Data Science with Python
Studied practical Python-based analysis, exploratory data analysis, statistical modelling, optimisation, robust data management and reproducible scientific analysis.
Official course source ↗Academic training
Complete coursework map.
Every taught or completed module currently evidenced by the supplied records and earlier portfolio data is listed here. Descriptions are concise mappings to official Sheffield course information; no marks, rankings or pass counts are published.
32 modules shown.
Professional Issues
Studied legal, social, ethical and professional responsibilities in computing, including intellectual property, software liability, computer misuse and ethical decision-making.
Official course source ↗Text Processing
Worked with text corpora, quantitative text analysis, language representation and systems for processing large volumes of natural-language text.
Official course source ↗Machine Learning and Adaptive Intelligence
Studied statistical machine learning and probabilistic modelling, with attention to mathematical assumptions and the application of learning algorithms to real-world phenomena.
Official course source ↗Parallel Computing with Graphical Processing Units (GPUs)
Gained exposure to parallel programming concepts, GPU execution models, performance-aware implementation and the use of accelerators for computational workloads.
Official course source ↗Scalable Machine Learning
Studied parallelisation, stochastic optimisation, Spark, Python/Scala exposure and deployment concepts for high-performance or cluster computing.
Official course source ↗Natural Language Processing
Studied core NLP concepts, models and algorithms, together with their strengths, limitations and applications.
Official course source ↗Team Project
Practised team-based project scoping, requirements analysis, solution design, implementation, presentation and technical reporting.
Official course source ↗Foundations of Computer Science
Studied discrete and continuous mathematics for computing, including logic, proof, combinatorics, graphs, calculus, matrices and linear algebra.
Official course source ↗Java Programming
Developed experience in object-oriented programming with Java, program decomposition, data structures, debugging and maintainable implementation.
Official course source ↗Machines and Intelligence
Studied foundational ideas in artificial intelligence, intelligent behaviour, search, representation and the relationship between natural and machine intelligence.
Official course source ↗Devices and Networks
Studied how computing devices, operating concepts and networks support communication, computation and end-to-end digital systems.
Official course source ↗Web and Internet Technology
Worked with web architecture, client–server interaction, standards-based front-end development and the technologies underlying internet applications.
Official course source ↗Introduction to Algorithms and Data Structures
Studied algorithmic problem solving, common data structures, correctness, complexity and implementation trade-offs.
Official course source ↗Global Engineering Challenge Week
Worked in an interdisciplinary team on an engineering challenge, developing problem framing, sustainable design, communication and collaborative decision-making.
Official course source ↗Automata, Computation and Complexity
Studied finite-state machines, formal languages, pushdown automata, Turing machines, computability and computational complexity.
Official course source ↗Functional Programming
Studied functional programming principles, immutable data, higher-order functions, recursion, type-driven design and reasoning about programs.
Official course source ↗Engineering – You’re Hired
Completed an intensive team exercise centred on employability, project planning, commercial awareness, communication and professional presentation.
Official course source ↗Robotics
Studied sensing, control, perception and decision-making for autonomous systems, with practical attention to how software interacts with physical environments.
Official course source ↗AI Group Project
Worked collaboratively to scope, design, implement and communicate an AI-oriented software solution, balancing technical and team requirements.
Official course source ↗Logic in Computer Science
Studied formal logic, automated reasoning, decision procedures, temporal and modal logics, verification and type-system applications.
Official course source ↗Data Driven Computing
Developed experience in extracting, cleaning, analysing and interpreting data, using computational and statistical methods to answer defined questions.
Official course source ↗Systems Design and Security
Studied secure systems design, threat-aware engineering, access control, defensive thinking and the relationship between architecture and security properties.
Official course source ↗Dissertation Project: Emotion Recognition using Visual Information
Completed an end-to-end computer-vision project covering literature review, requirements, architecture, model implementation, testing, evaluation, ethics and technical reporting.
Official course source ↗Software Development for Mobile Devices
Studied mobile application design and implementation, including platform constraints, interface design, lifecycle considerations and device-aware development.
Official course source ↗Text Processing
Studied computational methods for processing text, including corpus preparation, text representation, analysis pipelines and evaluation.
Official course source ↗Bioinspired Computing
Studied computational methods inspired by natural systems, such as evolutionary search, swarm behaviour, neural computation and adaptation.
Official course source ↗Finance and Law for Engineers
Gained exposure to financial reasoning, commercial context and legal responsibilities relevant to engineering decisions. The title follows Sheffield’s historical programme regulations.
Official course source ↗Modelling and Simulation of Natural Systems
Studied differential-equation and individual-based approaches to dynamic natural systems, including assumptions, limitations, simulation and interpretation.
Official course source ↗Theory of Distributed Systems
Studied models and reasoning techniques for concurrent and distributed computation, including coordination, communication, correctness and system-level trade-offs.
Official course source ↗Adaptive Intelligence
Studied adaptive decision-making and reinforcement-learning ideas, including agents, rewards, policies, value estimation, exploration and evaluation. The official historical title is Adaptive Intelligence.
Official course source ↗Managing Engineering Projects and Teams
Studied project planning, risk, team organisation, leadership, stakeholder communication and delivery in engineering contexts.
Official course source ↗No module matches those filters.
Accuracy note: Sheffield periodically revises curricula and module titles. The descriptions use official course pages or historical programme-regulation entries where available. MGT388 and COM3240 use the official historical titles found in Sheffield regulations; this avoids treating an informal label as the formal module name.