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Discover courses across every level โ from primary school to professional development.
1,187 courses available
Cyber Security
Cryptography Principles (Year 2)
Introduces the mathematical and practical foundations of cryptography, covering symmetric and asymmetric encryption, hashing, and digital signatures.
Cyber Security
Security Risk Assessment (Year 2)
Covers the process of identifying, analysing, and prioritising information security risks within an organisation, forming the basis for risk-based security decision-making.
Cyber Security
Ethical Hacking and Penetration Testing Concepts (Year 2)
Introduces the methodology and concepts behind authorised penetration testing, covering reconnaissance, vulnerability identification, and reporting within an ethical and legal framework.
Cyber Security
Security Policy and Governance (Year 2)
Covers the development and implementation of organisational security policies and governance frameworks that align security practice with business objectives.
Data Science
Statistical Methods for Data Science (Year 2)
Covers the statistical foundations essential to data science practice, from probability distributions through to hypothesis testing and regression.
Data Science
Data Structures and Algorithms (Year 2)
Covers the fundamental data structures and algorithms used to write efficient programs, forming the computational foundation for data science work.
Data Science
Database Systems for Data Science (Year 2)
Covers relational and non-relational database systems used to store and retrieve the data that data science workflows depend on.
Data Science
Data Visualization (Year 2)
Covers the principles and tools used to communicate data insights effectively through visual representation, from chart selection to dashboard design.
Data Science
Introduction to Machine Learning (Year 2)
Introduces the core concepts and algorithms of machine learning, covering supervised and unsupervised learning and how models are evaluated.
Artificial Intelligence
Machine Learning Fundamentals (Year 2)
Introduces the core algorithms and evaluation methods of machine learning, forming the foundation for the more advanced AI coursework that follows.
Artificial Intelligence
Knowledge Representation and Reasoning (Year 2)
Covers the classical AI methods for representing knowledge and reasoning over it, including logic-based representation and rule-based systems.
Artificial Intelligence
Search and Optimization Algorithms (Year 2)
Covers the search and optimisation algorithms that underpin many AI systems, from uninformed search through to heuristic and evolutionary methods.