Better Informatics - Coursework Calculator

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) acp: Applied Cloud Programming 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 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 ccs: Computational Cognitive Science cdi1: Case Studies in Design Informatics 1 cdi2: Case Studies in Design Informatics 2 cggs: Computer Graphics: Geometry and Simulation cgr: Computer Graphics: Rendering cic: Computing in the Classroom cns: Computational Neuroscience comn: Computer Communications and Networks csai: Case Studies in AI Ethics (CSAI) csec-10: Computer Security csec-11: Computer Security (Level 11) ct: Compiling Techniques dbba: Data-driven Business and Behaviour Analytics diss: MSc Dissertation (Informatics) diss-dsti-dl: Data Science, Technology and Innovation Dissertation (Distance Learning) dmp: Discrete Mathematics and Probability eip: Entrepreneurship and Innovation Project epl: Elements of Programming Languages exc: Extreme Computing fnlp: Foundations of Natural Language Processing fv: Formal Verification hci: Human-Computer Interaction (Level 11) iaml-dl: Introductory Applied Machine Learning (Distance Learning) iaml-pg2: Introductory Applied Machine Learning (Semester 2) idb: Introduction to Databases iel-08: Informatics Experiential Learning (Level 8) 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) iqc: Introduction to Quantum Computing irr: Informatics Research Review itcs: Introduction to Theoretical Computer Science ivc: Image and Vision Computing kg: Knowledge Graphs mci: Methods for Causal Inference mcs: Modelling Concurrent Systems (Level 11) mcs-10: Modelling Concurrent Systems (Level 10) 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 moss: Modelling of Systems for Sustainability 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-11: Natural Language Understanding, Generation, and Machine Translation os: Operating Systems pdiot: Principles and Design of IoT Systems pi: Professional Issues (Level 10) pmr: Probabilistic Modelling and Reasoning ppls: Parallel Programming Languages and Systems (Level 11) proj: Honours Project (Informatics) proj-ga: Honours Project (Data Science Graduate Apprenticeship) psml: Privacy and Security with Machine Learning qcs: Quantum Cyber Security qps-11: Introduction to Quantum Programming and Semantics ra: Randomized Algorithms rl: Reinforcement Learning rmfc: Research Methods in Financial Computing scm: Seminar in Cognitive Modelling scsd: Standards Compliant Software Development sdm: Software Design and Modelling sdp: System Design Project seng: Security Engineering sp: Secure Programming st: Software Testing tspl: Types and Semantics for Programming Languages ttds: Text Technologies for Data Science usec: Usable Security and Privacy wbppc: Work-Based Professional Practice C in Data Analytics drps

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