• Algorithms And Data Structures:
  • Greedy Approximation Algorithms
  • Time Complexity
• Computer Systems:
  • Memory Hierarchy
  • (MIPS) Assembly Language
• Calculus:
  • Calculus
• Computer Security:
  • ARP (Address Resolution Protocol)
  • RSA Algorithm
  • Buffer Overflow Attack

Resources:

• See tasters of all INF courses → https://opencourse.inf.ed.ac.uk
• BetterInformatics → https://betterinformatics.com