# Better Informatics

## Where is my course?

Each course is put in a folder with the year that Informatics lists the course to be run for. You can view all courses and their associated years at course.inf.ed.ac.uk.

## Sharing

When you share a link (see types of links below), only people who are added to the Better Informatics Team Drive have access.

Type Example URL

If you share one of the above links directly, users without access will be presented with the below interface:

This is bad! There is an automated system to add users to the Team Drive.

You can just click the link at the top, and this will just prompt you to log in and associate your Informatics DICE account (to prove you’re an inf student) with a Google account (to use Google Drive).

If you would like to directly send a link to someone in a group chat… copy the bolded bit in the URLs above and paste it in the section indicated below by ID_HERE:

https://betterinformatics.com/drive?next=ID_HERE


For example, the following URL https://drive.google.com/drive/u/0/folders/0AIKEqWfeWuQQUk9PVA would produce https://betterinformatics.com/drive?next=0AIKEqWfeWuQQUk9PVA.

(todo: replace these annoying instructions with a little edit box that auto-converts it for you)

## Statistics

As of 2020-02-04 we had 2025 users registered on our Google Drive. We may have had more registrations, but that’s the number of people who hadn’t removed themselves from the drive at the time. On this day we reset the entire list and requested people to rejoin. This is so that they change this setting.

## Thank you

Thank you to all these contributors for contributing to the website. And many more who have contributed to the Team Drive.

Thank you to TARDIS for hosting this website. And thanks to for hosting files.

### General handbook Edit on GitHub

don’t stress yourself out too much, first year doesn’t count towards your degree

### General guide, mailing list archives Edit on GitHub

• Honours hurdles: refer to your DRPS programme
• InfBase: a drop in helpdesk for you to get additional tutoring and support with your courses. See the schedule here - there’s no need to sign up, just drop in

### Honours Project | drps, info Edit on GitHub

• You can manage citations with JabRef or Zotero
• Use DBLP to generate .bib citations over Google Scholar
• Write your Intro, Conclusion and Abstract last — your project might change by the time you’ve written everything else.
• Introduction: Similar in that you want to be general, but you have more space. You need to talk about the Motivation, Objective, Contribution and Organisation.
• Conclusion: An overview of the project and your results. You’ll want to have “Critical evaluation of own work” in here and also discuss how the project has helped you (the latter isn’t in the marking scheme however was advised to include this).
• Ask your supervisor if you can use “I” and what tense to use. My supervisor banned “I” and mandated past tense, YMMV.
• Outstanding undergraduate projects - Recent dissertations which have scored 80% and above.
• A Template-based Model for Automatic Image Description (2014), feedback, with Mirella Lapata (83%)
• WILDEBEAST: A webservice for real time characterisation of infectious disease epidemics, supervised by Andrew Rambaut (80%)

### INF2D - Reasoning and Agents | drps, info, papers April/May exam Edit on GitHub

50% closed book exam, 30% across two courseworks, 20% tutorial / engagement. Pass: 40% overall

2014

### COMN - Computer Communications and Networks | drps, info April/May exam Edit on GitHub

• See shared drive for some unofficial solutions.
• Textbook in shared drive here
• Video explaining CRC calculation - link
• Wiki explaining CRC calculation - link
• Revision notes by Ben Shaw
• https://web.archive.org/web/20081209125106/http://www.ee.ryerson.ca/~courses/cn8800/solutions/Ch7.pdf

### Cognitive Science | drps, info April/May exam Edit on GitHub

All of the readings are examinable, but if you want to prioritise, here is the recommended order:

• Chapters 1, 2, 3, 4 and 7 of Pinker’s “Words and Rules”, minus places where there’s no relevance to lecture content
• Chapter 4 of Harley’s “Psychology of Language”
• Any academic paper covering something you’re not sure you fully understand. For example, if you’re not 100% clear on perceptrons, have a look at the Gurney reading

### DME | drps, info Edit on GitHub

The discussion of papers on http://nb.mit.edu

2015 Paper Discussions Here

### DS Edit on GitHub

Aggregated solutions to questions from 2009-2012 combined here

We’ve started some notes on the course content, they can be found here.

Tree mapping to the slides here.

### Discrete Math and Probability drps, drive Edit on GitHub

DMMR and PwA has been merged to form this new course, DMP is now solely based on coursework but you can find information about past papers here.

Online (flipped-classroom) version of this course. 10x better than the lectures.

Exam type: 100% Coursework.

Discrete Mathematics:

Probablity

### FNLP - Foundations of Natural Language Processing Edit on GitHub

• (2019-20) Bora’s Notes
• See shared drive for past papers and solutions. Addtional resources on discourse coherence:
• http://homepages.inf.ed.ac.uk/alex/papers/iwcs4.pdf
• https://www3.cs.stonybrook.edu/~ychoi/cse507/slides/06-discourse.pdf
• All slides (2014) in one pdf
• 14/15 slides rough summary: here (Directly exported from org-mode, so algorithms and formulas are largely missing)

### IAR Edit on GitHub

Revision notes 2014 - collective effort

Revision notes

### INF2-FDS - Foundations of Data Science | drps, info Edit on GitHub

(New course: Details are sparse. Please contribute!)

50% coursework, 50% exam.

### INF2B - Learning Edit on GitHub

75% closed book exam, 25% across two courseworks. Pass: 40% overall.

coursework

Buddy system

### Object Oriented Programming | drps, info Edit on GitHub

the key to passing is practicing

• The exam is 2 hours. It used to be 3 hours in previous years. They will not pressure you for time, don’t worry.
• There is a mock exam in week 11.
• All code must compile for ANY credit at all. If you miss a single semicolon, you get 0 marks. Trip-check if it compiles and is the right file before submitting!
• Your code must also pass the very basic tests (JUnit tests, these will be provided in the exam for you to check) to get any credit at all.

### PMR Edit on GitHub

Exam + Solutions:

### Proofs and Problem Solving Edit on GitHub

• Printable notes with all of the course material
• Twelvefold way for combinatorics problems.
• The course will follow the book A Concise Introduction to Pure Mathematics, by Martin Liebeck, 4th Ed. 015, CRC Press, £25.99
• To pass the course you must achieve an average of more than 40% AND at least 40% in the examination.
• Cheatsheet with all the notations, definitions, theorems, propositions, and examples from the textbook (condensed into 38 pages) grouped by sections: pdf, source

### SDP - System Design Project | drps, info Edit on GitHub

• Project has changed as of 2017/18:
• no competitiveness
• no robots playing football, instead designing an assistive robotic device
• more details TBC

### TTDS - Text Technologies in Data Science | drps, info, papers April/May; April/May exam Edit on GitHub

Crowdsourced solutions

There are some “hidden” formulas about LSH error probabilities in the lectures.

An overall studyguide for TTS 2013-2014: all lecture slides summarized added things from notabene, said in lecture, and just figured out by Sophia.

Topic history

* means that this has ALL THREE OPTIONAL QUESTIONS
† means that the course is TTS and not TTDS (very old course!)

Exam Question 1 Question 2 Question 3
2019 May Knowledge Retrieval Models & Web IR Evaluation
2018 May* Knowledge Retrieval Models IR Evaluation & PageRank
2017 December* Knowledge Retrieval Models IR Evaluation
2015 May* Retrieval Models Evaluation PageRank & HITS