278 Courses in Cardiff delivered Live Online

Develop the commercial awareness, financial knowledge and strategic thinking capabilities, to influence the direction of the business Course overview Duration: 2 days (13 hours) This course is aimed at managers who want to develop their commercial awareness, financial knowledge and strategic thinking capabilities, so that they can influence the direction of their business and deliver to their full potential. Day one of the course provides the skills and insights to make sense of your company’s financial position and performance. Day two helps delegates to consider the strategic thinking tools required to plot the forward course needed to maximise the potential of the business. As well as looking at how to make effective business decisions, this course gives a good grounding in finance and profitability. As a two day programme, day one provides the skills and insights to make sense of the company’s financial position and performance. Day two then considers the strategic thinking tools needed to plot the forward course needed to maximise the potential of the business. Objectives By the end of the course you will be able to: An understanding of the balance sheet, profit and loss account, cash flow and statutory and management accounts Learnt to correctly employment key financial ratios to analyse your business A practical definition of strategy analysis tools to examine the current environment and capabilities Steps to devise a mission and vision statement Recognition of the skills and resources needed to achieve the vision Generation of appropriate strategic and tactical commercial objectives Content What is Strategy Defining Strategy Strategic thinking Strategic models Commercial thinking – what is money? Where are we now STEEPLE analysis SWOT Analysis P&E forces at work Political distortions in capitalist markets Where are we trying to get to Setting the mission and vision Creating a BHAG Strategies for deflation and inflation The role of banks Commercial and investment banking Fractional reserving Securitisation How to get there Skill gap analysis Business Process Re engineering The role of creativity How to get there Getting the team on board Individual and team motivation The power of the brand Overcoming challenges Debt and deleveraging Change management Creating value Discounted Cash Flows Building the business case Asset Valuation techniques Making it happen Turning Strategic Thinking into Strategic Plans Scenario planning for an uncertain future Creating commitments and lock in Discussion and review Time will be set aside during the course for review sessions with time for questions, answers and action learning.

Duration 3 Days 18 CPD hours This course is intended for Experienced system administrators or network administrators, software and DevOps engineers Overview By the end of the course, you should be able to meet the following objectives: Describe VMware NSX Advanced Load Balancer architecture Describe VMware NSX Advanced Load Balancer components and main functions Explain VMware NSX Advanced Load Balancer key features and benefits Describe and leverage VMware NSX Advanced Load Balancer REST API Describe and leverage VMware NSX Advanced Load Balancer SDKs with extended focus on Python SDK Leverage REST API and SDK features and functions to provision application delivery components Describe and leverage VMware NSX Advanced Load Balancer Ansible and Terraform integrations Describe and leverage VMware NSX Advanced Load Balancer Github, Docker (avinetworks/avitools), Ansible Galaxy and other open source resources to accelerate the automation planning and implementation Leverage VMware NSX Advanced Load Balancer Ansible and Terraform integrations to provision infrastructure components Leverage VMware NSX Advanced Load Balancer Ansible and Terraform integrations to automate and streamline application delivery services provisioning This three-day, fast-paced course provides comprehensive training on how to automate infrastructure and application components of VMware NSX Advanced Load Balancer (Avi Networks) solution. This course covers key application delivery features of NSX Advanced Load Balancer (Avi Networks) features and functionality offered in VMware NSX Advanced Load Balancer 18.2 release and focuses on how to plan and implement automation of infrastructure and application components leveraging REST API, SDK or automation solutions such as Ansible, Terraform or similar. Access to a software-defined data center environment is provided through hands-on labs to reinforce the skills and concepts presented in the course. Course Introduction Introductions and course logistics Course objectives Introduction to NSX Advanced Load Balancer Introduce NSX Advanced Load Balancer Discuss NSX Advanced Load Balancer use cases, and benefits Explain NSX Advanced Load Balancer architecture and components Explain the management, control, data, and consumption planes and functions Virtual Services Configuration Concepts Explain Virtual Service components Explain Virtual Service types Explain and configure basic virtual services components such as Application Profiles, Network Profiles,Pools and Health Monitors Pools Configuration Concepts Explain and deep dive on Pool configuration options Describe multiple load balancing algorithms Explain multiple Health Monitor types Explain multiple Persistent profiles Explain and configure Pool Groups Leveraging NSX Advanced Load Balancer REST API Explain NSX Advanced Load Balancer automation vision Explain and introduce NSX Advanced Load Balancer REST API Describe NSX Advanced Load Balancer REST API methods and capabilities Describe NSX Advanced Load Balancer REST API session handling properties such authentication, API versioning and tenancy model Deep dive on NSX Advanced Load Balancer REST API Object Model Explain and investigate NSX Advanced Load Balancer REST API leveraging browser and command line utilities Explain and interact with NSX Advanced Load Balancer REST API leveraging browser, Postman and Curl Explain Swagger-based API Documentation Explain and leverage NSX Advanced Load Balancer Inventory API Explain and leverage NSX Advanced Load Balancer methods such as GET, PUT, POST and PATCH and associated queries, filters and parameters Deep dive on NSX Advanced Load Balancer PATCH method Explain and leverage NSX Advanced Load Balancer Analytics API Explain and leverage NSX Advanced Load Balancer MACRO API NSX Advanced Load Balancer Software-Defined Kits (SDKs) and ControlScripts Introduce NSX Advanced Load Balancer SDKs Describe, install and leverage NSX Advanced Load Balancer Python SDK Deep dive on NSX Advanced Load Balancer Python SDK Describe and leverage Golang SDK Leverage NSX Advanced Load Balancer open source resources such as Github, etc to accelerate SDKs adoption Describe NSX Advanced Load Balancer Events and Alerts framework Introduce ControlScripts foundations Leverage ControlScripts to automate configuration changes and alerts remediation Automating NSX Advanced Load Balancer Application Delivery Services with Ansible and Terraform Introduce NSX Advanced Load Balancer Configuration Orchestration and Management vision Introduce and explain Ansible foundations Describe Ansible and NSX Advanced Load Balancer Ansible capabilities Deep dive and implement NSX Advanced Load Balancer Ansible Core configuration modules (avinetworks/avisdk) Deep dive and implement Ansible NSX Advanced Load Balancer Declarative configuration role (avinetworks/aviconfig) Leverage Swagger NSX Advanced Load Balancer REST API models to develop and implement Ansible playbooks Explain application delivery configuration automation approach and models Apply configuration automation models with Ansible Introduce and explain Terraform foundations Describe Terraform and NSX Advanced Load Balancer Terraform capabilities Deep dive and implement NSX Advanced Load Balancer Terraform Provider Leverage Swagger NSX Advanced Load Balancer REST API models to develop and implement Terraform plans Apply configuration automation models with Terraform Automating NSX Advanced Load Balancer Infrastructure with Ansible and Terraform Introduce NSX Advanced Load Balancer infrastructure Automation vision Describe infrastructure deployment approach and capabilities Describe Ansible and NSX Advanced Load Balancer Ansible Infrastructure deployment approach and capabilities Describe Terraform and NSX Advanced Load Balancer Terraform deployment approach and capabilities Leverage Terraform to deploy Controllers and perform system configuration, including control plane cluster setup Leverage Terraform to provision Cloud, Service Engine Groups and Service Engine components Describe and leverage Ansible roles to deploy Controllers and perform initial system configuration, including control plane cluster setup Leverage Ansible declarative and core roles to provision Cloud, Service Engine Groups and Service Engine components Describe and implement combined Terraform + Ansible model to streamline NSX Advanced Load Balancer solution deployment

Duration 2 Days 12 CPD hours This course is intended for Executives, Project Managers, Business Analysts, Business and IT stakeholders working with analysts, Quality and process engineers, technicians, managers; supervisors, team leaders, and process operators; anyone who wants to improve their Business Analysis skills. Overview After completing this course, students will know how to: Plan, manage and close requirements for software development project in reduced time using Agile Scrum practices Minimize project uncertainty and risk by applying Agile principles through the Scrum method Ensure your project delivers required functionality and adds value to the business Create an environment of self-management for your software development team that will be able to continuously align the delivered software with desired business needs, easily adapting to changing requirements throughout the process. Learn how to apply Agile Scrum by measuring and evaluating status based on the undeniable truth of working, testing software, creating a more accurate visibility into the actual progress of projects. Many of today?s Project Management and Business Analyst Professionals are finding themselves leading, managing and analyzing on Agile development teams - only to find that many of the tools and techniques applied when using a traditional project management approach no longer work as effectively or at all. In order to do more than survive in this iterative development environment, today?s Project Manager and Business Analyst must employ additional project management and business analysis tools and techniques to effectively lead their teams and deliver their projects. Introduction - Fundamentals of Agile Why Agile? Exercise 1a: Waterfall-Lean-Agile Simulation History & Mindset: Understand how the agile approach arose. The Agile Lifecycle Introducing Agile to the organization Roles and Responsibilities on an Agile project team. Understand the purpose, the concepts, the theory, and some applications around the importance of people as individuals providing value through working in teams. Establishing core hours - How will the team work during a day? How to build end-to-end systems in early iterations Exercise 1b: How to build end-to-end systems in early iterations Planning and Managing Business Analysis Communication and Performance Agile and CMMI Exercise 1c: Case Study Project Assembling the team ? Scrum Roles Value-Driven Development: Understand why agile development focuses so heavily on working products, its more general casting as 'value-driven' development, with incremental, iterative and risk-driven approaches. Themes, theory and applications. Exercise 2a: Identify the ?Product Owner? Identify Project Success Criteria Exercise 2b: Review the Scrum Cheat Sheet Establish your Agile team using RACI Exercise 2c: Build the Scrum Team Define the Product and Project Vision Envision the Product and Project outcomes Exercise 3a: Review Agile Checklist Project Chartering (Project Planning) Assemble the Agile project team ? what are their responsibilities? Compile the Product Backlog (Coarse-Grain Requirements) Discuss how to Plan Sprints and Releases Exercise 3b: Product Vision ? Goals and Strategies Establish the Project ?time-box? Exercise 3c: Create a Release Plan Embrace the High-Level (Coarse-Grain) Plan Managing different types of Personas on an Agile Project Identifying and managing ?Information Radiators? Planning in Agile Projects ? Common practices that work Determine how the team will tracking and monitoring activities Exercise 3c: Establish the Project Time-box Tools and Techniques ? Building the Scrum Task board Communications Exercise 4a: Discussion ? Tools and Techniques for Scrum Planning, Monitoring and Adapting Scrum Task Board Exercise 4c: Create a Scrum Task board ? Identify work streams Agile Estimating Agile Analysis and Design Burndown Chart Team Velocity Soft Skills Negotiation Estimating ad Prioritizing Effort Planning Releases. Understand the value, the concepts, the theory and some applications for learning and adapting at all levels and on all topics (the product, the process, the team, and the organization). Exercise 5a: Brainstorm Business Functionality Establishing decision and acceptance criteria for user stories Planning Poker Exercise 5b: Estimate Effort (Coarse-Grain) Prioritize themes and releases Prioritize user stories Exercise 5c: Confirm the Estimated Effort (Fine Grain) Estimating team velocity Preparing for change ? Is the organization ready? Exercise 5d: Hold a daily Scrum and update the Scrum Task Board Exercise 5e: Conduct a Scrum or Scrums Plan the Iteration (Sprint) Sprint Zero activities Elements of a successful Sprint Planning meeting Create a Sprint Backlog How to create a task board Exercise 6a: Using the case study ? Review Iteration Planning Checklist Create a Sprint plan ? Establishing Sprint success metrics Exercise 6b: Discussion Sprint ?Zero? Activities Define the vision and Iteration Requirements Estimating the level of effort (LOE) with the team Creating user Stories for the Product Backlog -Guidelines to consider The art of slicing user stories Exercise 6c: Review the Sprint Plan Managing the Solution Scope and Requirements using 2-4 week Sprints Exercise 6d: Adapting a change-driven Project plan that works Adapting a change-driven (Agile) Project plan that works ? what are the key differences from traditional (waterfall) project plans? Finalize the Iteration Plan and how the team will operate Running the Sprint - from Planning to Review and Retrospective Managing your Scrums and setting expectations with your team Exercise 7a: Using the case study ? Review the Review Planning checklist Using Burndown charts to track progress Exercise 7b: Using the case study ? Review the Review Retrospective checklist Manage changes during the Sprint ? What questions to ask Prepare for the Sprint Review Exercise 7c: Review of roles - Quiz Obtain Customer Acceptance of the Product Increment Hold a Sprint Retrospective - What is working and what needs to be improved upon during the Sprints Update the product backlog - Rework the High-Level (Coarse-Grain) Plan Plan and Execute the next Sprint Create an environment for continuous improvement ? Product, Process and People Additional Information Useful books and links on Agile

Duration 1 Days 6 CPD hours This course is intended for The content is appropriate for test automation engineering roles, test manager roles, test lead roles, test architect roles, as well as developer roles. This course assumes you have a foundational understanding of testing and the purpose of automation. This course will be beneficial to anyone who is accountable for assessing, planning, designing, and implementing an integrated set of technology (testing infrastructure) that supports development, testing, and deployment. Overview Working in an interactive learning environment, led by our expert facilitator, attendees will learn to: Document the current state of test automation in your organization Define a custom test automation plan and architecture to fit their situation Create an initial implementation plan Identify initial key measures Develop a metrics dashboard for tracking the value of test automation Lay out a future strategy and roadmap to get there Introduction to Test Automation is a one-day, hands-on event designed to provide participants with the skills required to develop a custom test automation plan and architecture for their organization. Throughout the course, students will examine and work through various practical examples, learning how to create an integrated test automation plan and develop a test automation architecture. Participants will also learn about the possible real-world challenges they may face while trying to accomplish their goals, exploring the practical positive aspects of engaging their technical team, along with the possible frustrations of experiencing too much isolation between test automators and test designers. Getting Started Automation beginnings Software as a series of imperfect translations The Compelling Business Needs for Automation Automation the next opportunity Islands of Automation Getting products to market more quickly, at the right costs and quality Automation Challenges and Requirements Automation Challenges Test Automation Key Requirements Foundational material for your automation plan Templates Questions Examples Virtual Consulting included with this course Automation plan vision and strategy Vision, Strategy, Approach Example Defining your end in mind Deciding where to start Engaging Others Conducting a current state tools inventory Assessing your current state - tools and processes Tools inventory example and template Radar Chart as a means of presenting current state information Consider the best automation approach Waterfall vs. agile cycles of work Aligning tools with your methodologies Strategies for Automating The Test Automation Pyramid Developing your test automation architecture Blocks of automation capabilities Islands of Automation Integrated Tools Architecture Template Integrated Tools Architecture Examples Test automation architecture examples Examples of different test automation architectures and frameworks Selenium Key Test Automation Architecture Characteristics Acceptance test-driven and behavior-driven testing overview Test automation approaches FitNesse Cucumber Gherkin script overview Tool workflow Considerations for what to automate and when Categories of tests that might be automated We have many tool choices Key points in Test Tool Architecture Planning Piloting and Implementing automation Selecting and evaluating tools and rolling them out Selling Automation - qualitative questions Selling Automation - quantitative questions Measuring automation benefits Measures in technical terms Measures in business terms Measures of testing vs. measures of test automation Next Steps A few keys to success

This comprehensive online interior design course includes 12 self study modules, and weekly 1:1 telephone and or video consultations. I will personally guide and inspire you through your creative learning journey.

Duration 3 Days 18 CPD hours This course is intended for Technical Leaders Overview What is BlockchainHow does Blockchain workTypes of BlockchainsHow is Blockchain different from what we have todayWhat are use cases for BlockchainWhat does a Blockchain app look likeHow do I design a Blockchain appHow do I develop a Blockchain appHow do I test a Blockchain app This instructor-led 3 day Blockchain Architecture training is for technical leaders who need to make decisions about architecture, environment, and development platforms. What is Blockchain? A record keeping system Trust Decentralization Trustless environment How does Blockchain work? Announcements Blocks Nodes Chaining Verification Consensus Scalability Privacy Crypto Hashing Digital Fingerprinting PoW vs PoS Types of Blockchains Public vs Private Open vs closed Smart Contracts Blockchain as History Tokens / Coins Gas How is Blockchain different from what we have today? Decentralized Peer-to-peer architecture Software vs Firmware Database vs Blockchain Distributed database or other technology? Data Sovereignty Group Consensus What are Use Cases for Blockchain? Use Case Examples Currency Banking Services Voting Medical Records Supply Chain / Value Chain Content Distribution Verification of Software Updates (cars, planes, trains, etc) Law Enforcement Title and Ownership Records Social Media and Online Credibility Fractional asset ownership Cable Television billing High fault tolerance DDoS-proof Public or Private Blockchain? Who are the participants? What does a Blockchain app look like? DApp Resembles typical full stack web application Any internal state changes and all transactions are written to the blockchain Node.js IDE Public Blockchain visibility Private Blockchain solutions Oracles How do I design a Blockchain app? What does this solution need to let users do? Will the proposed solution reduce or remove the problems and pain points currently felt by users? What should this solution prevent users from doing? Do you need a solution ready for heavy use on day 1? Is your solution idea enhanced by the use of Blockchain? Does the use of Blockchain create a better end-user experience? If so, how? Has your business developed custom software solutions before? What level of support are you going to need? How big is the developer community? Does your vision of the future align with the project or platform's vision of the future? Does the platform aim to make new and significant contributions to the development space, or is it an efficiency / cost play? Should the solution be a public or private Blockchain? Should the solution be an open or closed Blockchain? Create a plan for contract updates and changes! Hybrid solutions Monetary exchanges? How do I develop a Blockchain app? AGILE approach pre-release Define guiding principles up front Software vs Firmware Announcements, not transactions! Classes, not contracts Link contracts to share functions Use calling contracts to keep contract address the same Hyperledger vs Ethereum CONSIDER No of Users * Avg No of Transactions (state changes) per User Should a Blockless solution be applied? Performance Security Anonymity Security Monolithic vs Modular Sandwich complexity model How do I test a Blockchain app? Recommend 5x to 10x traditional application testing time Security Networks

Course Overview: This course provides in-depth knowledge of cinematography and directing, including the use of different cameras, lighting setups, metering techniques, and creative direction. Students will learn to master key elements of production and post-production processes. Hourly Session Breakdown: 8 one-hour sessions on Skype.

•The Online NLP Practitioner Training is a comprehensive program that will provide you with the tools and techniques you need to overcome your chronic pain and mental health conditions. • The program includes a printable digital copy of the NLP Practitioner Manual, access to the video recording of the training, ‘live’ online demonstrations of the techniques in action on yourself, online support for one year by way of group calls, and assistance set up your business website. • This program is perfect for anyone who wants to achieve positive change in their lives! Whether you’re a self-starter who is interested in self-development or a professional who is seeking career development and job fulfilment.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies

This comprehensive online interior design course includes 12 self study modules, and weekly 1:1 telephone and or video consultations. I will personally guide and inspire you through your creative learning journey.