Electricity and Magnetism

• Basic definitions of current, voltage and power.
• Principles of electricity: voltage and current sources, resistors, capacitors.
• Principles of magnetism: magnetic field, magnetic forces, inductors.
• DC circuits: Ohm’s Law, Kirchhoff’s Laws, Norton and Thevenin equivalent circuits with voltage and current source transformations. Steady state and transient (switching) DC circuit analysis. Analysis by nodal and loop methods. Superposition Theorem. Power.
• AC Circuits: Sinusoidal signals, amplitude, frequency and phase. Complex notation, Ohm’s Law, Kirchhoff’s Law and Norton and Thevenin equivalent circuits generalised to impedance and admittance. Steady state AC circuit analysis and phasor diagrams. Frequency response for RC, RL and RLC circuits. Resonance for RLC circuits. Superposition Theorem and Single Phase AC power.
• Measurement and Test Equipment: Meter Loading effects for voltage and current measurement. Use of multimeters, oscilloscopes, power supplies and signal generators in the laboratory.

Analogue Electronics

• Semiconductors: Semiconductor doping, electron and hole transport. The device physics of a p-n junction in forward and reverse bias.
• Diodes: diode equation, graphical/load line analysis, diode models. Zener and light emitting diodes. Diode circuits including rectifier, peak sample, power rectifier, clamps and regulator.
• Bipolar Junction Transistors (BJT): BJT structure, basic BJT operation, BJT characteristics and parameters, BJT amplifiers and BJT switching applications.
• Field effect transistors (FET): FET characteristics and parameters, FET biasing, FET amplifiers and FET switching applications.
• Operational amplifiers: Concept of an ideal operational amplifier and its practical realisation, design of inverting, non-inverting, summing and differential amplifiers.

Digital Electronics

• Number systems: decimal numbers, binary numbers, decimal-to-binary conversion, binary arithmetic, 2’s complements of binary numbers, hexadecimal numbers.
• Logic gates: the Inverter, AND, OR, NAND, NOR, Exclusive-OR and Exclusive-NOR.
• Logic fundamentals: Boolean algebra and logic simplification, Karnaugh map, De Morgan’s law.
• Combinational logic analysis: basic combinational logic circuits, implementing combinational logic, the universal property of NAND and NOR gates, combinational logic using NAND and NOR gates.
• Basic sequential logic circuits: Latches, S-R Flip-Flop, D Flip-Flop, J-K Flip Flop, registers.

This is an experiential learning opportunity that incorporates, 20 teaching contact hours/lectures to prepare for the150 contract hours where L5 students can use all their skills learned to date on an actual real-world (external business) client driven project, working in teams and produce an artefact. 

Students are also expected to undertake around 30 hours of self study.

This module not only gives them enhanced skills but the opportunity to work for a real client thus giving them a valuable CV and LInkedIn entry as work experience that can contribute to their employability portfolio. 

Students will collaborate in teams and produce full client documentation alongside a reflection of their expereince and this all give some much needed contemplation of their skills to date and how to use them. 

This module provides a structured, university-level work placement for 4, 5 or 7 weeks as one continuous block / period with a placement provider (i.e. industry apprioprate sector). It is designed to enhance your professional skills in a real-world job setting.

The placement can either be organised by you or with support from university staff.

All work placements within this module must be university-level; this means:

• Undertaking high-skilled work commensurate with level 5 study (e.g. report writing, attending meetings, delivering presentations, producing spreadsheets, writing content on webpages, social media, marketing services/products etc)
• Physically placed (albeit part of it can be hybrid) within an employer setting in one continuous block / period for 4, 5 or 7 weeks for a minimum of 140-147 hours over the course of the entire work placement

Where applicable, your existing part-time employer can be approached/used as the placement provider, if the high-skilled work.

• criterion above is fulfilled for the full duration of the placement.
• All quality assurances/agreements provided by the University are adhered to, by you and the employer.

The work placement context may not necessarily, reflect your degree discipline per se, but rather, it will give you an enriched experience to enhance your professional skills in a real-world job setting.

The Level 5, 40-credit modules require a basic foundation of knowledge of your chosen language e.g. GCSE or equivalent,  a Level 4 module in the same language or equivalent previous learning. This module includes an optional placement abroad, such as an intensive course at a partner university. You can choose:

• Advanced Language Development and Global Sustainability (choice of German, French or Spanish)
• Upper Intermediate Language Development and Global Employability (choice of Chinese, French or Spanish)
• Post Beginner Language Development and Global Cultures (choice of German, Italian or Spanish)

The module introduces students to the basics of static websites - their structure (HTML), aethetics (CSS) and interactivity (JavaScript). It also introduces the kep protocol of the web (HTTP) and use of it's key verbs to make requests.

Students will be taught how websites compliant with HTML and CSS document standards, as well as being accessible, as defined by the Web Content Accessibility Guidelines (WCAG).

Students will also be introduced to various associated technolohies, such as IDEs, FTP clients and introduced to DevOps processes.

Students will then be introduced to mechanisms for developing dynamic websites through the development of server-side applications which utilise a database (i.e. full-stack development).

This module provides a comprehensive introduction to data analytics, focusing on foundational concepts and practical applications. Students will develop essential skills to analyse data, solve real-world problems, and explore the rapidly growing field of big data analytics. The key perspectives are:

• Introduction to the data analytics process, including data collection, cleaning, analysis, visualisation, and interpretation.
• Hands-on experience with data analytics tools and techniques.
• Exploring big data analytics concepts, including scalable data processing and analysis.
• Promoting ethical decision-making and effective communication in data-driven contexts.

The data analytics process covers :

• Identifying business problems and defining objectives.
• Collecting and cleaning raw data for analysis.
• Performing exploratory data analysis (EDA) to uncover patterns.
• Visualising and interpreting results to derive actionable insights.

The statistical and analytical thinking aspect includes: 

• Measures of central tendency and dispersion.
• Regression analysis and correlation.
• Data modelling and simulation.

The tools and techniques component covers:

• cleaning and preprocessing using Python or R.
• SQL for querying and managing databases.
• Data visualisation using tools like Tableau, Power BI, Matplotlib and Apache Superset
• Introduction to big data ecosystem.

The big data analytics aspect addresses:

• Scalable data storage and processing.
• Analysing large datasets with distributed systems.
• Leveraging machine learning for big data insights.
• Real-time analytics and stream processing.

The ethical and professional skills aspect encompasses:

• Ethical issues in data privacy and security.
• Effective communication of data insights through storytelling.
• Collaboration and teamwork in data projects.
• Presentation and reporting of analytics outcomes.