1400 Opera courses in Belfast delivered Live Online

Assuring Quality Through Acceptance Testing: Virtual In-House Training It is also the business analyst's responsibility to confirm that the resulting solution developed by IT does, in fact, solve the defined problem. This is done first through testing, especially acceptance testing, and then through monitoring of the installed solution in the user community. It is the business analyst's job to define the business problem to be solved by IT. It is also the business analyst's responsibility to confirm that the resulting solution developed by IT does, in fact, solve the defined problem. This is done first through testing, especially acceptance testing, and then through monitoring of the installed solution in the user community. The business analyst is not only concerned with the testing itself, but also with the management and monitoring of the users doing the acceptance testing, and recording, analyzing, and evaluating the results. What you will Learn Upon completion, participants will be able to: Create a set of acceptance test cases Manage and monitor an acceptance test stage where users perform the testing Work with the development team in the systems testing stage Assess the solution once it is in the business environment Foundation Concepts The role of the business analyst An introduction to the BABOK® Guide BA roles and relationships through the project life cycle Introduction to assuring software quality through acceptance testing The Scope of IT Testing Overview of testing stages The testing process Testing documentation Pre-Acceptance Testing The BA's role in testing Early development testing stages (unit and integration) Late development testing stage (system) The Acceptance Test Stage - Part I (Planning, Design, and Development) Overview of user acceptance testing Acceptance test planning Designing user acceptance tests Developing individual user acceptance test cases Building effective user acceptance test scenarios The Acceptance Test Stage - Part II (Execution and Reporting) Operating guidelines Execution Reporting Post-Acceptance Testing Overview Project implementation Project transition (project closure) Production through retirement Testing Commercial Off-the-Shelf (COTS) Software Overview Selecting the software Implementing the software Summary What did we learn and how can we implement this in our work environments?

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Project Risk Management: Virtual In-House Training Have you been surprised by unplanned events during your projects? Are you and your project team frequently fighting fires? Well, you are not alone. Uncertainty exists in any project environment. While it's impossible to predict project outcomes with 100% certainty, you can influence the outcome, avoid potential risks, and be ready to respond to challenges that arise. In this course, you'll gain the proper knowledge needed to identify, assess, plan for, and monitor risk in your projects. You'll learn how to set up and implement risk management processes, helping you to minimize uncertainty and achieve more consistent, predictable outcomes as a result. What You Will Learn You'll learn how to: Demonstrate to others how the risk management processes in A Guide to the Project Management Body of Knowledge (PMBOK® Guide) apply to your project's environment, especially for high-risk projects Adapt these processes for a particular high-risk project team's operating principles Explain the importance of using risk management best practices at single and enterprise project levels Lead an initiative to implement risk management best practices in your project environment Foundation Concepts Risk-related definitions The risk management process High-risk projects and project failures Classical failures in implementing risk management Plan Risk Management Project risk management and governance Risk management planning for high-risk projects High-risk variations on a risk management plan Identify Risk Adapting the risk identification process for high-risk projects Recognizing risks spontaneously Confirming and structuring risk events for treatment Wrapping up risk identification for high-risk projects Perform Qualitative Risk Analysis Adapting qualitative risk analysis for high-risk projects Accelerating risk analysis Clearing risk action Wrapping up qualitative risk analysis for the next level Perform Quantitative Risk Analysis Adapting quantitative risk analysis for high-risk projects Ensuring effective risk analyses with data quality assessments Building a foundation for quantitative risk analysis Using discrete quantitative tools Using continuous quantitative tools Wrapping up quantitative risk analysis for high-risk projects Plan Risk Responses Adapting risk response planning for high-risk projects Optimizing active risk response strategies Leveraging contingencies for high project performance Wrapping up risk response planning for high-risk projects Implement Risk Responses Implementing Risk Responses Process Executing Risk Response Plans Tools and Techniques Best Practices Continuous Risk Management Monitor Risks Adapting risk monitoring for high-risk projects Optimizing risk plan maintenance Weaving risk reassessment into the project's progress Maintaining a continuous 'vigil' in high-risk project environments

Business Intelligence: Virtual In-House Training Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence

This practitioner-level 4 award encourages individuals in IT and technical roles to explore the many teams, ideas, and functions within an organisation and maximise their contribution. You will achieve this by learning the key concepts and considering behaviour and response in different scenarios.

This course will create insight about carbon,carbon emission, Green House Gases ( GHG's) and the voluntary carbon market. It will enable learners understand the concept of climate change, as well as nature based solutions to mitigate climate change

The course will be delivered through 9 online virtual classroom sessions. The 10th and last session will involve the additional practical work for the course as well as the written examination (multiple choice for City & Guilds and written for Hi-Tech Training) which will take place at our training centre at 43 North Great Georges Street, Dublin 1 (completed online for non ROI learners). During the virtual classroom sessions, trainees will have a live video feed with their instructor talking to them, doing practical live demonstrations on equipment being involved actively in the learning. We will send out a practical kit so that trainees can complete assignments and practical work at home. The kit is the property of Hi-Tech Training and will be returned to Hi-Tech Training on the last day of the course. (The kits may also be purchased by the learner….see the Kits Page Link for more details). The kit consists of power supply unit breadboard, multimeter, cables, The kit consists of breadboard, multimeter, oscilloscope, battery and connectors, components including resistors, LEDs and ICs (AND, NAND, OR, NOR, X-OR, X-NOR, Inverter, Buffer, Latches, Flip-Flops, Timers, etc). Trainees will build various projects as part of the course. The kit forms an integral part of the course, so full course fees need to be paid at least 7 days prior to course commencement to allow time to ship the kit in time for the course.

Immerse yourself in the ancient practice of yoga, a transformative journey that extends far beyond the mere physical postures. Our comprehensive yoga sessions are meticulously curated and led by seasoned professionals, offering a serene sanctuary tailored for the demands of modern-day professionals yearning for holistic balance and wellness. Delve into innate human abilities such as intuition, telepathy, clairvoyance, lucid dreaming, and energy healing. Uncover these dormant gifts existing within and enjoy awakening them fully.

Rhino Basic to Intermediate Training Course

Duration 1 Days 6 CPD hours This course is intended for The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don?t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful. This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. Prerequisites Prerequisite certification is not required before taking this course. Successful Azure AI Fundamental students start with some basic awareness of computing and internet concepts, and an interest in using Azure AI services. Specifically: Experience using computers and the internet. Interest in use cases for AI applications and machine learning models. A willingness to learn through hands-on exp... 1 - Fundamental AI Concepts Understand machine learning Understand computer vision Understand natural language processing Understand document intelligence and knowledge mining Understand generative AI Challenges and risks with AI Understand Responsible AI 2 - Fundamentals of machine learning What is machine learning? Types of machine learning Regression Binary classification Multiclass classification Clustering Deep learning Azure Machine Learning 3 - Fundamentals of Azure AI services AI services on the Azure platform Create Azure AI service resources Use Azure AI services Understand authentication for Azure AI services 4 - Fundamentals of Computer Vision Images and image processing Machine learning for computer vision Azure AI Vision 5 - Fundamentals of Facial Recognition Understand Face analysis Get started with Face analysis on Azure 6 - Fundamentals of optical character recognition Get started with Vision Studio on Azure 7 - Fundamentals of Text Analysis with the Language Service Understand Text Analytics Get started with text analysis 8 - Fundamentals of question answering with the Language Service Understand question answering Get started with the Language service and Azure Bot Service 9 - Fundamentals of conversational language understanding Describe conversational language understanding Get started with conversational language understanding in Azure 10 - Fundamentals of Azure AI Speech Understand speech recognition and synthesis Get started with speech on Azure 11 - Fundamentals of Azure AI Document Intelligence Explore capabilities of document intelligence Get started with receipt analysis on Azure 12 - Fundamentals of Knowledge Mining with Azure Cognitive Search What is Azure Cognitive Search? Identify elements of a search solution Use a skillset to define an enrichment pipeline Understand indexes Use an indexer to build an index Persist enriched data in a knowledge store Create an index in the Azure portal Query data in an Azure Cognitive Search index 13 - Fundamentals of Generative AI What is generative AI? Large language models What is Azure OpenAI? What are copilots? Improve generative AI responses with prompt engineering 14 - Fundamentals of Azure OpenAI Service What is generative AI Describe Azure OpenAI How to use Azure OpenAI Understand OpenAI's natural language capabilities Understand OpenAI code generation capabilities Understand OpenAI's image generation capabilities Describe Azure OpenAI's access and responsible AI policies 15 - 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 Additional course details: Nexus Humans AI-900T00 - Microsoft Azure AI Fundamentals 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 AI-900T00 - Microsoft Azure AI Fundamentals 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.