Coursework Calculator
If you want to see how much you need in your exam to get 40% overall, first:
Select your course.
Click calculate me! next to "Exam"
Fill in how much you got in your coursework (in x%).
Fill in 40
in the "Overall" field
The "Exam" field should now tell you how much you need in your exam to get 40% overall.
Calculator
Select course:
(select a course)
adbs: Advanced Database Systems
ads: Algorithms and Data Structures
agta: Algorithmic Game Theory and its Applications
aml: Applied Machine Learning
anlp: Accelerated Natural Language Processing
ar: Automated Reasoning
aro: Advanced Robotics
asr: Automatic Speech Recognition
bai-gp: Group Research Project (Biomedical AI)
bai-icdm: Issues in Clinical Data Modelling
bai-ip: Individual Research Project (Biomedical AI)
bdl: Blockchains and Distributed Ledgers
bio1: Bioinformatics 1
card: Computer Architecture and Design
ccn: Computational Cognitive Neuroscience
ccs: Computational Cognitive Science
cdi1: Case Studies in Design Informatics 1
cdi2: Case Studies in Design Informatics 2
cg: Computer Graphics
cic: Computing in the Classroom
cns: Computational Neuroscience
comn: Computer Communications and Networks
cqi: Categories and Quantum Informatics
cs: Computer Security
csai: Case Studies in AI Ethics (CSAI)
ct: Compiling Techniques
dbba: Data-driven Business and Behaviour Analytics
diss: MSc Dissertation (Informatics)
diss-dsti-dl: Data Science, Technology and Innovation Dissertation
dmp: Discrete Mathematics and Probability
epl: Elements of Programming Languages
exc: Extreme Computing
fnlp: Foundations of Natural Language Processing
hci: Human-Computer Interaction
iaml-dl: Introductory Applied Machine Learning
iaml-pg2: Introductory Applied Machine Learning (Semester 2)
idb: Introduction to Databases
iel-08: Informatics Experiential Learning
iel-10: Informatics Experiential Learning (Level 10)
ilp: Informatics Large Practical
imc: Introduction to Modern Cryptography
inf1-cg: Informatics 1 - Cognitive Science
inf1a: Informatics 1 - Introduction to Computation
inf1b: Informatics 1 - Object Oriented Programming
inf2-fds: Informatics 2 - Foundations of Data Science
inf2-iads: Informatics 2 - Introduction to Algorithms and Data Structures
inf2-sepp: Informatics 2 - Software Engineering and Professional Practice
inf2c-cs: Informatics 2C - Introduction to Computer Systems
inf2d: Informatics 2D - Reasoning and Agents
ipp: Informatics Project Proposal
ipp-dl: Informatics Project Proposal (Distance Learning)
ipp-ga: Informatics Project Proposal (Graduate Apprenticeship)
ippo: Introduction to Practical Programming with Objects
ippo-dl: Introduction to Practical Programming with Objects (Distance Learning)
iqc: Introduction to Quantum Computing
irr: Informatics Research Review
itcs: Introduction to Theoretical Computer Science
ivc: Image and Vision Computing
mci: Methods for Causal Inference
mdi: Masters Dissertation (Design Informatics)
mip1: MInf Project (Part 1)
mip2: MInf Project (Part 2)
mlg: Machine Learning
mlp: Machine Learning Practical
mlpr: Machine Learning and Pattern Recognition
mlt: Machine Learning Theory
mob: Introduction to Mobile Robotics
nat: Natural Computing
nat-dl: Natural Computing (Distance Learning)
nlp-dr: Doing Research in Natural Language Processing
nlp-gp: Group Project in Advanced Natural Language Processing
nlp-ip: Individual Project in Advanced Natural Language Processing
nlp-ip-80: Individual Project in Advanced Natural Language Processing (80 credits)
nlu+: Natural Language Understanding, Generation, and Machine Translation
os: Operating Systems
pdiot: Principles and Design of IoT Systems
pi: Professional Issues
pmr: Probabilistic Modelling and Reasoning
ppls: Parallel Programming Languages and Systems
proj: Honours Project (Informatics)
proj-ga: Honours Project (Data Science Graduate Apprenticeship)
qcs: Quantum Cyber Security
ra: Randomized Algorithms
rl: Reinforcement Learning
rmfc: Research Methods in Financial Computing
scm: Seminar in Cognitive Modelling
sdm: Software Design and Modelling
sdp: System Design Project
seng: Security Engineering
sp: Secure Programming
spt: Research Methods in Security, Privacy, and Trust
st: Software Testing
tspl: Types and Semantics for Programming Languages
ttds: Text Technologies for Data Science
usec: Usable Security and Privacy
wbppa: Work-Based Professional Practice A in Data Analytics
wbppb: Work-Based Professional Practice B in Data Analytics
wbppc: Work-Based Professional Practice C in Data Analytics
drps
Weighting (select course above to fill this in)
Targets (lock one, fill other two)
Last updated from course.inf.ed.ac.uk : 17/01/2023 07:30:01
Don't forget to visit drps to double check the cw/exam weighting and
check for any additional assessment info (such as a requirement to pass the exam)