1087 Architect courses in Cardiff delivered Live Online

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Computer Science GCSE Syllabus The GCSE Computer Science Tutor Syllabus is designed to provide tutors in England with a comprehensive framework for teaching the GCSE Computer Science curriculum effectively. This syllabus aims to equip tutors with the necessary knowledge and skills to support students in their understanding and application of core computer science concepts.  Module 1: Introduction to Computer Science - Overview of computer science and its relevance in today's world - Understanding the components of a computer system - Introduction to algorithms and problem-solving techniques - Exploration of programming languages and their uses Module 2: Computer Hardware - Understanding the main components of a computer system, including CPU, memory, and storage devices - Exploring input and output devices and their functionalities - Understanding the role of operating systems and software in computer systems Module 3: Software Development - Introduction to programming concepts and languages (e.g., Python or Java) - Understanding variables, data types, and operators - Building algorithms and logical reasoning skills - Introduction to flowcharts and pseudocode - Implementation of simple programs and debugging techniques Module 4: Data Representation - Understanding binary, hexadecimal, and denary number systems - Representation of text, images, and sound using binary - Introduction to data compression and encryption techniques Module 5: Computer Networks - Understanding the basics of computer networks, including LAN, WAN, and the Internet - Introduction to network topologies, protocols, and security - Exploring the impact of digital communication on society Module 6: Cybersecurity and Ethical Issues - Understanding the importance of cybersecurity and data protection - Introduction to common threats and vulnerabilities - Exploring ethical issues related to computer science, such as privacy and intellectual property rights Module 7: Algorithms and Programming Techniques - Advanced programming concepts, including conditionals, loops, and functions - Introduction to sorting and searching algorithms - Exploring data structures, such as arrays and lists Module 8: System Architecture - Understanding the structure and function of a CPU - Introduction to memory hierarchy and cache - Exploring the Von Neumann architecture and its limitations Module 9: Computational Thinking and Problem Solving - Advanced problem-solving techniques using computational thinking - Introduction to algorithms for complex problems - Exploring algorithmic efficiency and optimization techniques Module 10: Exam Preparation and Revision - Reviewing key concepts covered throughout the syllabus - Practicing past exam questions and providing guidance on exam techniques - Supporting students with exam preparation strategies Please note that the duration and depth of each module can vary depending on the level of expertise required and the specific needs of the learners. Additionally, it's important to adapt the curriculum to the learners' proficiency levels, whether they are A Level/GCSE students or adult learners with different experience levels.

Course Overview: The "CAD Designer Training" course provides a comprehensive introduction to the world of Computer-Aided Design (CAD). Learners will explore the core principles, tools, and techniques used in CAD software to create both 2D and 3D designs. The course covers fundamental topics such as shape creation, geometry, modelling, and assemblies, along with software introductions to AutoCAD, T-Flex, SolidWorks, and FreeCAD. By the end of this course, participants will have a solid understanding of CAD design and the technical skills necessary to pursue a career in design, engineering, or architecture. Course Description: This in-depth course is designed to equip learners with the essential skills for becoming proficient in CAD design. It covers a variety of important areas, including the basics of CAD design, 2D and 3D shape creation, geometry and modelling, and assembly techniques. Learners will gain an introduction to industry-standard software such as AutoCAD, T-Flex, SolidWorks, and FreeCAD, allowing them to explore multiple platforms used in the CAD design field. With modules covering extrusion, rotations, grids, polygons, and civil drawings, this course ensures learners develop a comprehensive understanding of the tools and techniques used by CAD professionals. It is an excellent foundation for anyone wishing to pursue a career in the design and engineering sectors. Course Modules: Module 01: Introduction to CAD Design Module 02: CAD Designer Career in the United Kingdom Module 03: Basics for CAD Design – Part 1 Module 04: Basics for CAD Design – Part 2 Module 05: 2D Shape in CAD Module 06: 3D Shape in CAD Module 07: Geometry and Modelling Module 08: Assemblies in CAD Design Module 09: Extrusion and Rotations Module 10: Blending Operations in CAD Module 11: Grids and Regular Polygons Module 12: Parameters in Civil Drawings Module 13: Introduction to AutoCAD Module 14: Introduction to T-Flex CAD Module 15: Introduction to SolidWorks Module 16: Introduction to FreeCAD (See full curriculum) Who is this course for? Individuals seeking to build a career in design and engineering. Professionals aiming to develop their CAD design skills. Beginners with an interest in CAD software and design. Those pursuing opportunities in the construction, architecture, or manufacturing industries. Career Path: CAD Designer 3D Modeler Architectural Drafter Mechanical Designer Civil Drafter Product Designer Engineering Assistant Design Consultant

Course Overview The LEED V4 - Building Design and Construction course offers an in-depth exploration of sustainable building practices in line with the LEED (Leadership in Energy and Environmental Design) standards. Learners will gain a comprehensive understanding of the LEED V4 framework and its application to building design and construction. The course highlights key principles, including energy efficiency, environmental responsibility, and resource management, equipping participants with the knowledge to meet LEED certification requirements. Upon completion, learners will be prepared to integrate sustainable practices into their work, contributing to green building initiatives and reducing environmental impact in the construction industry. Course Description This course delves into the core components of the LEED V4 standards, covering a broad spectrum of topics such as integrative processes, sustainable site development, water efficiency, energy optimisation, and indoor environmental quality. Learners will explore how these elements impact building design and construction, learning how to create energy-efficient, eco-friendly structures. The course provides a thorough examination of each LEED category, equipping participants with the skills needed to navigate the certification process and apply sustainable design principles to real-world projects. By the end, learners will have the knowledge to assess projects for LEED compliance and incorporate green strategies into building practices, driving sustainability forward. Course Modules Module 01: Introduction Module 02: Integrative Process Module 03: Location & Transportation Module 04: Sustainable Sites Module 05: Water Efficiency Module 06: Energy & Atmosphere Module 07: Materials & Resources Module 08: Indoor Environment Quality Module 09: Innovation Module 10: Regional Priority Module 11: Completion (See full curriculum) Who is this course for? Individuals seeking to enhance their knowledge of sustainable building practices Professionals aiming to pursue LEED accreditation or certification Beginners with an interest in green building and environmental design Architects, engineers, and construction managers looking to stay current with industry standards Sustainability advocates looking to make a difference in the built environment Career Path Green Building Consultant LEED Accredited Professional Sustainability Coordinator Environmental Consultant Energy Manager Construction Project Manager Sustainability Analyst

Course Overview The DeepSeek Masterclass: A Complete DeepSeek Zero to Hero! provides a comprehensive exploration of the DeepSeek AI ecosystem, designed to guide learners from fundamental understanding to advanced applications. This course equips individuals with the knowledge to navigate the capabilities of DeepSeek across various domains such as software development, business analysis, and education. Whether you're looking to stay current in a rapidly evolving technological landscape or explore how AI transforms diverse sectors, this course offers a structured pathway. By the end of the programme, learners will be able to understand DeepSeek’s architecture, apply its tools across multiple contexts, and critically evaluate its potential within both technical and professional settings. Course Description This course delves into the foundational principles and progressive applications of DeepSeek, starting from basic concepts in artificial intelligence through to its tailored use in education, business, and software environments. Learners will explore how to configure and interpret DeepSeek outputs, understand the structure of AI decision-making, and evaluate its integration across various workflows. Key modules address the needs of developers, educators, students, and professionals seeking efficient AI-driven solutions. Throughout the course, learners will be introduced to scenario-based uses of DeepSeek, helping them build a contextual understanding of its functions. The curriculum is designed to support strategic thinking, digital literacy, and informed adoption of AI tools in both academic and professional environments. Course Modules Module 01: Getting Started Module 02: Foundations of Artificial Intelligence (AI) Module 03: Setting up DeepSeek AI for Beginners Module 04: DeepSeek for Software Developers Module 05: DeepSeek for Business Professionals Module 06: DeepSeek Smart Solutions for Students Module 07: The Power of DeepSeek Module 08: DeepSeek for Teaching Professionals (See full curriculum) Who is this course for? Individuals seeking to build an informed understanding of DeepSeek and AI. Professionals aiming to implement AI solutions within their field. Beginners with an interest in artificial intelligence and its uses. Educators, students, and technologists exploring innovative learning and working tools. Career Path AI Integration Analyst Business Intelligence Associate Education Technology Consultant Software Solution Strategist Digital Transformation Specialist AI Literacy Educator

Course Overview The Computer Maintenance, PAT & Cyber Security course offers a comprehensive introduction to the essential components of modern IT systems, combining core knowledge in hardware setup, system troubleshooting, and security protocols. Designed to build foundational understanding as well as introduce advanced cybersecurity concepts, this course equips learners with the confidence to navigate today’s digital infrastructure. From building a computer to understanding network vulnerabilities, learners will explore a variety of modules that address both traditional and emerging technologies, including IoT and encryption. By the end of the course, students will have developed the skills to identify risks, support device performance, and understand secure systems architecture—essential for any role in technology-focused sectors. Course Description This course blends key topics across computer hardware maintenance, PAT (Portable Appliance Testing), and cyber security to prepare learners for a well-rounded understanding of IT system management. The curriculum begins with assembling and configuring computers, progressing into network security and advanced Windows troubleshooting. Learners are introduced to essential software tools and coding applications like C++ with OpenCV, and gain insights into the Internet of Things and encryption principles. Additionally, the course includes training in cyber security awareness, addressing the latest threats and preventative frameworks. With clear instructional guidance and structured content delivery, the course is suitable for learners aiming to understand technical environments and the protocols behind secure computing. It is ideal for those seeking career progression or looking to explore new opportunities in IT security, maintenance, or systems analysis. Course Modules: Module 01: Building Your Own Computer Module 02: Computer Networks Security from Scratch to Advanced Module 03: Computer Vision By Using C++ and OpenCV with GPU support Module 04: Advance Windows 10 Troubleshooting for IT HelpDesk Module 05: Portable Appliance Testing (PAT) Module 06: Internet of Things Module 07: Cyber Security Awareness Training Module 08: Encryption (See full curriculum) Who is this course for? Individuals seeking to understand IT maintenance and cybersecurity principles. Professionals aiming to broaden their knowledge of system configuration and data protection. Beginners with an interest in computer technology and digital safety. Employers looking to upskill their IT or facilities staff in security and device compliance. Career Path IT Support Specialist Systems Administrator Network Security Analyst Cyber Security Consultant Electrical Safety Compliance Officer Technical Services Coordinator

Course Overview The Professional Photography course provides a comprehensive journey into the world of photography, blending creative techniques with technical understanding. This course covers everything from mastering exposure and digital photography to exploring specialist scenarios such as portraits, landscapes, macro, and aerial photography. Learners will gain an in-depth understanding of camera anatomy, lighting, white balance, and post-production editing using industry-standard tools like Photoshop and Lightroom. Whether learners wish to enhance personal skills or pursue professional ambitions, this course equips them with the expertise to produce high-quality photographic work. By the end of the course, learners will be able to demonstrate proficiency across diverse photography styles, effectively manage photography equipment, and refine their editing capabilities. In addition, guidance on starting a photography business and selling work will support those looking to monetise their skills. This course offers valuable knowledge for both career development and personal enrichment in the creative industry. Course Description This course delves deeply into the art and science of photography, providing learners with a structured pathway to master both foundational principles and advanced techniques. Beginning with an introduction to camera settings, exposure, and digital photography, it progresses through specialised topics including focus and depth of field, lighting control, and the use of various photographic equipment. Learners will engage with diverse photography scenarios such as street photography, events, wildlife, and product shoots, developing a versatile skill set suitable for a range of professional contexts. The curriculum also explores post-processing with software such as Photoshop CC, Lightroom Classic CC, and mobile editing tools like Snapseed and Photoshop Express. Furthermore, modules on business development and stock photography sales offer valuable insights into potential income streams. Delivered in an engaging and accessible format, this course ensures that learners acquire both creative and technical expertise, setting a strong foundation for future opportunities in photography. Course Modules Module 01: Introduction Module 02: Exposure Module 03: Digital Photography Masterclass Module 04: Focus and Depth of Field Module 05: Camera Anatomy Module 06: White Balance and Colour Module 07: Lighting Module 08: Mobile Photography Module 09: Equipment – Cameras Module 10: Equipment – Lenses Module 11: Equipment – Accessories Module 12: Photo Scenario – Portrait Module 13: Photo Scenario – Long Exposure Module 14: Photo Scenario – Landscape Module 15: Photo Scenario – Product Module 16: Photo Scenario – Low Light Module 17: Photo Scenario – Sports & Action Module 18: Photo Scenario – Macro Module 19: Photo Scenario – Street & Architecture Module 20: Photo Scenario – Events Module 21: Photo Scenario – Aerial Module 22: Photo Scenario – Night Module 23: Introduction to Photo Editing Module 24: Photoshop CC Module 25: Lightroom Classic CC Module 26: Lightroom CC Module 27: Mac Photos Module 28: Google Photos Module 29: Photoshop Express Module 30: Snapseed Module 31: Sharing Your Photos Module 32: Starting a Photo Business Module 33: Selling Stock Photos Module 34: Printing Module 35: Wildlife Module 36: Conclusion (See full curriculum) Who is this course for? Individuals seeking to develop creative and technical photography skills. Professionals aiming to expand their visual media expertise. Beginners with an interest in photography and digital editing. Entrepreneurs wishing to build a photography business. Hobbyists looking to refine their photographic techniques. Career Path Professional Photographer Freelance Photojournalist Event and Wedding Photographer Wildlife Photographer Digital Content Creator Stock Photography Contributor Photography Business Owner Visual Media Consultant

Hybrid Vehicle Expert Training Course Overview The Hybrid Vehicle Expert Training course provides an in-depth understanding of hybrid electric vehicles (HEVs), focusing on their design, operation, and technology. Learners will explore various types of hybrids, key components, and the degree of hybridisation, enhancing their technical knowledge for the automotive industry. This course equips participants with essential skills to analyse regenerative systems and other innovative features that improve fuel efficiency and reduce emissions. By the end of the course, learners will be confident in identifying different HEV architectures and understanding their functional principles, preparing them for roles in vehicle maintenance, engineering, and technical consultancy within the evolving green transport sector. Course Description This course offers comprehensive coverage of hybrid vehicle technology, beginning with an introduction to hybrid electric vehicles and their classifications. It delves into the degree of hybridisation, explaining how various systems operate to optimise energy use. Detailed study of HEV components provides insight into powertrains, batteries, and control systems. The course also covers regenerative braking and energy recovery technologies that enhance vehicle efficiency. Learners will gain analytical skills required to evaluate hybrid systems and keep pace with developments in sustainable automotive design. The structured learning experience combines theory and technical knowledge, suitable for those aiming to build expertise in green vehicle technologies and contribute to environmental sustainability within the automotive sector. Hybrid Vehicle Expert Training Curriculum: Module 01: Introduction Module 02: Types of Hybrid Electric Vehicles Module 03: Degree of Hybridisation Module 04: Components of HEVs Module 05: Regenerative Systems (See full curriculum) Who is this course for? Individuals seeking to develop expertise in hybrid vehicle technology. Professionals aiming to advance their careers in the automotive or green transport sectors. Beginners with an interest in sustainable automotive technologies. Technicians and engineers preparing for roles in vehicle systems analysis and maintenance. Career Path Hybrid Vehicle Technician Automotive Engineer specialising in green technologies Vehicle Systems Analyst Technical Consultant for sustainable transport solutions Research and Development Specialist in automotive innovation

Develop Big Data Pipelines with R, Sparklyr & Power BI Course Overview: This course offers a comprehensive exploration of building and managing big data pipelines using R, Sparklyr, and Power BI. Learners will gain valuable insight into the entire process, from setting up and installing the necessary tools to creating effective ETL pipelines, implementing machine learning techniques, and visualising data with Power BI. The course is designed to provide a strong foundation in data engineering, enabling learners to handle large datasets, optimise data workflows, and communicate insights clearly using visual tools. By the end of this course, learners will have the expertise to work with big data, manage ETL pipelines, and use Sparklyr and Power BI to drive data-driven decisions in various professional settings. Course Description: This course delves into the core concepts and techniques for managing big data using R, Sparklyr, and Power BI. It covers a range of topics including the setup and installation of necessary tools, building ETL pipelines with Sparklyr, applying machine learning models to big data, and using Power BI for creating powerful visualisations. Learners will explore how to extract, transform, and load large datasets, and will develop a strong understanding of big data architecture. They will also gain proficiency in visualising complex data and presenting findings effectively. The course is structured to enhance learners' problem-solving abilities and their competence in big data environments, equipping them with the skills needed to manage and interpret vast amounts of information. Develop Big Data Pipelines with R, Sparklyr & Power BI Curriculum: Module 01: Introduction Module 02: Setup and Installations Module 03: Building the Big Data ETL Pipeline with Sparklyr Module 04: Big Data Machine Learning with Sparklyr Module 05: Data Visualisation with Power BI (See full curriculum) Who is this course for? Individuals seeking to understand big data pipelines. Professionals aiming to expand their data engineering skills. Beginners with an interest in data analytics and big data tools. Anyone looking to enhance their ability to analyse and visualise data. Career Path: Data Engineer Data Analyst Data Scientist Business Intelligence Analyst Machine Learning Engineer Big Data Consultant

Duration 3 Days 18 CPD hours This course is intended for This class is intended for the following participants: Cloud architects, administrators, and SysOps/DevOps personnel Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform. Overview This course teaches participants the following skills: Understand how software containers work Understand the architecture of Kubernetes Understand the architecture of Google Cloud Platform Understand how pod networking works in Kubernetes Engine Create and manage Kubernetes Engine clusters using the GCP Console and gcloud/ kubectl commands Launch, roll back and expose jobs in Kubernetes Manage access control using Kubernetes RBAC and Google Cloud IAM Managing pod security policies and network policies Using Secrets and ConfigMaps to isolate security credentials and configuration artifacts Understand GCP choices for managed storage services Monitor applications running in Kubernetes Engine This class introduces participants to deploying and managing containerized applications on Google Kubernetes Engine (GKE) and the other services provided by Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as pods, containers, deployments, and services; as well as networks and application services. This course also covers deploying practical solutions including security and access management, resource management, and resource monitoring. Introduction to Google Cloud Platform Use the Google Cloud Platform Console Use Cloud Shell Define cloud computing Identify GCPs compute services Understand regions and zones Understand the cloud resource hierarchy Administer your GCP resources Containers and Kubernetes in GCP Create a container using Cloud Build Store a container in Container Registry Understand the relationship between Kubernetes and Google Kubernetes Engine (GKE) Understand how to choose among GCP compute platforms Kubernetes Architecture Understand the architecture of Kubernetes: pods, namespaces Understand the control-plane components of Kubernetes Create container images using Google Cloud Build Store container images in Google Container Registry Create a Kubernetes Engine cluster Kubernetes Operations Work with the kubectl command Inspect the cluster and Pods View a Pods console output Sign in to a Pod interactively Deployments, Jobs, and Scaling Create and use Deployments Create and run Jobs and CronJobs Scale clusters manually and automatically Configure Node and Pod affinity Get software into your cluster with Helm charts and Kubernetes Marketplace GKE Networking Create Services to expose applications that are running within Pods Use load balancers to expose Services to external clients Create Ingress resources for HTTP(S) load balancing Leverage container-native load balancing to improve Pod load balancing Define Kubernetes network policies to allow and block traffic to pods Persistent Data and Storage Use Secrets to isolate security credentials Use ConfigMaps to isolate configuration artifacts Push out and roll back updates to Secrets and ConfigMaps Configure Persistent Storage Volumes for Kubernetes Pods Use StatefulSets to ensure that claims on persistent storage volumes persist across restarts Access Control and Security in Kubernetes and Kubernetes Engine Understand Kubernetes authentication and authorization Define Kubernetes RBAC roles and role bindings for accessing resources in namespaces Define Kubernetes RBAC cluster roles and cluster role bindings for accessing cluster-scoped resources Define Kubernetes pod security policies Understand the structure of GCP IAM Define IAM roles and policies for Kubernetes Engine cluster administration Logging and Monitoring Use Stackdriver to monitor and manage availability and performance Locate and inspect Kubernetes logs Create probes for wellness checks on live applications Using GCP Managed Storage Services from Kubernetes Applications Understand pros and cons for using a managed storage service versus self-managed containerized storage Enable applications running in GKE to access GCP storage services Understand use cases for Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Bigtable, Cloud Firestore, and Bigquery from within a Kubernetes application