473 Research courses in Cardiff delivered Live Online

Develop your technical report writing and presentation skills with EnergyEdge's course designed for oil & gas professionals. Sign up now!

Bunnyfoot were the pioneers and are now one of the leading providers of the Certified Professional for Usability and User Experience – Foundation Level (CPUX-F) in the United Kingdom. Created in association with the international UXQB, this professional 3-day UX certification programme covers user experience methods and theories – and is independently assessed/certified.

Certificate in SEO Content Writing Course Overview This Certificate in SEO Content Writing equips learners with the essential knowledge and skills to create compelling, search-engine-optimised content that drives online visibility and engagement. The course covers key principles of content writing, SEO fundamentals, keyword research, and effective writing techniques to attract and retain readers. Learners will develop an understanding of how to craft content that meets both audience needs and search engine criteria, enhancing website rankings and digital marketing success. Upon completion, participants will be confident in producing high-quality, SEO-friendly content tailored to diverse platforms and industries, enabling them to advance in digital marketing or content creation roles. Course Description This comprehensive course explores the full spectrum of SEO content writing, starting with foundational concepts of content creation and progressing through advanced SEO strategies. Topics include writing saleable content, mastering keyword research, optimising meta tags, and understanding off-page SEO factors. Learners will gain insight into engaging readers effectively and making any piece of writing SEO-friendly without compromising quality. The learning experience balances theory with structured guidance on writing processes, text objectives, and article rewriting techniques. By the end, learners will possess a robust skill set applicable to roles in digital marketing, copywriting, and content management, equipped to produce content that enhances online presence and supports business goals. Certificate in SEO Content Writing Curriculum Module 01: What Is Content Writing? Module 02: How To Write Saleable Content Module 03: The Importance of SEO Based Content Writing Module 04: Basics of SEO Module 05: Essential SEO Skills for Content Writers Module 06: How to Engage the Reader? Module 07: Search Engine Optimization Process Module 08: Off Page SEO Module 09: Meta Tags Optimization Module 10: The Importance of Keyword Research Module 11: Keyword Strategy Module 12: How to Make Any Content SEO-Friendly Module 13: The Process of Good Writing Module 14: Text Objectives Module 15: How to Rewrite an Article (See full curriculum) Who is this course for? Individuals seeking to develop skills in SEO content writing. Professionals aiming to enhance their digital marketing career. Beginners interested in digital content creation and optimisation. Freelancers wanting to expand their writing service offerings. Career Path SEO Content Writer Digital Marketing Executive Copywriter Content Strategist Social Media Content Creator Website Content Manager

Duration 2 Days 12 CPD hours This course is intended for People working in an organization aiming to improve performance, especially in response to digital transformation or disruption. Any roles involved in the creation and delivery of products or services: Leadership and CXO, especially CIO, CTO, CPO, and CVO Transformation and evolution leads and change agents Value stream architects, managers, engineers Scrum Masters, agile and DevOps coaches and facilitators Portfolio, product and project managers, and owners Business analysts Architects, developers, and engineers Release and environment managers IT Ops, service and support desk workers Customer experience and success professionals Overview After completing this course, students will be able to: Describe the origins of value stream management and key concepts such as flow, value, and delivery Describe what value stream management is, why it's needed and the business benefits of its practice Describe how lean, agile, DevOps, and ITSM principles contribute to value stream management Identify and describe value streams, where they start and end, and how they interconnect Identify value stream roles and responsibilities Express value streams visually using mapping techniques, define current and target states and hypothesis backlog Write value stream flow and realization optimization hypotheses and experiments Apply metrics such as touch/processing time, wait/idle time, and cycle time to value streams Understand flow metrics and how to access the data to support data-driven conversations and decisions Examine value realization metrics and aligning to business outcomes, and how to sense and respond to them (outcomes versus outputs) Architect a DevOps toolchain alongside a value stream and data connection points Design a continuous inspection and adaptation approach for organizational evolution The Value Stream Management Foundation course from Value Stream Management Consortium, and offered in partnership with DevOps Institute, is an introductory course taking learners through a value stream management implementation journey. It considers the human, process, and technology aspects of this way of working and explores how optimizing value streams for flow and realization positively impacts organizational performance. History and Evolution of Value Stream Management and its Application Value stream management?s origins Definitions of value stream management Flow Lean and systems thinking and practices Agile, DevOps and other frameworks Research and analysis Identifying Value Streams What is a value stream? Identifying value streams Choosing a value stream Digital value streams Value stream thinking Mapping Value Streams Types of maps Value stream mapping The fuzzy front end Artifacts 10 steps to value stream mapping Mapping and management VSM investment case Limitations of value stream mapping Connecting DevOps Toolchains CICD and the DevOps toolchain Value stream management processes Value stream management platforms DevOps tool categories Building an end-to-end DevOps toolchain Common data model and tools integrations Value Stream Metrics The duality of VSM Downtime in technology Lean, DORA and Flow metrics Definition of Done Value metrics Benefits hypotheses Value streams as profit centers KPIs and OKRs Inspecting the Value Stream 3 Pillars of Empiricism Organizational performance Visibility When to inspect Data and discovery Insights and trends Organizing as Value Streams Value stream alignment Team types and topologies Project to product Hierarchy to autonomy Target Operating Model Value stream people Value stream roles Value stream funding Evolving Value Streams Why now? Transitions VSM capability matrix VSM culture iceberg Learning Making local discoveries global improvements Managing value stream interdependencies

Duration 2 Days 12 CPD hours This course is intended for Anyone who works with IBM SPSS Statistics and wants to learn advanced statistical procedures to be able to better answer research questions. Overview Introduction to advanced statistical analysis Group variables: Factor Analysis and Principal Components Analysis Group similar cases: Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Predict categorical targets with Discriminant Analysis Predict categorical targets with Logistic Regression Predict categorical targets with Decision Trees Introduction to Survival Analysis Introduction to Generalized Linear Models Introduction to Linear Mixed Models This course provides an application-oriented introduction to advanced statistical methods available in IBM SPSS Statistics. Students will review a variety of advanced statistical techniques and discuss situations in which each technique would be used, the assumptions made by each method, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for predicting variables, as well as methods to cluster variables and cases. Introduction to advanced statistical analysis Taxonomy of models Overview of supervised models Overview of models to create natural groupings Group variables: Factor Analysis and Principal Components Analysis Factor Analysis basics Principal Components basics Assumptions of Factor Analysis Key issues in Factor Analysis Improve the interpretability Use Factor and component scores Group similar cases: Cluster Analysis Cluster Analysis basics Key issues in Cluster Analysis K-Means Cluster Analysis Assumptions of K-Means Cluster Analysis TwoStep Cluster Analysis Assumptions of TwoStep Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Nearest Neighbor Analysis basics Key issues in Nearest Neighbor Analysis Assess model fit Predict categorical targets with Discriminant Analysis Discriminant Analysis basics The Discriminant Analysis model Core concepts of Discriminant Analysis Classification of cases Assumptions of Discriminant Analysis Validate the solution Predict categorical targets with Logistic Regression Binary Logistic Regression basics The Binary Logistic Regression model Multinomial Logistic Regression basics Assumptions of Logistic Regression procedures Testing hypotheses Predict categorical targets with Decision Trees Decision Trees basics Validate the solution Explore CHAID Explore CRT Comparing Decision Trees methods Introduction to Survival Analysis Survival Analysis basics Kaplan-Meier Analysis Assumptions of Kaplan-Meier Analysis Cox Regression Assumptions of Cox Regression Introduction to Generalized Linear Models Generalized Linear Models basics Available distributions Available link functions Introduction to Linear Mixed Models Linear Mixed Models basics Hierachical Linear Models Modeling strategy Assumptions of Linear Mixed Models Additional course details: Nexus Humans 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

This one-day course introduces the field of user experience and provides an excellent entry point to our other specialised training courses. UX processes and practices have become a central component of product design, service design and web design.

The Sales Toolkit workshop has been designed to help you increase your sales performance and skill level for you or your sales team.

This one-day course introduces the field of user experience and provides an excellent entry point to our other specialised training courses. UX processes and practices have become a central component of product design, service design and web design.

Course Overview The Psychology of Alcohol and Drug Addiction course provides a comprehensive insight into the complex psychological factors behind substance misuse and dependency. It explores the behavioural, cognitive, and emotional aspects that contribute to addiction, offering learners a thorough understanding of its causes and effects. Designed to bridge theoretical knowledge with real-world relevance, this course prepares learners to engage more confidently in fields related to mental health, counselling, and addiction support. By completing this course, learners will develop a stronger foundation in recognising addiction patterns, understanding psychological interventions, and applying evidence-based approaches. Whether you are looking to build a career in addiction services or deepen your understanding of this critical area of psychology, the course equips you with valuable insights and knowledge that are highly relevant to today’s social and healthcare settings. Course Description Delving into the psychological roots of alcohol and drug addiction, this course covers a wide range of essential topics including the biological basis of addiction, theories of dependence, psychological treatment models, and societal influences on substance use. Learners will explore how addiction develops, how it impacts mental health, and the key strategies used to address it within professional settings. The course combines theoretical frameworks with an exploration of real-world applications to enhance understanding and critical thinking. Upon completion, learners will possess a clearer perspective on addiction psychology, be familiar with intervention methods, and understand the psychological principles underpinning treatment and recovery. The course is suitable for those seeking to enter mental health support roles, enhance existing professional skills, or simply broaden their knowledge in psychology. It offers a structured learning experience that emphasises both academic understanding and professional development, aligned with contemporary psychological research. Course Modules Module 01: Understanding Addiction: Psychological and Biological Perspectives Module 02: Models of Addiction: Cognitive, Behavioural, and Social Theories Module 03: Psychological Approaches to Treatment and Recovery Module 04: Societal Impact and the Future of Addiction Studies (See full curriculum) Who is this course for? Individuals seeking to understand the psychological foundations of addiction. Professionals aiming to expand their knowledge in mental health and addiction services. Beginners with an interest in psychology, counselling, or behavioural sciences. Volunteers or support workers involved in community or rehabilitation programmes. Students considering further study in psychology or health-related fields. Career Path Addiction Counsellor Mental Health Support Worker Substance Abuse Research Assistant Rehabilitation Case Worker Community Outreach Coordinator Health and Wellness Coach Youth Support Worker Social Work Assistant

Course Overview The Financial Engineering Courses – 8 Courses Bundle is a comprehensive training package designed to equip learners with a robust understanding of the mathematical, statistical, and analytical foundations of modern finance. This bundle merges core financial theories with quantitative models to support strategic financial decision-making. Learners will explore concepts ranging from derivatives pricing and risk modelling to portfolio optimisation and stochastic processes, gaining a solid foundation in the methodologies used in financial institutions and investment firms. By the end of the course, participants will be able to interpret financial models, assess risk frameworks, and contribute effectively to quantitative analysis roles. This course is particularly valuable for those aiming to strengthen their understanding of finance through an analytical lens, aligning with roles in investment banking, financial consultancy, or quantitative research. Course Description This course bundle offers eight interconnected modules covering a wide array of financial engineering topics. Learners will be introduced to financial mathematics, stochastic calculus, fixed income securities, options pricing, quantitative risk management, and algorithmic trading strategies. The programme provides an in-depth look into the mechanics of financial markets and the computational tools that underpin asset valuation and portfolio structuring. Through clear instruction and structured content, learners will build confidence in applying quantitative techniques and economic theory to real-world financial challenges. Emphasis is placed on theoretical rigour, analytical accuracy, and strategic application. Ideal for learners with a background or interest in finance, mathematics, or economics, this course supports a deeper understanding of financial markets and prepares participants for roles that require data-driven financial modelling and risk assessment skills. Course Modules Module 01: Introduction to Financial Engineering Module 02: Financial Mathematics and Modelling Techniques Module 03: Fixed Income Securities and Yield Curves Module 04: Derivatives and Options Pricing Theory Module 05: Quantitative Risk Management Fundamentals Module 06: Stochastic Processes in Finance Module 07: Portfolio Theory and Investment Analysis Module 08: Algorithmic and Computational Finance (See full curriculum) Bundle Instructions Access all eight courses through a single enrolment. Courses are self-paced and available online 24/7. Learners receive a certificate for each completed module. Support is available throughout the learning journey. Who is this course for? Individuals seeking to build a strong foundation in quantitative finance. Professionals aiming to advance their knowledge in financial modelling and analysis. Beginners with an interest in finance, mathematics, or data-driven investment theory. Graduates or career changers targeting roles in banking, analytics, or asset management. Career Path Quantitative Analyst Financial Risk Manager Investment Banking Analyst Asset or Portfolio Manager Financial Modelling Consultant Data Analyst in Financial Services Derivatives Pricing Specialist Economic Research Associate