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 Databases ads: Algorithms and Data Structures afds: Algorithmic Foundations of Data Science agta: Algorithmic Game Theory and its Applications aipf: Artificial Intelligence, Present and Future anlp: Accelerated Natural Language Processing apl: Advances in Programming Languages ar: Automated Reasoning asr: Automatic Speech Recognition atfd: Advanced Topics in Foundations of Databases av: Advanced Vision bdl: Blockchains and Distributed Ledgers bio1: Bioinformatics 1 bio2: Bioinformatics 2 ca: Computer Algebra 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 cmc: Computational Complexity comn: Computer Communications and Networks copt: Compiler Optimisation cp: Computer Programming Skills and Concepts cs: Computer Security ct: Compiling Techniques dbs: Database Systems diss: MSc Dissertation (Informatics) diss-dsti: Data Science, Technology and Innovation Dissertation (Distance Learning) dme: Data Mining and Exploration dmmr: Discrete Mathematics and Mathematical Reasoning dmr: Decision Making in Robots and Autonomous Agents epcc/01: Advanced Message-passing Programming epcc/02: Advanced Parallel Techniques epcc/03: Data Analytics with High Performance Computing epcc/04: Design and Analysis of Parallel Algorithms epcc/05: Dissertation (DSTI - EPCC) (Distance Learning) epcc/06: Dissertation (HPC with Data Science) epcc/07: Dissertation (High Performance Computing) epcc/08: Fundamentals of Data Management epcc/09: HPC Architectures epcc/10: Message-passing Programming epcc/11: Numerical Algorithms for High Performance Computing epcc/12: Parallel Design Patterns epcc/13: Performance Programming epcc/14: Practical Introduction to Data Science (Distance Learning) epcc/15: Practical Introduction to High Performance Computing (Distance Learning) epcc/16: Programming Skills epcc/17: Project Preparation epcc/18: Software Development epcc/19: Threaded Programming exc: Extreme Computing fnlp: Foundations of Natural Language Processing hci: Human-Computer Interaction iaml: Introductory Applied Machine Learning iaml-dl: Introductory Applied Machine Learning (Distance Learning) iaml-pg: Introductory Applied Machine Learning ijp: Introduction to Java Programming ijp-dl: Introduction to Java Programming (Distance Learning) ilp: Informatics Large Practical imc: Introduction to Modern Cryptography inf1-cg: Informatics 1 - Cognitive Science inf1-da: Informatics 1 - Data and Analysis inf1-op: Informatics 1 - Object-Oriented Programming inf1a: Informatics 1 - Introduction to Computation 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 ivc-dl: Image and Vision Computing (Distance Learning) 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 and Pattern Recognition nat: Natural Computing nat-dl: Natural Computing (Distance Learning) nc: Neural Computation nip: Neural Information Processing nlu+: Natural Language Understanding, Generation, and Machine Translation os: Operating Systems pdiot: Principles and Design of IoT Systems perp: Pervasive Parallelism pi: Professional Issues pm: Performance Modelling (Level 11) 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 sdm: Software Design and Modelling sdp: System Design Project sp: Secure Programming st: Software Testing stn: Social and Technological Networks thf: The Human Factor: Working with Users tspl: Types and Semantics for Programming Languages ttds: Text Technologies for Data Science usec: Usable Security and Privacy drps

• Coursework: %
• Exam: %

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