26127 TEC courses in Cardiff delivered Online

In this webinar, we will explore the power of customer reviews and how they can significantly impact your reputation and attract more customers to your business. Join us as we delve into the strategies and best practices for leveraging reviews to enhance your online presence and ultimately drive growth. Whether you're a small business owner, a marketer, or a customer service professional, this webinar will provide you with valuable insights and actionable tips to optimise your review management approach.

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

Duration 70 Days 420 CPD hours Cisco Learning Library: Networking offers a subscription to all Cisco core online networking training, including product training, technology training, and certifications such as Cisco Routing and Switching, Wireless, Design, and Network Programmability.This comprehensive technical training library includes full-length, interactive certification courses, additional product and technology training with labs, and thousands of reference materials. Networking Library Certification Courses CCNA Implementing and Administering Cisco Solutions (CCNA) v1.0 CCNP Enterprise Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.0 Implementing Cisco Enterprise Advanced Routing and Services (ENARSI) v1.0 Implementing Cisco SD-WAN Solutions (SDWAN300) v1.0 Designing Cisco Enterprise Networks (ENSLD) v1.0 Designing Cisco Enterprise Wireless Networks (ENWLSD) v1.0 Implementing Cisco Enterprise Wireless Networks (ENWLSI) v1.1 Implementing Automation for Cisco Enterprise Solutions (ENAUI) v1.0 CCIE Enterprise Infrastructure Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.0 CCIE Enterprise Wireless Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.0 Product and Technology Training Implementing and Administering Cisco Solutions (CCNA) v1.0 Developing Applications and Automating Workflows Using Cisco Core Platforms (DEVASC) v1.0 Developing Applications Using Cisco Core Platforms and APIs (DEVCOR) v1.0 Developing Solutions Using Cisco IoT and Edge Platforms (DEVIOT) v1.0 Implementing DevOps Solutions and Practices Using Cisco Platforms (DEVOPS) v1.0 Developing Applications for Cisco Webex and Webex Devices (DEVWBX) v1.0 Implementing Automation for Cisco Enterprise Solutions (ENAUI) v1.0 Implementing Automation for Cisco Collaboration Solutions (CLAUI) v1.0 Implementing Automation for Cisco Data Center Solutions (DCAUI) v1.0 Implementing Automation for Cisco Security Solutions (SAUI) v1.0 Implementing Automation for Cisco Service Provider Solutions (SPAUI) v1.0 Introducing Automation for Cisco Solutions (CSAU) v1.0 Cisco Certified Technician Supporting Cisco Routing and Switching Network Devices (RSTECH) v3.0 Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.0 Implementing Cisco Enterprise Advanced Routing and Services (ENARSI) v1.0 Implementing Cisco SD-WAN Solutions (SDWAN300) v1.0 Designing Cisco Enterprise Networks (ENSLD) v1.0 Implementing Cisco Enterprise Wireless Networks (ENWLSI) v1.1 Cisco NCS 2000 Deploying 96-Channel Flex Spectrum (OPT201) v3.0 Cisco Digital Network Architecture Implementation Essentials (DNAIE) v2.0 Understanding Cisco Industrial IoT Networking Foundation (INFND) v1.0 Programming Use Cases for Cisco Digital Network Architecture v1.0 (DNAPUC) v1.0 Engineering Cisco Meraki Solutions Part 1 (ECMS1) v1.0 Deploying Cisco SD-Access (ENSDA) v1.1 Cisco SD-WAN Operation and Deployment (ENSDW) v1.0 Introduction to Cisco IOS XR (IOSXR100) v2.0 Cisco IOS XR System Administration (IOSXR200) v1.1 Cisco IOS XR Basic Troubleshooting (IOSXR201) v1.1 Cisco ASR 9000 Series IOS XR 64-Bit Software Migration and Operational Enhancements (IOSXR211) v1.0 Cisco IOS XR Layer 3 VPN Implementation and Verification (IOSXR301) v1.1 Cisco IOS XRMulticast Routing Implementation and Verification (IOSXR302) v1.1 Cisco IOS XR Broadband Network Gateway Implementation and Verification (IOSXR304) v1.0 NSO Essentials for Programmers and Network Architects (NSO201) v3.0 Cisco NSO Administration and DevOps (NSO303) v3.0 Cisco Optical Technology Advanced (OPT300) v2.0 Implementing Segment Routing on Cisco IOS XR (SEGRTE201) v2.0 Operating and Implementing Cisco WAN Automation Engine (WAE200) v3.0 Implementing Cisco Virtual Wide Area Application Services (VWAAS) v1.0 Configuring and Operating Cisco EPN Manager (EPNM100) v3.0 Cisco Elastic Services Controller (ESC300) v2.0 Product and Technology Training Deploying Cloud Connect Solutions with Cisco Cloud Services Router 1000V (CLDCSR) v1.0 Implementing Cisco Multicast (MCAST) v2.0 Cisco Prime Central Intermediate ? Administration and Operations (CPCI-AO) v1.0 Cisco Prime Network Intermediate ? Administration and Operation (CPNI-AO) v1.1 Cisco Prime Provisioning (CPP) v6.5 Cisco Prime Performance Manager (CPPERF) v1.0 Implementing Cisco Catalyst 9000 Switches (ENC9K) v1.0 Cisco Aggregation Services Router 9000 Series Essentials (ASR9KE) v6.0 Network Convergence System 5500 Series Router (NCS5500HW) v1.0 Cisco DNA Center Fast-Start Use Cases (A-SDA-FASTSTART) Getting Started with DNA Center Assurance (A-DNAC-ASSUR) v1.0 Overview of Cisco DNA Center Fast Start Use Cases for System Engineers (P-SDA-SYSEF) Planning and Deploying SD-Access Fundamentals (For Customers) (CUST-SDA-FUND) v1.0 Preparing the Identity Services Engine (ISE) for SD-Access (For Customers) (CUST-SDA-ISE) v1.0 SD-Access 1.2 Update Supplement (A-SDA-12UPDT) The SD-WAN Mastery Collection - Getting Started (For Customers) v1.0 (A-SDW-START) The SD-WAN Mastery Collection - Deploying the Data Plane (For Customers) v1.0 (A-SDW-DATPLN) The SD-WAN Mastery Collection - Developing the Overlay Topology (For Customers) v1.0 (A-SDW-OVRLAY) The SD-WAN Mastery Collection - Managing the Application Experience (For Customers) v1.0 (A-SDW-APPEXP) The SD-WAN Mastery Collection - Bringing Up the Control Plane Devices (For Customers) v1.0 (A-SDW-CTRPLN) Securing Branch Internet and Cloud Access with Cisco SD-WAN (A-SDW-BRSEC) Programming for Network Engineers (PRNE) v1.0 Cisco Optical Technology Intermediate (OPT200) v2.0 Advanced Implementing and Troubleshooting MPLS VPN Networks (AMPLS) BGP Bootcamp (BGP) Building Core Networks with OSPF, IS-IS, BGP and MPLS Bootcamp (BCN) Configuring BGP on Cisco Routers (BGP) v4.0 Implementing Cisco MPLS v3.0 Internetworking Technology Overview (ITO) Introduction to IP Multicast Bootcamp Introduction to IPsec VPN Bootcamp (IPsec VPN) Introduction to IPv6 Bootcamp (IPv6) Introduction to MPLS-VPN Bootcamp (MPLS-VPN) LAN Switching Bootcamp (LAN-SW) RP Bootcamp Troubleshooting for Network Support Engineers

Duration 2 Days 12 CPD hours This course is intended for Workspace ONE administrators, account managers, solutions architects, solutions engineers, sales engineers, technical support engineers, and consultants Overview By the end of the course, you should be able to meet the following objectives: Summarize the basic troubleshooting methodologies Outline common troubleshooting techniques in the Workspace ONE UEM console Outline common troubleshooting techniques when integrating enterprise solutions in the Workspace ONE UEM console Summarize common troubleshooting strategies for Workspace ONE UEM managed devices Outline common application management troubleshooting techniques in the Workspace ONE UEM console Summarize common troubleshooting techniques for email management in the Workspace ONE UEM console Explain common troubleshooting approaches for the VMware Unified Access Gateway™ platform and individual edge services Outline useful troubleshooting tools, such as the Self-Service Portal and VMware Workspace ONE Assist™ In this two-day course, you learn to investigate, analyze, and determine issues that might occur with all the different components of VMware Workspace ONE© UEM. Troubleshooting is the backbone of service maintenance and management. To effectively troubleshoot product issues, administrators must understand how product services communicate and function. This in turn helps optimize service and software health management. Course Introduction Introductions and course logistics Course objectives Fundamentals of Troubleshooting Workspace ONE UEM Outline software troubleshooting logic and support methods Summarize the main process flows for the Workspace ONE UEM components Explain the importance of Workspace ONE UEM process flows for troubleshooting Identify different Workspace ONE UEM log files Workspace ONE UEM Console Troubleshooting Outline the best practices for troubleshooting Workspace ONE UEM console issues Identify common group management and assignment-related issues Outline common issues for Workspace ONE UEM console roles and system settings Understand how analytic events can be used to identity platform errors Summarize the steps for collecting and analyzing Workspace ONE UEM console logs Integration Troubleshooting Outline the common enterprise integrations in Workspace ONE UEM Outline common troubleshooting techniques for the VMware AirWatch© Cloud Connector? Troubleshoot issues related to Directory Services integration Identify directory user and groups synchronization issues Troubleshoot issues related to certificate authority integration Explain VMware Workspace ONE© Access? integration and VMware Workspace ONE© Intelligent Hub troubleshooting techniques Endpoint Troubleshooting Compare the endpoint connection topologies in Workspace ONE UEM Outline useful tools and resources for endpoint troubleshooting Summarize the best practices for device enrollment troubleshooting Explain device connectivity troubleshooting techniques Understand how to identify and resolve profile-related issues Identify common compliance policy issues and potential root causes Applications Troubleshooting Explain the different scoping questions for troubleshooting applications Review application management configurations Summarize the general tools and resources for application troubleshooting Describe the general logic of troubleshooting public applications Understand internal application issues and potential causes Explain purchased application troubleshooting techniques Unified Access Gateway And Edge Services Troubleshooting Review Unified Access Gateway architecture and edge service workflows Understand Unified Access Gateway general configurations Explain how to utilize Unified Access Gateway related troubleshooting tools and resources Identify and resolve common issues for Content Gateway on Unified Access Gateway Summarize troubleshooting techniques for VMware Workspace ONE© Tunnel? on Unified Access Gateway Email Troubleshooting Review different email architecture and workflows Summarize common errors associated with email profiles Identify tools and resources for email troubleshooting Discuss troubleshooting techniques for VMware AirWatch© Secure Email Gateway? on Unified Access Gateway Outline PowerShell integration issues and techniques to address them Additional Troubleshooting Tools Describe how the Self-Service Portal helps administrators and empowers end-users to resolve issues Understand how Workspace ONE Assist can help endpoint troubleshooting

Duration 5 Days 30 CPD hours This course is intended for Workspace ONE UEM operators and administrators, account managers, solutions architects, solutions engineers, sales engineers, and consultants Overview By the end of the course, you should be able to meet the following objectives: Explain and apply the fundamental techniques for launching and maintaining an intelligence-driven, multiplatform endpoint management solution with Workspace ONE UEM Outline the components of Workspace ONE UEM Explain the general features and functionality enabled with Workspace ONE UEM Summarize basic Workspace ONE administrative functions Explain and deploy common Workspace ONE integrations Securely deploy configurations to Workspace ONE UEM managed devices Onboard device endpoints into Workspace ONE UEM Summarize alternative management methodologies for rugged devices Discuss strategies for maintaining environment and device fleet health Configure and deploy applications to Workspace ONE UEM managed devices Analyze a Workspace ONE UEM deployment Enable email access on devices Integrate Workspace ONE UEM with content repositories and corporate file shares Summarize basic troubleshooting methodologies Outline common troubleshooting techniques in the Workspace ONE UEM console Outline common troubleshooting techniques when integrating enterprise solutions in the Workspace ONE UEM console Summarize common troubleshooting strategies for Workspace ONE UEM managed devices Outline common application management troubleshooting techniques in the Workspace ONE UEM console Summarize common troubleshooting techniques for email management in the Workspace ONE UEM console Explain common troubleshooting approaches for the VMware Unified Access Gateway™ platform and individual edge services Outline useful troubleshooting tools, such as the Self-Service Portal and VMware Workspace ONE Assist™ In this five-day course, you learn how to apply the fundamental techniques for launching and maintaining an intelligence-driven, multiplatform endpoint management solution with VMware Workspace ONE© UEM. Through a combination of hands-on labs, simulations, and interactive lectures, you will configure and manage the endpoint life cycle. You will also learn to investigate, analyze, and determine issues that might occur with all the different components of Workspace ONE UEM.By understanding how to effectively troubleshoot product issues, administrators can understand how product services communicate and function, in turn optimizing service and software health management. At the end of five days, you will have the foundational knowledge for effectively managing and conducting basic troubleshooting for Workspace ONE UEM. Course Introduction Introductions and course logistics Course objectives Online resources and references Platform Architecture Summarize the features and functionality of Workspace ONE UEM Outline the benefits of leveraging Workspace ONE UEM Recognize the core and productivity components that make up the Workspace ONE UEM platform Summarize high availability and disaster recovery for the Workspace ONE solution Administration Navigate and customize the Workspace ONE UEM console Summarize the hierarchical management structure Explain the features and functions of Workspace ONE Hub Services Outline account options and permissions Enterprise Integrations Outline the process and requirements to integrate with directory services Explain certificate authentication and practical implementation with Workspace ONE Explain the benefits of integrating an email SMTP service into the Workspace ONE UEM console Describe VMware Dynamic Environment Manager? and its architecture Onboarding Outline the prerequisite configurations in the Workspace ONE UEM environment for onboarding devices for management Outline the steps for setting up autodiscovery in the Workspace ONE UEM console Enroll an endpoint through the VMware Workspace ONE© Intelligent Hub app Summarize platform onboarding options Managing Endpoints Explain the differences between device and user profiles Describe policy management options for Windows and macOS Describe the functions and benefits of using compliance policies Explain the use case for Freestyle Orchestrator Describe the capabilities that sensors and scripts enable Alternative Management Methods Describe the function and benefits of device staging Configure product provisioning in the Workspace ONE UEM console Understand the benefits of deploying a VMware Workspace ONE© Launcher? configuration to Android devices List the system and device requirements for Linux device management in Workspace ONE UEM Applications Describe the features, benefits, and capabilities of application management in Workspace ONE UEM Understand and configure deployment settings for public, internal, and paid applications in the Workspace ONE UEM console Describe the benefits of using Apple Business Manager content integration Describe the benefits of using server-to-client software distribution List the functions and benefits of VMware Workspace ONE© SDK Device Email List the email clients supported by Workspace ONE UEM Configure an Exchange Active Sync profile in the Workspace ONE UEM console Configure VMware Workspace ONE© Boxer settings Summarize the available email infrastructure integration models and describe their workflows Configure email compliance policies and notifications services Content Sharing Describe the benefits of using Content Gateway and the Content Gateway workflows Describe the benefits of integrating content repositories with Workspace ONE UEM Configure a repository in the Workspace ONE UEM console Maintenance Manage endpoints from the Device List View and the Device Details View pages Analyze endpoint deployment and compliance data from Monitor Overview page Fundamentals of Troubleshooting Workspace ONE UEM Outline software troubleshooting logic and support methods Summarize the main process flows for the Workspace ONE UEM components Explain the importance of Workspace ONE UEM process flows for troubleshooting Identify different Workspace ONE UEM log files Workspace ONE UEM Console Troubleshooting Outline the best practices for troubleshooting Workspace ONE UEM console issues Identify common group management and assignment-related issues Outline common issues for Workspace ONE UEM console roles and system settings Understand how analytic events can be used to identity platform errors Summarize the steps for collecting and analyzing Workspace ONE UEM console logs Integration Troubleshooting Outline the common enterprise integrations in Workspace ONE UEM Outline common troubleshooting techniques for the VMware AirWatch© Cloud Connector? Troubleshoot issues related to Directory Services integration Identify directory user and groups synchronization issues Troubleshoot issues related to certificate authority integration Explain VMware Workspace ONE© Access? integration and Workspace ONE Intelligent Hub troubleshooting techniques Endpoint Troubleshooting Compare the endpoint connection topologies in Workspace ONE UEM Outline useful tools and resources for endpoint troubleshooting Summarize the best practices for device enrollment troubleshooting Explain device connectivity troubleshooting techniques Demonstrate how to identify and resolve profile-related issues Identify common compliance policy issues and potential root causes Application Troubleshooting Explain the different scoping questions for troubleshooting applications Review application management configurations Summarize the general tools and resources for application troubleshooting Describe the general logic of troubleshooting public applications Understand internal application issues and potential causes Explain purchased application troubleshooting techniques Unified Access Gateway and Edge Services Troubleshooting Review Unified Access Gateway architecture and edge service workflows Understand Unified Access Gateway general configurations Explain how to utilize Unified Access Gateway related troubleshooting tools and resources Identify and resolve common issues for Content Gateway on Unified Access Gateway Summarize troubleshooting techniques for VMware Workspace ONE© Tunnel? on Unified Access Gateway Email Troubleshooting Review different email architecture and workflows Summarize common errors associated with email profiles Identify tools and resources for email troubleshooting Discuss troubleshooting techniques for VMware AirWatch© Secure Email Gateway? on Unified Access Gateway Outline PowerShell integration issues and techniques to address them Additional Troubleshooting Tools Describe how the Self-Service Portal helps administrators and empowers end users to resolve issues Explain how Workspace ONE Assist can help with troubleshooting endpoints

Duration 3 Days 18 CPD hours This course is intended for The target audience for this course includes: Software testers (both technical and user acceptance testers), Test analysts, Test engineers, Test consultants, Software developers, Managers including test managers, project managers, quality managers. Overview By the end of this course, an attendee should be able to: perform effective testing of software, be aware of techniques and standards, have an awareness of what testing tools can achieve, where to find more information about testing, and establish the basic steps of the testing process. This is an ISTQB certification in software testing for the US. In this course you will study all of the basic aspects of software testing and QA, including a comprehensive overview of tasks, methods, and techniques for effectively testing software. This course prepares you for the ISTQB Foundation Level exam. Passing the exam will grant you an ISTQB CTFL certification. Fundamentals of Testing What is Testing? Typical Objectives of Testing Testing and Debugging Why is Testing Necessary? Testing?s Contributions to Success Quality Assurance and Testing Errors, Defects, and Failures Defects, Root Causes and Effects Seven Testing Principles Test Process Test Process in Context Test Activities and Tasks Test Work Products Traceability between the Test Basis and Test Work Products The Psychology of Testing Human Psychology and Testing Tester?s and Developer?s Mindsets Testing Throughout the Software Development Lifecycle Software Development Lifecycle Models Software Development and Software Testing Software Development Lifecycle Models in Context Test Levels Component Testing Integration Testing System Testing Acceptance Testing Test Types Functional Testing Non-functional Testing White-box Testing Change-related Testing Test Types and Test Levels Maintenance Testing Triggers for Maintenance Impact Analysis for Maintenance Static Testing Static Testing Basics Work Products that Can Be Examined by Static Testing Benefits of Static Testing Differences between Static and Dynamic Testing Review Process Work Product Review Process Roles and responsibilities in a formal review Review Types Applying Review Techniques Success Factors for Reviews Test Techniques Categories of Test Techniques Choosing Test Techniques Categories of Test Techniques and Their Characteristics Black-box Test Techniques Equivalence Partitioning Boundary Value Analysis Decision Table Testing State Transition Testing Use Case Testing White-box Test Techniques Statement Testing and Coverage Decision Testing and Coverage The Value of Statement and Decision Testing Experience-based Test Techniques Error Guessing Exploratory Testing Checklist-based Testing Test Management Test Organization Independent Testing Tasks of a Test Manager and Tester Test Planning and Estimation Purpose and Content of a Test Plan Test Strategy and Test Approach Entry Criteria and Exit Criteria (Definition of Ready and Definition of Done) Test Execution Schedule Factors Influencing the Test Effort Test Estimation Techniques Test Monitoring and Control Metrics Used in Testing Purposes, Contents, and Audiences for Test Reports Configuration Management Risks and Testing Definition of Risk Product and Project Risks Risk-based Testing and Product Quality Defect Management Tool Support for Testing Test Tool Considerations Test Tool Classification Benefits and Risks of Test Automation Special Considerations for Test Execution and Test Management Tools Effective Use of Tools Main Principles for Tool Selection Pilot Projects for Introducing a Tool into an Organization Success Factors for Tools Additional course details: Nexus Humans ISTQB Software Testing Certification Training - Foundation Level (CTFL) 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 ISTQB Software Testing Certification Training - Foundation Level (CTFL) 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 Operational Technology (OT) Engineers IT engineers Generalists, including managers, project leads, and solutions and business architects Overview Define what IIoT is and identify IIoT architectures. Identify IIoT market verticals, and their motivations and requirements. Explore Cisco IIoT networking devices, how they are different from other devices, and use common administrative tools for managing them. Explore industrial communications protocols for control and automation, and how they have been adapted to run on top of a TCP/IP network infrastructure. Describe wireless protocols used in IIoT environments, including architectures and devices used. Understand the TCP/IP protocol stack and how it is used with other protocols in IIoT environments. Discuss network protocols for clock synchronization between network devices, and describe available tools for IIoT network administration. Discuss wireless technologies used in a core LAN, and their relevance to IIoT implementations. Explore field WAN technologies and how they are used in IIoT environments. Explore legacy protocols and explain the methods available to transport non-routable protocols over modern networks. Explain fundamental concepts of Quality of Service (QoS) related to IIoT network environments. Discuss Multiprotocol Label Switching (MPLS) operation, components, terminology, and features, and explore its use in IIoT environments. Explore Layer 2 and Layer 3 VPN technologies and describe the way they can be used on IIoT deployments. Describe Dense Wave Division Multiplexing (DWDM) technology and its use in IIoT environments. Explore Layer 1 and Layer 2 high availability technologies and redundancy mechanisms. Describe Layer 3 high availability and the need for Layer 3 redundancy in IIoT deployments The Understanding Cisco Industrial IoT Networking Foundation (INFND) v1.0 course gives you an overview of the protocols, applications, and network infrastructure you need to support and manage Industrial Internet of Things (IIoT) solutions. You will learn about IIoT industry verticals and how different protocols are used within them. The course also covers configuring and verifying the protocols on Cisco© IIoT networking devices. Course Introduction.Defining Industrial Internet of ThingsExamining Common IIoT Verticals.Examining Cisco IIoT Networking Devices.Examining and Configuring Industrial Communication Protocols.Describing Wireless IIoT Protocols.Explaining and Configuring TCP/IP Protocols, Addressing, and Segmentation.Examining Network Services and Administration.Examining and Configuring Wireless Core LAN Technologies.Describing Field WAN Technologies.Examining and Configuring Transportation of Legacy Protocols.Describing, Configuring, and Verifying Quality of Service (QoS) for IIoT Protocols.Examining and Verifying MPLS and IIoT.Configuring and Explaining VPN Technology and IIoT.Describing DWDM.Configuring and Defining Layer 1 and Layer 2 High Availability Technologies.Defining and Configuring Layer 3 High Availability TechnologiesLab outline Connect to the Cisco IIoT Devices. Use Industrial Protocols with Cisco Industrial Ethernet Switches. Configure an 802.11 Client. Configure an IPv6 Address. Configure Layer 2 Network Address Translation (NAT) and IP Addressing in an Example IoT Deployment.

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 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 1 Days 6 CPD hours This course is intended for To gain the most from attending this course you should possess the following incoming skills: Basic knowledge of programming concepts and syntax in Python. Familiarity with common data formats such as CSV, JSON, and XML. Experience using command-line interfaces and basic text editing tools. Understanding of basic machine learning concepts and algorithms. Overview Working in an interactive learning environment, led by our engaging expert, you will: Gain a solid understanding of prompt engineering concepts and their applications in software development and AI-driven solutions. Master the techniques for preprocessing and cleaning text data to ensure high-quality inputs for AI models like GPT-4. Develop expertise in GPT-4 tokenization, input formatting, and controlling model behavior for various tasks and requirements. Acquire the ability to design, optimize, and test prompts effectively, catering to diverse business applications and use cases. Learn advanced prompt engineering techniques, such as conditional text generation and multi-turn conversations, to create more sophisticated AI solutions. Practice creating prompts to generate, run, and test code in a chosen programming language using GPT-4 and OpenAI Codex. Understand the ethical implications and best practices in responsible AI deployment, ensuring fair and unbiased AI applications in software development. Prompt Engineering offers coders and software developers a competitive edge by empowering them to develop more effective and efficient AI-driven solutions in their projects. By harnessing the capabilities of cutting-edge AI models like GPT-4, coders can automate repetitive tasks, enhance natural language understanding, and even generate code suggestions, boosting productivity and creativity. In addition, mastering prompt engineering can contribute to improved job security, as professionals with these in-demand skills are highly sought after in the rapidly evolving tech landscape. Quick Start to Prompt Engineering for Coders and Software Developers is a one day course designed to get you quickly up and running with the prompting skills required to out AI to work for you in your development efforts. Guided by our AI expert, you?ll explore key topics such as text preprocessing, data cleansing, GPT-4 tokenization, input formatting, prompt design, and optimization, as well as ethical considerations in prompt engineering. In the hands-on labs you?ll explore tasks such as formatting inputs for GPT-4, designing and optimizing prompts for business applications, and implementing multi-turn conversations with AI. You?ll work with innovative tools like the OpenAI API, OpenAI Codex, and OpenAI Playground, enhancing your learning experience while preparing you for integrating prompt engineering into your professional toolkit. By the end of this immersive course, you?ll have the skills necessary to effectively use prompt engineering in your software development projects. You'll be able to design, optimize, and test prompts for various business tasks, integrate GPT-4 with other software platforms, and address ethical concerns in AI deployment. Introduction to Prompt Engineering Overview of prompt engineering and its importance in AI applications Major applications of prompt engineering in business Common challenges faced in prompt engineering Overview of GPT-4 and its role in prompt engineering Key terminology and concepts in prompt engineering Getting Things Ready: Text Preprocessing and Data Cleansing Importance of data preprocessing in prompt engineering Techniques for text cleaning and normalization Tokenization and n-grams Stop word removal and stemming Regular expressions and pattern matching GPT-4 Tokenization and Input Formatting GPT-4 tokenization and its role in prompt engineering Understanding and formatting GPT-4 inputs Context windows and token limits Controlling response length and quality Techniques for handling out-of-vocabulary tokens Prompt Design and Optimization Master the skills to design, optimize, and test prompts for various business tasks. Designing effective prompts for different tasks Techniques for prompt optimization GPT-4 system and user parameters for controlling behavior Importance of prompt testing and iteration Best practices for prompt engineering in business applications Advanced Techniques and Tools in Prompt Engineering Learn advanced techniques and tools for prompt engineering and their integration in business applications. Conditional text generation with GPT-4 Techniques for handling multi-turn conversations Overview of tools for prompt engineering: OpenAI API, OpenAI Codex, and OpenAI Playground Integration of GPT-4 with other software platforms and tools Monitoring and maintaining prompt performance Code Generation and Testing with Prompt Engineering Develop the skills to generate, integrate, and test AI-generated code effectively, enhancing productivity and creativity in software development projects. Introduction to code generation with AI models like GPT-4 Designing prompts for code generation across programming languages Techniques for specifying requirements and constraints in prompts Generating and interpreting code snippets using AI-driven solutions Integrating generated code into existing projects and codebases Best practices for testing and validating AI-generated code Ethics and Responsible AI Understand the ethical implications of prompt engineering and the importance of responsible AI deployment in business. Ethical considerations in prompt engineering Bias in AI systems and its impact on prompt engineering Techniques to minimize bias and ensure fairness Best practices for responsible AI deployment in business applications Monitoring and addressing ethical concerns in prompt engineering