452 Developer courses in Cardiff delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques.Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course.This skills-focused ccombines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Applied AI: Building Recommendation Systems with Python (TTAI2360) 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 Applied AI: Building Recommendation Systems with Python (TTAI2360) 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.

Duration 5 Days 30 CPD hours This course is intended for This course is designed for technology leaders, solution developers, project managers, organizational decision makers, and other individuals seeking to demonstrate a vendor-neutral, cross-industry understanding of ethics in emerging data-driven technologies, such as AI, robotics, IoT, and data science. This course is also designed for professionals who want to pursue the CertNexus Certification Exam CET-110: Certified Ethical Emerging Technologies. Overview In this course, you will incorporate ethics into data-driven technologies such as AI, IoT, and data science. You will: Describe general concepts, theories, and challenges related to ethics and emerging technologies. Identify ethical risks. Practice ethical reasoning. Identify and mitigate safety and security risks. Identify and mitigate privacy risks. Identify and mitigate fairness and bias risks. Identify and mitigate transparency and explainability risks. Identify and mitigate accountability risks. Build an ethical organization. Develop ethical systems in technology-focused organizations. Mutually reinforcing innovations in computing and engineering are catapulting advances in technological production. From blockchain and artificial intelligence (AI) to gene editing and the Internet of Things (IoT), these advances come with tremendous opportunities for improvement in productivity, efficiency, and human well-being. But as scandals increasingly demonstrate, these advances also introduce new and serious risks of conflict and harm.Technology professionals now face growing demands to identify and mitigate ethical risks to human rights and the environment, as well as to navigate ethical tradeoffs between qualities such as privacy and accuracy, fairness and utility, and safety and accountability. This course provides the tools to identify and manage common ethical risks in the development of emerging data-driven technologies. It distills ethical theory, public regulations, and industry best practices into concrete skills and guidelines needed for the responsible development of digital products and services. By following the course's practical, problems-based approach, learners will become adept at applying theories, principles, frameworks, and techniques in their own roles and organizations. Introduction to Ethics of Emerging Technologies Topic A: What?s at Stake Topic B: Ethics and Why It Matters Topic C: Ethical Decision-Making in Practice Topic D: Causes of Ethical Failures Identifying Ethical Risks Topic A: Ethical Reasons Topic B: Stumbling Blocks for Ethical Reasoning Topic C: Identify Ethical Risks in Product Development Topic D: Tools for Identifying Ethical Risks Topic E: Use Regulations, Standards, and Human Rights to Identify Ethical Risks Ethical Reasoning in Practice Topic A: Ethical Theories Topic B: Use Ethical Decision-Making Frameworks Topic C: Select Options for Action Topic D: Avoid Problems in Ethical Decision-Making Identifying and Mitigating Security Risks Topic A: What Is Security? Topic B: Identify Security Risks Topic C: Security Tradeoffs Topic D: Mitigate Security Risks Identifying and Mitigating Privacy Risks Topic A: What Is Privacy? Topic B: Identify Privacy Risks Topic C: Privacy Tradeoffs Topic D: Mitigate Privacy Risks Identifying and Mitigating Fairness and Bias Risks Topic A: What Are Fairness and Bias? Topic B: Identify Bias Risks Topic C: Fairness Tradeoffs Topic D: Mitigate Bias Risks Identifying and Mitigating Transparency and Explainability Risks Topic A: What Are Transparency and Explainability? Topic B: Identify Transparency and Explainability Risks Topic C: Transparency and Explainability Tradeoffs Topic D: Mitigate Transparency and Explainability Risks Identifying and Mitigating Accountability Risks Topic A: What Is Accountability? Topic B: Identify Accountability Risks Topic C: Accountability Tradeoffs Topic D: Mitigate Accountability Risks Building an Ethical Organization Topic A: What Are Ethical Organizations? Topic B: Organizational Purpose Topic C: Ethics Awareness Topic D: Develop Professional Ethics within Organizations Developing Ethical Systems in Technology-Focused Organizations Topic A: Policy and Compliance Topic B: Metrics and Monitoring Topic C: Communication and Stakeholder Engagement Topic D: Ethical Leadership

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview This skills-focused combines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques. Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Building Recommendation Systems with Python (TTAI2360) 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 Building Recommendation Systems with Python (TTAI2360) 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.

Duration 3 Days 18 CPD hours This course is intended for This course is intended for Information workers, IT Professionals and Developers. Students should have an existing working knowledge of either Microsoft Dynamics 365 or Microsoft Dynamics CRM. Overview Understand the features and tools that exist in Microsoft Dynamics 365 for Customizers Be aware of integrating complimenting Microsoft products such as SharePoint, Skpe for Business and Exchange Undertake and carry out the initial setup and configuration required in a Microsoft Dynamics 365 deployment Design and configure a comprehensive Security model using the inbuilt tools in Microsoft Dynamics 365 Customize the Dynamics 365 schema by creating custom Entities, Fields and Relationships Design custom Information Forms, Quick View Forms, Quick Create Forms and System Views Create System Charts, Dashboards and Interactive Experience Dashboards Create and manage Business Rules using the Business Rule Designer Plan, design and implement best practice Workflow, Business Process Flows and Custom Actions Be able to apply best practice methodology using Unmanaged and Managed Solutions to deploy Microsoft Dynamics 365 customizations and patches This course provides students with a detailed hands-on experience of setting up, customizing, configuring and maintaining the CRM components of Microsoft Dynamics 365. Attendees of this course will gain an in-depth understanding of the Dynamics 365 security model, learn how to customize the Dynamics 365 framework, create and maintain powerful workflows and business process flows and use solutions to package and deploy customizations across multiple Dynamics 365 environments. The course applies to both Business and Enterprise Editions of Dynamics 365 as well as Online and On-premise deployments. Introduction Getting familiar with the versions of Microsoft Dynamics CRM\365 Get acquainted with the Dynamics 365 framework Review the Dynamics 365 interfaces, devices and apps Understand the tools for Dynamics 365 customizers A brief overview of Solutions Understand the differences between Dynamics 365 organisations and environments Review further reading and resources Set up the lab environment - Acme Enterprises Event Management Solution Initial Setup and Configuration An introduction to Dynamics 365 online setup An introduction to Dynamics 365 on premise setup Review the System Settings area Understand how to configure Auto Save Settings Understand how to configure Format Settings Understand how to configure Email Settings Understand how to configure Skype Integration Understand how to configure SharePoint Integration Security Design and configure Business Units Configure Security Roles Manage Users and Teams Implement Access Teams Configure Hierarchy Security Creating and Managing Entities Introduction to the Dynamics 365 schema Review the different Entity Types Create new Custom Entities Managing Entity Ownership Managing Entity Properties Custom Entity Security Review Entities and Solutions Customizing Fields Introduction to Field Customization Understand the different Field Types Review Field Formats Create a new Field Review Fields and Solutions Implement a Calculated Field Configure Field Level Security Customizing Relationships and Mappings Introduction to Relationships Review the different Relationship Types Create a Relationship Review Relationships and Solutions Understand Relationship Behavior Implement a Hierarchy Relationship Configure Field Mappings Customizing Forms, Views and Visualizations The process to create a new Form Review the different Form types Using the Form Designer Customizing the Main, Quick View and Quick Create Forms Configure Form Security Review the different View types Customizing System Views Customizing System Charts and Dashboards Workflows, Business Process Flows and Custom Actions Introduction to Processes Workflow Business Process Flows Custom Actions Solution Management An introduction to Solution Management How to add and administer components in a Solution The differences between unmanaged and managed Solutions How to export and import a Solution How to set Managed Properties for a Solution What happens when you delete a Solution How to Clone a Solution Patch How to Clone a Solution

Duration 1.875 Days 11.25 CPD hours This course is intended for The job roles best suited to the material in this course are: team leaders, project managers, managers of scrum teams, teams transitioning to scrum, professionals intending to pursue the scrum master certification. Overview How to use the Scrum Framework to deliver products and services faster and with higher quality. How to leverage lean principles to identify waste in a system, process, or organization. Techniques and metics Scrum Masters use to improve. team happiness and performance. The patterns and practices of high-performing teams. How the Scrum Master role scales in an Agile implementation. This course is an adaptive, repeatable process that equips individuals and organizations in how to thrive in a world where change is the only constant. From Fortune 100 companies (Google, Amazon, Apple, etc) to nonprofits. Scrum has a proven record of reducing burnout, doubling throughput in half the time, and increase employee happiness. Core Scrum The Scrum Framework The Origins of Scrum (Optional) The Scrum Team Developers Scrum Master Leadership/Management Scrum Events The Sprint Product Backlog Re1nement Estimation Sprint Planning Sprint Review Sprint Retrospective Daily Scrum Scrum Artifacts Lean Principles Describe a Kaizen mindset and explain how small, iterative changes can lead to revolutionary leaps. Describe the three pillars of Scrum ? Transparency, Inspection, and Adaptation,? which implement the work of Ogunnaike and Ray. Explain the importance of reducing and eliminating waste in the system. Perform a root-cause analysis (e.g., using the ?5 Whys? technique). Assess the Process EZciency of their Scrum Team and recall that the de1nition of Lean is a Process EZciency of 25% or higher. Explain how the work of Takeuchi and Nonaka on Lean and the Toyota Production System paved the way for Scrum. Describe the origins of the name ?Scrum? from Takeuchi and Nonaka?s ?New New Product Development Game. Recognize that a Lean mindset suggests that you address a defect immediately after it is identi1ed as opposed to a mindset where defects are stored to be 1xed later. Agile Manifesto Recognize the four values of the Agile Manifesto and their signi1cance in the context of complex adaptive systems. Identify the 12 principles of the Agile Manifesto and describe their function in guiding practices that support teams in implementing and executing with agility. Explain that Scrum is one of the driving forces that gave rise to the Agile movement and predates the Agile Manifesto. Explain why the majority of ?Agile? teams are late, over-budget, and with unhappy customers (i.e., not agile) and explain what needs to be done to 1x that. Patterns of High Performing Teams Yesterday?s Weather Happiness Metric Teams that Finish Early Accelerate Faster Stable Teams Swarming Interrupt Buffer Good Housekeeping (formerly Daily Clean Code) Scrum Emergency Procedure Scrum@Scale Descaling Scaling the Scrum Master Registered Scrum Master Credential Access and complete the Registered Scrum Master by Scrum Inc. exam. Download their Registered Scrum Master Credential (upon successful completion of the exam). Be Recognized in the International Registry of Agile ProfesstionalsTM State the renewal process. Additional course details: Nexus Humans Agile Scrum 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 Agile Scrum 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.

Duration 3 Days 18 CPD hours This course is intended for This course is ideal for developers and engineers including: Cloud administrators Cloud solution architects Customer sales engineers DevOps engineers Sales engineers Systems engineers Technical solutions architects Overview After completing the course, you should be able to: Explain business and technical challenges of going to the cloud Understand benefits of an application-centric hybrid cloud multicloud management platform Navigate Cisco CloudCenter Suite architecture Understand Cisco CloudCenter Suite administrative capabilities including cloud management, multitenancy, governance, and policy enforcement Describe application lifecycle management and provisioning in cloud Describe how to use Cisco CloudCenter Suite to manage the workloads in multicloud The course, Mulitcloud Management with Cisco© CloudCenter Suite (CLDCCS) v1.0 is an intensive training course that teaches you to securely design, automate, and deploy applications across multiple clouds while optimizing cost and compliance with comprehensive reporting, visibility, and policy-enforcement. Through a combination of lessons with hands-on lab exercises, you will learn to simplify the lifecycle management of multicloud applications, workflows, and their infrastructure Understanding Cloud Transitions Overview of Traditional IT Introducing Cisco CloudCenter Suite Cisco CloudCenter Suite Definition Setting Up Cisco CloudCenter Workload Manager Artifact Repository Overview and Configuration Understanding User Administration and Multitenancy in Cisco CloudCenter Suite Cisco CloudCenter Suite User Roles Grasping Application Modeling in Cisco CloudCenter Workload Manager Model an Application Identifying Resource Placement Callouts and Lifecycle Actions in Cisco CloudCenter Workload Manager Resource Placement and Validation Callout Understanding Application Deployment Framework in Cisco CloudCenter Workload Manager Workload Manager Application Parameters Exploring Application Services in Cisco CloudCenter Workload Manager Application Services Framework Integrating Cisco CloudCenter Workload Manager with Cisco Application-Centric Infrastructure Configure CloudCenter Workload Manager for Cisco ACI Introducing Application Management in Cisco CloudCenter Workload Manager Cisco CloudCenter Workload Manager Actions Library Exploring Advanced Features in CloudCenter Workload Manager Scheduling an Application in Cisco CloudCenter Workload Manager Comprehending Policies and Tagless Governance in CloudCenter Workload Manager Cisco CloudCenter Workload Manager Policies Introducing Action Orchestrator and Cost Optimizer in Cisco CloudCenter Suite Action Orchestrator in Cisco CloudCenter Suite Lab outline Explore Cisco CloudCenter Suite Admin GUI Discover Cisco CloudCenter Workload Manager GUI Create Cisco CloudCenter Workload Manager Repository Design Deployment Environments in Cisco CloudCenter Workload Manager Create Images in Cisco CloudCenter Workload Manager Form Cost Bundles and Usage Plans in Cisco CloudCenter Workload Manager Explore Multitenancy in Cisco CloudCenter Suite Model and Deploy Two-Tier Application Model and Deploy Multitier Application Perfect and Arrange Multitier Application on Docker Model and Deploy Application on Kubernetes Cloud Deploy Application in Hybrid Cloud Arrange Application Using Automated Resource Placement Perform Lifecycle Actions on Deployed Applications Create User-Defined Parameters and Explore Macros Understand Application Services in Cisco CloudCenter Workload Manage Benchmark, Schedule, and Share Applications in Cisco CloudCenter Workload Manager Continuous Integration/Continuous Delivery (CI/CD) Project Board Manage Policies in Cisco CloudCenter Workload Manager Manage System Tags and Governance in Cisco CloudCenter Workload Manager Explore Action Orchestrator Explore Cost Optimizer Additional course details: Nexus Humans Cisco Multicloud Management with Cisco CloudCenter Suite (CLDCCS) v1.0 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 Cisco Multicloud Management with Cisco CloudCenter Suite (CLDCCS) v1.0 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.

Duration 3 Days 18 CPD hours This course is intended for This course is designed for project managers, Scrum masters, business analysts, and team leaders looking to effectively manage their development projects using Team Foundation Server 2017. Overview The course also demonstrates how TFS facilitates the use of storyboards to prototype experiences, request stakeholder feedback, foster team collaboration, and generate reports. The final two modules of the course provide an overview of how testers and developers can work effectively using appropriate tools in the Visual Studio family. In this course, attendees will plan a new software development project and go through the steps to initiate the project using Visual Studio 2017. This includes recording requirements, creating a product backlog, and estimating effort for backlog items. Introducing the Microsoft Visual Studio 2017 Family What?s new in Visual Studio 2017 Overview of the Visual Studio 2017 family Overview of product features Project workflow across the Visual Studio 2017 suite of products Initiating a New Project Organizing projects in TFS Understanding process templates Creating a new team project Setting team project properties Switching between team projects Work Item Primer Overview of work items Traceability between work items Searching and creating custom queries Work item charting and pinning charts Work item tagging Configuring project notifications Creating our Product Backlog Examining requirement types Creating backlog items Creating requirement hierarchies using features The importance of acceptance criteria Agile Estimation Introduction to estimation Using story points Planning Poker and other popular estimation techniques Adding your estimates to TFS work items Working from the Product Backlog Introducing the Kanban board Entering and editing details on the Kanban board Customizing columns, including using split columns and limiting WIP Recording our Definition of Done (DoD) Understanding the Cumulative Flow Diagram Working in Sprints Specifying your sprint schedule and your team capacity Selecting items for the sprint backlog using forecasting Decomposing requirements into tasks Using burndown charts to track progress Monitoring work using the task board Working with unparented work items Retrospectives The importance of retrospectives Conducting an efficient sprint retrospective What you should avoid in your retrospective Working with TFS Teams Configuring teams in our team project Managing work from a master backlog Allocating work to our teams Configuring iterations for TFS teams Enhancing Requirements Using Storyboards Overview of storyboarding capabilities Creating a storyboard to illustrate a requirement Linking a storyboard to a work item Getting Stakeholder Feedback Introducing the Microsoft Feedback Client Using the Microsoft Feedback Client to provide rich feedback to the team Adding continuous feedback into your workflow Fostering Team Collaboration An overview of the various clients The use of email in sharing information Choosing the appropriate client tool Creating and Customizing Reports Overview of reporting architecture Reviewing the out of the box reports Adding new reports Creating ad hoc reports using Excel Overview of Agile Testing The role of the tester in a sprint planning meeting A lap around web-based test management Creating a test plan Creating manual test cases from requirements Overview of Agile Development Using My Work to select tasks from the sprint backlog Understanding the value of linking changesets to work items The importance of unit testing Creating a continuous integration build Additional course details: Nexus Humans Managing Agile Projects Using TFS 2017 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 Managing Agile Projects Using TFS 2017 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.

Duration 3 Days 18 CPD hours This course is intended for This is an introductory-level XML training course, designed for those needing an introduction to concepts and technologies associated with XML and its related recommendations. Previous experience or knowledge of HTML is helpful but not essential. Overview This course is an intensive, hands-on introduction to XML, XPath, and XSLT. The course is a balanced mixture of theory and practical labs designed to take students from the basic fundamentals of XML through to the related advanced technologies. The students walk through the different standards in a structured manner to enable them to master the concepts and ideas, which are reinforced in the lab exercises. The course starts with the fundamentals of XML, including coverage of DTDs and XML Schema. It then moves on to the XPath and XSLT standards, and how to use them to transform XML documents into other documents such as HTML documents or other XML documents. This course provides indoctrination in the practical use of W3C standards (including XSL and XML Schema) and of implementing tools and technologies. This course is programming language independent, making it useful for Java, .NET, C++, and any other programming orientation. Graduates will hit the ground running, applying XML to projects at both an architectural as well as a line by line coding level. We can easily adapt this course to industry and client specific needs.In addition to valuable knowledge and working examples, students receive a copy of the 'Xtensil' product. This unique software was developed to assist in implementing, testing, and fielding XML applications. Xtensil is used as both a teaching aid and a straightforward, basic, fully functional XML toolkit that students can use on Windows and Linux platforms. Working in a hands-on learning environment student will learn to: Write well-formed XML documents Model business requirements using XML Handle XML reserved characters Validate an XML document with a DTD and with a Schema Centralize data and markup definition with entities Create DTDs and Schemas using XML tools Generate XML documents from databases Write XSL templates to transform XML documents into HTML Integrate XML, XSL and the DOM to implement a complete solution The Extensible Markup Language (XML) is a standard that is enabling a revolution in web applications and business to business interactions. XML is the basis for Wireless Markup Language (WML), Voice Markup Language (VoiceML), Simple Object Access Protocol (SOAP), Web Services, and numerous industry initiatives such as ACORD (insurance), PXML (proposal/RFP) and OTA (travel). Introduction to XML is a three-day, hands-on course geared for software developers who need to understand what XML is and how to use in with today's systems and architectures. This course covers the topics from tags to architectures. The course is a balanced mixture of theory and practical labs designed to take students from a quick review of the basic fundamentals of XML through to the related advanced technologies. The students walk through the different standards in a structured manner to enable them to master the concepts and ideas, which are reinforced in the lab exercises. The course starts with a quick review of the fundamentals of XML before covering XML Schema in detail. It then moves on to the XPath and XSLT covering advanced topics in both. Finally, XML and Web Services security mechanisms and issues are addressed. XML Content Introduction to XML XML Mechanics XML Structure Namespaces Structure Using Schemas XML Formatting CSS and Rendering XML XSL Transformations XSLT and XPath XPath 2.0 and XSLT 2.0 Overview XSL FO (Formatting Objects) Applying XML XML Interoperability XML Performance Improvements Web Services Overview XML Applications Additional course details: Nexus Humans Introduction to XML (TT4300) 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 Introduction to XML (TT4300) 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.

Duration 2 Days 12 CPD hours This course is intended for The introductory-level course is geared for software developers, project managers, and IT professionals seeking to enhance their understanding and practical skills in version control and collaboration using GitLab. It's also well-suited for those transitioning from another version control system to GitLab, or those responsible for software development lifecycle within their organization. Whether you are an individual looking to boost your proficiency or a team leader aiming to drive productivity and collaboration, this course will provide the necessary expertise to make the most of GitLab's capabilities. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Gain a firm understanding of the fundamentals of Git and GitLab, setting a solid foundation for advanced concepts. Learn to effectively manage and track changes in your code, ensuring a clean and reliable codebase. Discover ways to streamline your daily tasks with aliases, stashing, and other GitLab workflow optimization techniques. Develop skills in creating, merging, and synchronizing branches, enabling seamless collaboration and version control. Equip yourself with the knowledge to use Git as a powerful debugging tool, saving time and effort when troubleshooting issues. Understand the basics of continuous integration and continuous deployment (CI/CD) in GitLab, helping you automate the software delivery process. Immerse yourself in the dynamic world of GitLab, a leading web-based platform for version control and collaboration, through our intensive two-day course, GitLab Quick Start. Version control systems, such as GitLab, are the backbone of modern software development, enabling teams to work cohesively and maintain a structured workflow. By mastering GitLab, you can improve efficiency, encourage collaboration, and ensure accuracy and reliability within your projects, adding significant value to your organization. Throughout the course you?ll explore various aspects of GitLab, starting from the fundamental principles of source code management to advanced concepts like rebasing and continuous integration/design. Key topics covered include Git and GitLab basics, reviewing and editing commit history, mastering GitFlow and GitLab Flow, branching and merging strategies, and understanding remote repositories. You'll also learn how to utilize Git as a debugging tool and explore the power of GitLab's built-in CI/CD capabilities. The core value of this course lies in its practical application. You'll learn how to effectively manage changes in code with GitLab, allowing you to maintain audit trails, create reproducible software, and seamlessly move from another version control system. Then you?ll learn how to enhance your workflow efficiency using aliases for common commands, saving changes for later use, and ignoring build artifacts. You?ll also explore GitLab's CI/CD, which will enable you to automate your software delivery process. These hands-on labs will walk you through creating, merging, and synchronizing remote branches, configuring Git, troubleshooting using Git as a debugging tool, and setting up GitLab Runner for CI/CD. Each lab is designed to simulate real-world projects, offering you a first-hand experience in managing and contributing to a version control system like GitLab. Introduction to Source Code Management The Core Principles of Change Management The Power to Undo Changes Audit Trails and Investigations Reproducible Software Changing code-hosting platform Moving from another version control system Git and GitLab Introduction and Basics Introduction to Git GitFlow GitLab Flow Trees and Commits Configuring Git Adding, Renaming, and Removing Files Reviewing and Editing the Commit History Reviewing the Commit History Revision Shortcuts Fixing Mistakes Improving Your Daily Workflow Simplifying Common Commands with Aliases Ignoring Build Artifacts Saving Changes for Later Use (Stashing) Branching Branching Basics Listing Differences Between Branches Visualizing Branches Deleting Branches Tagging Merging Merging Basics Merge Conflicts Merging Remote Branches Remote Repositories Remote Repositories Synchronizing Objects with Remotes Tracking Branches Centralizing and Controlling Access Introduction to GitLab Git Repositories on GitLab Daily Workflow Reviewing Branching and Merging Branch Review Merging Basics Rebasing Rebasing Basics Rebasing with Local Branches Rebasing with Remote Branches Interactive Rebasing Squashing Commits Getting Out of Trouble Git as a Debugging Tool Using the Blame Command to See File History Performing a Binary Search Continuous Integration / Continuous Design (CI/CD) How to install GitLab Runner Adding to our example project Breaking down .gitlab-ci.yml Adding .gitlab-ci.yml to our example project Deconstructing an advanced .gitlab-ci.yml file GitLab CI/CD web UI Optional: Resetting Trees Introduction to Resetting Resetting Branch Pointers Resetting Branches and the Index Resetting the Working Directory Making Good Use of the Reset Command Optional More on Improving Your Daily Workflow Interactively Staging Changes Optional: Including External Repositories Submodules Subtrees Choosing Between Submodules and Subtrees Workflow Management Branch Management

Duration 5 Days 30 CPD hours This course is intended for This intermediate and beyond level course is geared for experienced technical professionals in various roles, such as developers, data analysts, data engineers, software engineers, and machine learning engineers who want to leverage Scala and Spark to tackle complex data challenges and develop scalable, high-performance applications across diverse domains. Practical programming experience is required to participate in the hands-on labs. Overview Working in a hands-on learning environment led by our expert instructor you'll: Develop a basic understanding of Scala and Apache Spark fundamentals, enabling you to confidently create scalable and high-performance applications. Learn how to process large datasets efficiently, helping you handle complex data challenges and make data-driven decisions. Gain hands-on experience with real-time data streaming, allowing you to manage and analyze data as it flows into your applications. Acquire practical knowledge of machine learning algorithms using Spark MLlib, empowering you to create intelligent applications and uncover hidden insights. Master graph processing with GraphX, enabling you to analyze and visualize complex relationships in your data. Discover generative AI technologies using GPT with Spark and Scala, opening up new possibilities for automating content generation and enhancing data analysis. Embark on a journey to master the world of big data with our immersive course on Scala and Spark! Mastering Scala with Apache Spark for the Modern Data Enterprise is a five day hands on course designed to provide you with the essential skills and tools to tackle complex data projects using Scala programming language and Apache Spark, a high-performance data processing engine. Mastering these technologies will enable you to perform a wide range of tasks, from data wrangling and analytics to machine learning and artificial intelligence, across various industries and applications.Guided by our expert instructor, you?ll explore the fundamentals of Scala programming and Apache Spark while gaining valuable hands-on experience with Spark programming, RDDs, DataFrames, Spark SQL, and data sources. You?ll also explore Spark Streaming, performance optimization techniques, and the integration of popular external libraries, tools, and cloud platforms like AWS, Azure, and GCP. Machine learning enthusiasts will delve into Spark MLlib, covering basics of machine learning algorithms, data preparation, feature extraction, and various techniques such as regression, classification, clustering, and recommendation systems. Introduction to Scala Brief history and motivation Differences between Scala and Java Basic Scala syntax and constructs Scala's functional programming features Introduction to Apache Spark Overview and history Spark components and architecture Spark ecosystem Comparing Spark with other big data frameworks Basics of Spark Programming SparkContext and SparkSession Resilient Distributed Datasets (RDDs) Transformations and Actions Working with DataFrames Spark SQL and Data Sources Spark SQL library and its advantages Structured and semi-structured data sources Reading and writing data in various formats (CSV, JSON, Parquet, Avro, etc.) Data manipulation using SQL queries Basic RDD Operations Creating and manipulating RDDs Common transformations and actions on RDDs Working with key-value data Basic DataFrame and Dataset Operations Creating and manipulating DataFrames and Datasets Column operations and functions Filtering, sorting, and aggregating data Introduction to Spark Streaming Overview of Spark Streaming Discretized Stream (DStream) operations Windowed operations and stateful processing Performance Optimization Basics Best practices for efficient Spark code Broadcast variables and accumulators Monitoring Spark applications Integrating External Libraries and Tools, Spark Streaming Using popular external libraries, such as Hadoop and HBase Integrating with cloud platforms: AWS, Azure, GCP Connecting to data storage systems: HDFS, S3, Cassandra, etc. Introduction to Machine Learning Basics Overview of machine learning Supervised and unsupervised learning Common algorithms and use cases Introduction to Spark MLlib Overview of Spark MLlib MLlib's algorithms and utilities Data preparation and feature extraction Linear Regression and Classification Linear regression algorithm Logistic regression for classification Model evaluation and performance metrics Clustering Algorithms Overview of clustering algorithms K-means clustering Model evaluation and performance metrics Collaborative Filtering and Recommendation Systems Overview of recommendation systems Collaborative filtering techniques Implementing recommendations with Spark MLlib Introduction to Graph Processing Overview of graph processing Use cases and applications of graph processing Graph representations and operations Introduction to Spark GraphX Overview of GraphX Creating and transforming graphs Graph algorithms in GraphX Big Data Innovation! Using GPT and Generative AI Technologies with Spark and Scala Overview of generative AI technologies Integrating GPT with Spark and Scala Practical applications and use cases Bonus Topics / Time Permitting Introduction to Spark NLP Overview of Spark NLP Preprocessing text data Text classification and sentiment analysis Putting It All Together Work on a capstone project that integrates multiple aspects of the course, including data processing, machine learning, graph processing, and generative AI technologies.