This module equips students with the skills to analyse large datasets and develop machine learning (ML) models for predictive analytics. Students are able to use both classical ML and deep learning models, and explore a variety of data-related challenges you may be facing. Master's level students in groups of 2-3 will analyse your company data set(s), perform exploratory data analysis (EDA), feature engineering and other techniques to build a model, evaluate its performance, make refinements and communicate the business-related findings to you in a short presentation. While we make every effort to align student interests with your project needs, we cannot guarantee project selection. Final confirmation of participating students will be provided by the last week of October or first week of November.

This work placement offers an introduction to real-life translation situations in the setting of a Language Service Provider (LSP). It constitutes a structured period of work-based learning which has been shown to help postgraduate students develop a wide range of generic work-related skills such as problem-solving, analytical and critical thinking, team working, communication skills, personal development skills, planning, and organizational skills, etc. In addition, students are given the opportunity to develop their professional competence as translators (and by extension as proof-readers, revisers, editors, project managers, etc.) in a working environment, benefiting from mentoring and support from experienced professionals. Students are available for up to 150 hours starting early January 2026 – May 2026. Unpaid for credit experience. Honorariums and Stipends welcome.  IMPORTANT: TIMELINE INFORMATION  Please mind that May 15th is the latest time when a project can start.   Students are available for up to 150 hours starting late January – May 2026. We currently support the following language combinations: Translation from English into French and from French into English Translation from English into Spanish Translation from English into Chinese Translation from English into Italian

The Charities and Social Enterprise Clinic (CSEC) builds on London Metropolitan University’s long-standing connection with London’s Voluntary, Community and Social Enterprise (VCSE) sector. Through the CSEC, charities and social enterprises can connect with our students, who are engaged across a wide range of applied modules, including community development, digital communications, business administration, media production, technology, and teaching support. Always keen to gain experience and make an impact, our hard-working, connected, and informed students (supervised by London Met academic tutors) can help you develop your organisation while gaining professional skills. Areas of practice covered by placements include: Digital Media Web design/development Social Media Media production (film/video, documentary, journalism) Digital communications & and Strategy Community development & engagement Data science and analytics

These Health and Social Care students are in their 2nd year of undergraduate study, bringing a strong mix of academic knowledge and practical experience. They have developed skills in research, public health, and human sciences, with exposure to labs, live research, and ethical decision-making. Many also have hands-on experience as care assistants, nurses, or in residential care settings, alongside transferable skills gained through retail and customer-facing roles. What they offer to companies: Research and data analysis to support evidence-based decision making Insights in public health, social care, and community engagement Contributions to projects focused on diversity, equity, and inclusion Support in applied healthcare settings, from health promotion to patient care pathways A developing professional skill set, with enthusiasm, adaptability, and commitment to teamwork Employers can expect learners who are motivated, adaptable, and ready to apply their 2nd-year university learning in practical settings to deliver meaningful outcomes. Course Module: Here