Coursework Calculator

Notes:

• Last updated from course.inf.ed.ac.uk: 11/05/2018 07:45:01
• If course.inf.ed.ac.uk counts "exam%" to be the total of written exam% and practical exam%, then this does too.
• Disabled fields are missing data on the "Work%/Exam%" column on course.inf.ed.ac.uk
• Selecting a course (optional) will:
  • automatically fill in the cw/exam weighting
  • link you to drps
• Don't forget to visit drps to:
  • double check the cw/exam weighting
  • check for any additional assessment info (such as a requirement to pass the exam)
• Instructions. 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 Databases ads: Algorithms and Data Structures agta: Algorithmic Game Theory and its Applications ailp: AI Large Practical ale1: Adaptive Learning Environments 1 anlp: Accelerated Natural Language Processing ar: Automated Reasoning asr: Automatic Speech Recognition atfd: Advanced Topics in Foundations of Databases av: Advanced Vision av-dl: Advanced Vision (Distance Learning) bdl: Blockchains and Distributed Ledgers bio1: Bioinformatics 1 bio2: Bioinformatics 2 ca: Computer Algebra car: Computer Architecture cav: Computer Animation & Visualisation ccn: Computational Cognitive Neuroscience ccs: Computational Cognitive Science cd: Computer Design cdi1: Case Studies in Design Informatics 1 cdi2: Case Studies in Design Informatics 2 cg: Computer Graphics cmc: Computational Complexity cn: Computer Networking comn: Computer Communications and Networks copt: Compiler Optimisation cp: Computer Programming Skills and Concepts cqi: Categories and Quantum Informatics cs: Computer Security cslp: Computer Science Large Practical ct: Compiling Techniques dbs: Database Systems diss: MSc Dissertation (Informatics) dme: Data Mining and Exploration dmmr: Discrete Mathematics and Mathematical Reasoning dmr: Decision Making in Robots and Autonomous Agents ds: Distributed Systems epl: Elements of Programming Languages exc: Extreme Computing fnlp: Foundations of Natural Language Processing fv: Formal Verification hci: Human-Computer Interaction iaml: Introductory Applied Machine Learning iaml-dl: Introductory Applied Machine Learning (Distance Learning) iar: Intelligent Autonomous Robotics ijp: Introduction to Java Programming ijp-dl: Introduction to Java Programming (Distance Learning) imc: Introduction to Modern Cryptography inf1-cg: Informatics 1 - Cognitive Science inf1-cl: Informatics 1 - Computation and Logic inf1-da: Informatics 1 - Data and Analysis inf1-fp: Informatics 1 - Functional Programming inf1-op: Informatics 1 - Object-Oriented Programming inf2a: Informatics 2A - Processing Formal and Natural Languages inf2b: Informatics 2B - Algorithms, Data Structures, Learning inf2c-cs: Informatics 2C - Introduction to Computer Systems inf2c-se: Informatics 2C - Introduction to Software Engineering inf2d: Informatics 2D - Reasoning and Agents iotssc: Internet of Things Systems, Security, and the Cloud (IoTSSC) ipp: Informatics Project Proposal iqc: Introduction to Quantum Computing irds: Introduction to Research in Data Science irr: Informatics Research Review itcs: Introduction to Theoretical Computer Science ivc: Image and Vision Computing ivr: Introduction to Vision and Robotics ivr-dl: Introduction to Vision and Robotics (Distance Learning) mdi: Masters Dissertation (Design Informatics) mi: Music Informatics mip1: MInf Project (Part 1) mip2: MInf Project (Part 2) mlp: Machine Learning Practical mlpr: Machine Learning & Pattern Recognition mt: Machine Translation nc: Neural Computation nip: Neural Information Processing nlu: Natural Language Understanding os: Operating Systems pa: Parallel Architectures pdiot: Principles and Design of IoT Systems perp: Pervasive Parallelism pi: Professional Issues pm: Performance Modelling pmr: Probabilistic Modelling and Reasoning ppls: Parallel Programming Languages and Systems proj: Honours Project (Informatics) rasrt: Robotics and Autonomous Systems Research Thesis rc: Randomness and Computation rl: Reinforcement Learning rlsc: Robot Learning and Sensorimotor Control rss: Robotics: Science and Systems rtds: MSc by Research Thesis (Data Science) rtds+: MSc by Research Thesis (Data Science; 120pt) rtpp: MSc by Research Thesis (Pervasive Parallelism) sapm: Software Architecture, Process, and Management sdp: System Design Project selp: Software Engineering Large Practical sp: Secure Programming st: Software Testing stn: Social and Technological Networks thf: The Human Factor: Working with Users tnlp: Topics in Natural Language Processing tspl: Types and Semantics for Programming Languages ttds: Text Technologies for Data Science drps

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• Exam: %

• Exam: %
• Coursework: %
• Overall: %