111 Software Developer courses in Cardiff delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for System administrators and operators who are operating in the AWS Cloud Informational technology workers who want to increase the system operations knowledge. Overview Identify the AWS services that support the different phases of Operational Excellence, an AWS Well-Architected Framework pillar Manage access to AWS resources using AWS accounts and organizations and AWS Identity and Access Management (IAM) Maintain an inventory of in-use AWS resources by using AWS services, such as AWS Systems Manager, AWS CloudTrail, and AWS Config Develop a resource deployment strategy using metadata tags, Amazon Machine Images (AMIs), and AWS Control Tower to deploy and maintain an AWS cloud environment Automate resource deployment by using AWS services, such as AWS CloudFormation and AWS Service Catalog Use AWS services to manage AWS resources through CloudOps lifecycle processes, such as deployments and patches Configure a highly available cloud environment that uses AWS services, such as Amazon Route 53 and Elastic Load Balancing, to route traffic for optimal latency and performance Configure AWS Auto Scaling and Amazon EC2 Auto Scaling to scale out your cloud environment based on demand Use Amazon CloudWatch and associated features, such as alarms, dashboards, and widgets, to monitor your cloud environment Manage permissions and track activity in your cloud environment by using AWS services, such as AWS CloudTrail and AWS Config Deploy your resources to an Amazon Virtual Private Cloud (Amazon VPC), establish necessary connectivity to your Amazon VPC, and protect your resources from disruptions of service State the purpose, benefits, and appropriate use cases for mountable storage in your AWS Cloud environment Explain the operational characteristics of object storage in the AWS Cloud, including Amazon Simple Storage Service (Amazon S3) and Amazon S3 Glacier Build a comprehensive cost model to help gather, optimize, and predict your cloud costs by using services such as AWS Cost Explorer and the AWS Cost & Usage Report This course teaches systems operators and anyone performing cloud operations functions how to manage and operate automatable and repeatable deployments of networks and systems on AWS. You will learn about cloud operations functions, such as installing, configuring, automating, monitoring, securing, maintaining, and troubleshooting these services, networks, and systems. The course also covers specific AWS features, tools, and best practices related to these functions. Prerequisites Successfully completed the AWS Technical Essentials course Background in either software development or systems administration Proficiency in maintaining operating systems at the command line, such as shell scripting in Linux environments or cmd/PowerShell in Windows Basic knowledge of networking protocols (TCP/IP, HTTP) 1 - Introduction to Cloud Operations on AWS What is Cloud Operations AWS Well-Architected Framework AWS Well-Architected Tool 2 - Access Management AWS Identity and Access Management (IAM) Resources, accounts, and AWS Organizations 3 - System Discovery Methods to interact with AWS services Tools for automating resource discovery Inventory with AWS Systems Manager and AWS Config Hands-On Lab: Auditing AWS Resources with AWS Systems Manager and AWS Config 4 - Deploy and Update Resources Cloud Operations in deployments Tagging strategies Deployment using Amazon Machine Images (AMIs) Deployment using AWS Control Tower 5 - Automate Resource Deployment Deployment using AWS CloudFormation Deployment using AWS Service Catalog Hands-On Lab: Infrastructure as Code 6 - Manage Resources AWS Systems Manager Hands-On Lab: Operations as Code 7 - Configure Highly Available Systems Distributing traffic with Elastic Load Balancing Amazon Route 53 8 - Automate Scaling Scaling with AWS Auto Scaling Scaling with Spot Instances Managing licenses with AWS License Manager 9 - Monitor and Maintain System Health Monitoring and maintaining healthy workloads Monitoring AWS infrastructure Monitoring applications Hands-On Lab: Monitor Applications and Infrastructure 10 - Data Security and System Auditing Maintaining a strong identity and access foundation Implementing detection mechanisms Automating incident remediation 11 - Operate Secure and Resilient Networks Building a secure Amazon Virtual Private Cloud (Amazon VPC) Networking beyond the VPC 12 - Mountable Storage Configuring Amazon Elastic Block Store (Amazon EBS) Sizing Amazon EBS volumes for performance Using Amazon EBS snapshots Using Amazon Data Lifecycle Manager to manage your AWS resources Creating backup and data recovery plans Configuring shared file system storage Hands-On Lab: Automating with AWS Backup for Archiving and Recovery 13 - Object Storage Deploying Amazon Simple Storage Service (Amazon S3) Managing storage lifecycles on Amazon S3 14 - Cost Reporting, Alerts, and Optimization Gaining AWS cost awareness Using control mechanisms for cost management Optimizing your AWS spend and usage Hands-On Lab: Capstone lab for CloudOps Additional course details: Nexus Humans Cloud Operations on AWS 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 Cloud Operations on AWS 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.

About this training course Business Impact: The main aim is to provide insight and understanding of data analytics and machine learning principles through applications. Field data is used to explain data-analysis workflows. Using easy to follow solution scripts, the participants will assess and extract value from the data sets. Hands-on solution approach will give them confidence to try out applicable techniques on data from their field assets. Data analysis means cleaning, inspecting, transforming, and modeling data with the goal of discovering new, useful information and supporting decision-making. In this hands-on 2-day training course, the participants learn some data analysis and data science techniques and workflows applied to petroleum production (specifically artificial lift) while reviewing code and practicing. The focus is on developing data-driven models while keeping our feet closer to the underlying oil and gas production principles. Unique Features: Eight business use cases covering their business impact, code walkthroughs for most all and solution approach. Industry data sets for participants to practice on and take home. No software or complicated Python frameworks required. Training Objectives After the completion of this training course, participants will be able to: Understand digital oil field transformation and its impact on business Examine machine learning methods Review workflows and code implementations After completing the course, participants will have a set of tools and some pathways to model and analyze their data in the cloud, find trends, and develop data-driven models Target Audience This training course is suitable and will greatly benefit the following specific groups: Artificial lift, production and facilities engineers and students to enhance their knowledge base, increase technology awareness, and improve the facility with different data analysis techniques applied on large data sets Course Level Intermediate Advanced Training Methods The course discusses several business use-cases that are amenable to data-driven workflows. For each use case, the instructor will show the solution using a data analysis technique with Python code deployed in the Google cloud. Trainees will solve a problem and tweak their solution. Course Duration: 2 days in total (14 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: Understanding of petroleum production concepts Knowledge of Python is not a must but preferred to get the full benefit. The training will use the Google Collaboratory environment available in Google-Cloud for hands-on exercises Trainees will need to bring a computer with a Google Chrome browser and a Google email account (available for free) Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. Developed a workshop on digital oilfield approaches for production engineers. Patents: Principal inventor: 'Smarter Slug Flow Conditioning and Control' Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations

Duration 4 Days 24 CPD hours This course is intended for Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure. AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language. Prerequisites Before attending this course, students must have: Knowledge of Microsoft Azure and ability to navigate the Azure portal Knowledge of either C# or Python Familiarity with JSON and REST programming semantics Recommended course prerequisites AI-900T00: Microsoft Azure AI Fundamentals course 1 - Prepare to develop AI solutions on Azure Define artificial intelligence Understand AI-related terms Understand considerations for AI Engineers Understand considerations for responsible AI Understand capabilities of Azure Machine Learning Understand capabilities of Azure AI Services Understand capabilities of the Azure Bot Service Understand capabilities of Azure Cognitive Search 2 - Create and consume Azure AI services Provision an Azure AI services resource Identify endpoints and keys Use a REST API Use an SDK 3 - Secure Azure AI services Consider authentication Implement network security 4 - Monitor Azure AI services Monitor cost Create alerts View metrics Manage diagnostic logging 5 - Deploy Azure AI services in containers Understand containers Use Azure AI services containers 6 - Analyze images Provision an Azure AI Vision resource Analyze an image Generate a smart-cropped thumbnail 7 - Classify images Provision Azure resources for Azure AI Custom Vision Understand image classification Train an image classifier 8 - Detect, analyze, and recognize faces Identify options for face detection analysis and identification Understand considerations for face analysis Detect faces with the Azure AI Vision service Understand capabilities of the face service Compare and match detected faces Implement facial recognition 9 - Read Text in images and documents with the Azure AI Vision Service Explore Azure AI Vision options for reading text Use the Read API 10 - Analyze video Understand Azure Video Indexer capabilities Extract custom insights Use Video Analyzer widgets and APIs 11 - Analyze text with Azure AI Language Provision an Azure AI Language resource Detect language Extract key phrases Analyze sentiment Extract entities Extract linked entities 12 - Build a question answering solution Understand question answering Compare question answering to Azure AI Language understanding Create a knowledge base Implement multi-turn conversation Test and publish a knowledge base Use a knowledge base Improve question answering performance 13 - Build a conversational language understanding model Understand prebuilt capabilities of the Azure AI Language service Understand resources for building a conversational language understanding model Define intents, utterances, and entities Use patterns to differentiate similar utterances Use pre-built entity components Train, test, publish, and review a conversational language understanding model 14 - Create a custom text classification solution Understand types of classification projects Understand how to build text classification projects 15 - Create a custom named entity extraction solution Understand custom named entity recognition Label your data Train and evaluate your model 16 - Translate text with Azure AI Translator service Provision an Azure AI Translator resource Specify translation options Define custom translations 17 - Create speech-enabled apps with Azure AI services Provision an Azure resource for speech Use the Azure AI Speech to Text API Use the text to speech API Configure audio format and voices Use Speech Synthesis Markup Language 18 - Translate speech with the Azure AI Speech service Provision an Azure resource for speech translation Translate speech to text Synthesize translations 19 - Create an Azure AI Search solution Manage capacity Understand search components Understand the indexing process Search an index Apply filtering and sorting Enhance the index 20 - Create a custom skill for Azure AI Search Create a custom skill Add a custom skill to a skillset 21 - Create a knowledge store with Azure AI Search Define projections Define a knowledge store 22 - Plan an Azure AI Document Intelligence solution Understand AI Document Intelligence Plan Azure AI Document Intelligence resources Choose a model type 23 - Use prebuilt Azure AI Document Intelligence models Understand prebuilt models Use the General Document, Read, and Layout models Use financial, ID, and tax models 24 - Extract data from forms with Azure Document Intelligence What is Azure Document Intelligence? Get started with Azure Document Intelligence Train custom models Use Azure Document Intelligence models Use the Azure Document Intelligence Studio 25 - Get started with Azure OpenAI Service Access Azure OpenAI Service Use Azure OpenAI Studio Explore types of generative AI models Deploy generative AI models Use prompts to get completions from models Test models in Azure OpenAI Studio's playgrounds 26 - Build natural language solutions with Azure OpenAI Service Integrate Azure OpenAI into your app Use Azure OpenAI REST API Use Azure OpenAI SDK 27 - Apply prompt engineering with Azure OpenAI Service Understand prompt engineering Write more effective prompts Provide context to improve accuracy 28 - Generate code with Azure OpenAI Service Construct code from natural language Complete code and assist the development process Fix bugs and improve your code 29 - Generate images with Azure OpenAI Service What is DALL-E? Explore DALL-E in Azure OpenAI Studio Use the Azure OpenAI REST API to consume DALL-E models 30 - Use your own data with Azure OpenAI Service Understand how to use your own data Add your own data source Chat with your model using your own data 31 - Fundamentals of Responsible Generative AI Plan a responsible generative AI solution Identify potential harms Measure potential harms Mitigate potential harms Operate a responsible generative AI solution

This course presents an approach for dealing with security and privacy throughout the entire software development lifecycle. You will learn about vulnerabilities that undermine security, and how to identify and remediate them in your own projects.

Duration 2 Days 12 CPD hours This course is intended for The target audience for the DevOps Foundation course includes Management, Operations, Developers, QA and Testing professionals such as: Individuals involved in IT development IT operations or IT service management. Individuals who require an understanding of DevOps principles. IT professionals working within, or about to enter, an Agile Service Design Environment The following IT roles: Automation Architects, Application Developers, Business Analysts, Business Managers, Business Stakeholders, Change Agents, Consultants, DevOps Consultants, DevOps Engineers, Infrastructure Architect, Integration Specialists, IT Directors, IT Managers, IT Operations, IT Team Leaders, Lean Coaches, Network Administrators, Operations Managers, Project Managers, Release Engineers, Software Developers, Software Tester/QA, System Administrators, Systems Engineers, System Integrators, Tool Providers. Overview The learning objectives for DevOps Foundation include an understanding of: DevOps objectives and vocabulary Benefits to the business and IT Principles and practices including Continuous Integration, Continuous Delivery, testing, security and the Three Ways DevOps relationship to Agile, Lean and ITSM Improved workflows, communication and feedback loops Automation practices including deployment pipelines and DevOps toolchains Scaling DevOps for the enterprise Critical success factors and key performance indicators Real-life examples and results The DevOps Foundation course provides a baseline understanding of key DevOps terminology to ensure everyone is talking the same language and highlights the benefits of DevOps to support organizational success. Learners will gain an understanding of DevOps, the cultural and professional movement that stresses communication, collaboration, integration, and automation to improve the flow of work between software developers and IT operations professionals. This course prepares you for the DevOps Foundation (DOFD) certification. Exploring DevOps Defining DevOps Why Does DevOps Matter? Core DevOps Principles The Three Ways The First Way The Theory of Constraints The Second Way The Third Way Chaos Engineering Learning Organizations Key DevOps Practices Continuous Testing, Integration, Delivery, Deployment Site Reliability & Resilience Engineering DevSecOps ChatOps Kanban Business and Technology Frameworks Agile ITSM Lean Safety Culture Learning Organizations Continuous Funding Culture, Behaviors & Operating Models Defining Culture Cultural Debt Behavioral Models Organizational maturity models Automation & Architecting DevOps Toolchains CI/CD Cloud, Containers, and Microservices AI and Machine Learning Automation DevOps Toolchains Measurement, Metrics, and Reporting The Importance of Measurement DevOps Metrics - Speed, Quality, Stability, Culture Change lead/cycle time Value Driven Metrics Sharing, Shadowing and Evolving DevOps in the Enterprise Roles DevOps Leadership Organizational Considerations Getting Started Challenges, Risks, and Critical Success Factors Additional course details: Nexus Humans DevOps Foundation (DevOps Institute) 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 DevOps Foundation (DevOps Institute) 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.

Learn user experience fundamentals and master the design process with a user-centered approach. This UX Design Course has been designed to fully equip you with all the tools and methodologies you need to succeed as a UX designer.

DASA DevOps Professional: Enable and Scale: In-House Training DevOps embodies both cultural changes and practices through which organizations can facilitate the IT functions of software development (Dev) and software operation (Ops). The DevOps movement advocates automation and phase-based monitoring practices. Its objectives include: Decreasing development cycles · Increasing deployment frequency Improving the reliability of releases Developing a closer alignment with business objectives The DASA DevOps Professional: Enable and Scale course (formerly known as DevOps Practitioner) is designed to provide individuals with the core education necessary to put DevOps into practice. With the help of DevOps theory, pragmatic examples and exercises, and interactive group discussions, the course will help you understand how to apply the necessary skills to practice DevOps. Building on the knowledge learned on theFundamentals course (the 'why'), you will learn the 'how'. The DevOps Professional: Enable and Scale course focuses on improving the skill set of the DASA competency model, which includes competencies like Courage, Teambuilding, DevOps Leadership, and Continuous Improvement. On completion of the DASA DevOps Professional: Enable and Scale training and passing the exam, the certification is awarded. What you will Learn At the end of this program, you will be able to: Explain the importance of DevOps culture and the aspects that can influence it Explain why courage, teambuilding, leadership, and continuous improvement are required in a DevOps environment Explain why courage is essential to enable trust, honesty, and experimentation Identify and evaluate different types of behavior in a DevOps environment Recognize the signals indicating impediments and/or team dysfunctions Describe how to form good DevOps teams and assess their maturity List the effects of happiness and motivation on team performance Identify how leaders encourage feedback and transparency Discuss the factors that leaders can influence to build trust Explain how and why leaders promote a 'safe to fail' environment Analyze value streams to improve throughput and flow Facilitate the tools for continuous improvement: structured problem-solving workshops, Story Mapping sessions, and retrospectives TEAMBUILDING Teambuilding is about understanding the other's point of view, collaboration, mutual accountability, common purpose, and the ability to integrally support the service/product. Design Teams Characteristics of a DevOps team Skills of a DevOps Team Self-organization and autonomy Rules to consider when designing DevOps teams Build Teams Effects of happiness and motivation on performance Feedback Creating high-performance teams Governance Governance within teams and between multiple teams Governance between organizations DevOps contracts DEVOPS LEADERSHIP This module describes how to facilitate teams to high performance, DevOps behavior, transparency, and a service lifecycle mindset. Build Culture Creating the right environment and providing vision and purpose Stimulating the right behavior Servant leadership: giving control, supporting, and inspiring Create Purpose Defining and aligning purpose Purpose of having a purpose Alignment versus autonomy Be a Servant Leader Give control to the team Inspire and support the team Focus on Success Output versus outcome Measuring and steering COURAGE The Courage module is about coaching courageous behavior, proactivity, reflection, trust, open discussions, experimentation, fail fast, and the courage to change. Build Courage The importance of courage Courage in relationship with leadership and feedback Enabling courage at the team level Dealing with failure Think Different Courage day to day Encourage critical thinking Techniques to promote courageous behavior VALUE CUSTOMER-CENTRIC ACTION This module describes the important aspects that are relevant to identify and deliver the required and expected value for all relevant stakeholders. Aspects of Value and Managing Expectations The different aspects of value Stakeholder management Customer collaboration and using customer feedback How to do prioritization CONTINUOUS IMPROVEMENT Continuous improvement describes the importance of a Kaizen mindset, quality at the source, first time right, knowledge-sharing, and the ability to adapt. Build Flow Understanding the importance of flow Using Lean to optimize flow Kaizen as a mindset Radical change versus Kaizen Using Pull to optimize flow Continuous Improvement Tools Kaizen Event Value Stream Mapping Visual Management Retrospective Daily Standup Five Times Why

DASA DevOps Professional: Enable and Scale: Virtual In-House Training DevOps embodies both cultural changes and practices through which organizations can facilitate the IT functions of software development (Dev) and software operation (Ops). The DevOps movement advocates automation and phase-based monitoring practices. Its objectives include: Decreasing development cycles · Increasing deployment frequency Improving the reliability of releases Developing a closer alignment with business objectives The DASA DevOps Professional: Enable and Scale course (formerly known as DevOps Practitioner) is designed to provide individuals with the core education necessary to put DevOps into practice. With the help of DevOps theory, pragmatic examples and exercises, and interactive group discussions, the course will help you understand how to apply the necessary skills to practice DevOps. Building on the knowledge learned on theFundamentals course (the 'why'), you will learn the 'how'. The DevOps Professional: Enable and Scale course focuses on improving the skill set of the DASA competency model, which includes competencies like Courage, Teambuilding, DevOps Leadership, and Continuous Improvement. On completion of the DASA DevOps Professional: Enable and Scale training and passing the exam, the certification is awarded. What you will Learn At the end of this program, you will be able to: Explain the importance of DevOps culture and the aspects that can influence it Explain why courage, teambuilding, leadership, and continuous improvement are required in a DevOps environment Explain why courage is essential to enable trust, honesty, and experimentation Identify and evaluate different types of behavior in a DevOps environment Recognize the signals indicating impediments and/or team dysfunctions Describe how to form good DevOps teams and assess their maturity List the effects of happiness and motivation on team performance Identify how leaders encourage feedback and transparency Discuss the factors that leaders can influence to build trust Explain how and why leaders promote a 'safe to fail' environment Analyze value streams to improve throughput and flow Facilitate the tools for continuous improvement: structured problem-solving workshops, Story Mapping sessions, and retrospectives TEAMBUILDING Teambuilding is about understanding the other's point of view, collaboration, mutual accountability, common purpose, and the ability to integrally support the service/product. Design Teams Characteristics of a DevOps team Skills of a DevOps Team Self-organization and autonomy Rules to consider when designing DevOps teams Build Teams Effects of happiness and motivation on performance Feedback Creating high-performance teams Governance Governance within teams and between multiple teams Governance between organizations DevOps contracts DEVOPS LEADERSHIP This module describes how to facilitate teams to high performance, DevOps behavior, transparency, and a service lifecycle mindset. Build Culture Creating the right environment and providing vision and purpose Stimulating the right behavior Servant leadership: giving control, supporting, and inspiring Create Purpose Defining and aligning purpose Purpose of having a purpose Alignment versus autonomy Be a Servant Leader Give control to the team Inspire and support the team Focus on Success Output versus outcome Measuring and steering COURAGE The Courage module is about coaching courageous behavior, proactivity, reflection, trust, open discussions, experimentation, fail fast, and the courage to change. Build Courage The importance of courage Courage in relationship with leadership and feedback Enabling courage at the team level Dealing with failure Think Different Courage day to day Encourage critical thinking Techniques to promote courageous behavior VALUE CUSTOMER-CENTRIC ACTION This module describes the important aspects that are relevant to identify and deliver the required and expected value for all relevant stakeholders. Aspects of Value and Managing Expectations The different aspects of value Stakeholder management Customer collaboration and using customer feedback How to do prioritization CONTINUOUS IMPROVEMENT Continuous improvement describes the importance of a Kaizen mindset, quality at the source, first time right, knowledge-sharing, and the ability to adapt. Build Flow Understanding the importance of flow Using Lean to optimize flow Kaizen as a mindset Radical change versus Kaizen Using Pull to optimize flow Continuous Improvement Tools Kaizen Event Value Stream Mapping Visual Management Retrospective Daily Standup Five Times Why

Use Cases for Business Analysis: In-House Training The use case is a method for documenting the interactions between the user of a system and the system itself. Use cases have been in the software development lexicon for over twenty years, ever since it was introduced by Ivar Jacobson in the late 1980s. They were originally intended as aids to software design in object-oriented approaches. However, the method is now used throughout the Solution Development Life Cycle from elicitation through to specifying test cases, and is even applied to software development that is not object oriented. This course identifies how business analysts can apply use cases to the processes of defining the problem domain through elicitation, analyzing the problem, defining the solution, and confirming the validity and usability of the solution. What you will Learn You'll learn how to: Apply the use case method to define the problem domain and discover the conditions that need improvement in a business process Employ use cases in the analysis of requirements and information to create a solution to the business problem Translate use cases into requirements Getting Started Introductions Course structure Course goals and objectives Foundation Concepts Overview of use case modeling What is a use case model? The 'how and why' of use cases When to perform use case modeling Where use cases fit into the solution life cycle Use cases in the problem domain Use cases in the solution domain Use case strengths and weaknesses Use case variations Use case driven development Use case lexicon Use cases Actors and roles Associations Goals Boundaries Use cases though the life cycle Use cases in the life cycle Managing requirements with use cases The life cycle is use case driven Elicitation with Use Cases Overview of the basic mechanics and vocabulary of use cases Apply methods of use case elicitation to define the problem domain, or 'as is' process Use case diagrams Why diagram? Partitioning the domain Use case diagramming guidelines How to employ use case diagrams in elicitation Guidelines for use case elicitation sessions Eliciting the problem domain Use case descriptions Use case generic description template Alternative templates Elements Pre and post conditions Main Success Scenario The conversation Alternate paths Exception paths Writing good use case descriptions Eliciting the detailed workflow with use case descriptions Additional information about use cases Analyzing Requirements with Use Cases Use case analysis on existing requirements Confirming and validating requirements with use cases Confirming and validating information with use cases Defining the actors and use cases in a set of requirements Creating the scenarios Essential (requirements) use case Use case level of detail Use Case Analysis Techniques Generalization and Specialization When to use generalization or specialization Generalization and specialization of actors Generalization and specialization of use cases Examples Associating generalizations Subtleties and guidelines Use Case Extensions The <> association The <> association Applying the extensions Incorporating extension points into use case descriptions Why use these extensions? Extensions or separate use cases Guidelines for extensions Applying use case extensions Patterns and anomalies o Redundant actors Linking hierarchies Granularity issues Non-user interface use cases Quality considerations Use case modeling errors to avoid Evaluating use case descriptions Use case quality checklist Relationship between Use Cases and Business Requirements Creating a Requirements Specification from Use Cases Flowing the conversation into requirements Mapping to functional specifications Adding non-functional requirements Relating use cases to other artifacts Wire diagrams and user interface specifications Tying use cases to test cases and scenarios Project plans and project schedules Relationship between Use Cases and Functional Specifications System use cases Reviewing business use cases Balancing use cases Use case realizations Expanding and explaining complexity Activity diagrams State Machine diagrams Sequence diagrams Activity Diagrams Applying what we know Extension points Use case chaining Identifying decision points Use Case Good Practices The documentation trail for use cases Use case re-use Use case checklist Summary What did we learn, and how can we implement this in our work environment?

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.