4699 Courses delivered Online

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brandnew version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative dversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 4 Days 24 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brand-new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm ? YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 5 Days 30 CPD hours This course is intended for This is a basic-level programming course designed for attendees with prior development experience in another language, such as COBOL, 4GL, Mainframe or other non-object oriented languages. This course is not geared for non-developers. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in core OO coding and Java development skills, coupling the most current, effective techniques with the soundest industry practices. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working within in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand what OO programming is and what the advantages of OO are in today's world Work with objects, classes, and OO implementations Understand the basic concepts of OO such as encapsulation, inheritance, polymorphism, and abstraction Understand not only the fundamentals of the Java language, but also its importance, uses, strengths and weaknesses Understand the basics of the Java language and how it relates to OO programming and the Object Model Work with the Modular system (Project Jigsaw) Understand and use classes, inheritance and polymorphism Understand and use collections, generics, autoboxing, and enumerations Process large amount of data using Lambda expressions and the Stream API Abstract, static and private methods in interfaces Take advantage of the Java tooling that is available with the programming environment being used in the class Java 11 features covered: Using the Local Variable Type in Lambda expressions; Updates made to the String API This course provides hands-on Java 11 training for developers who have little or no prior working knowledge of object-oriented programming languages such as C, COBOL, and 4GL. You will learn the best practices for writing great object-oriented programs in Java 11, using sound development techniques, new improved features for better performance, and new capabilities for addressing rapid application development. Special emphasis is placed on object oriented concepts and best practices. A First Look The Java Platform Using the JDK The Eclipse Paradigm Getting Started with Java Writing a Simple Class Adding Methods to the Class OO Concepts Object-Oriented Programming Inheritance, Abstraction, and Polymorphism Essential Java Programming Language Statements Using Strings Specializing in a Subclass Fields and Variables Using Arrays Local-Variable Type Inference Java Packages and Visibility Object Oriented Development Inheritance and Polymorphism Interfaces and Abstract Classes Introduction to Exception Handling Exceptions Java Developer's Toolboxÿ Utility Classes Java Date/Time Advanced Java Programming Introduction to Generics Lambda Expressions and Functional Interface Working with Collections Collections Using Collections Stream APIÿ Streams Collectors The Java Module System Introduction to the Module System Time Permitting Formatting Strings Introduction to Annotations Java 12 and beyond Additional course details: Nexus Humans Basic Java 11 and OO Programming for Developers New to OO (TT2120-J11) 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 Basic Java 11 and OO Programming for Developers New to OO (TT2120-J11) 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 Security administrators who are responsible for using SaltStack SecOps to manage the security operations in their enterprise Overview By the end of the course, you should be able to meet the following objectives: Describe the architecture of SaltStack Config and SaltStack SecOps Integrate SaltStack Config with directory services. Configure roles and permissions for users and groups to manage and use SaltStack SecOps Use targeting to ensure that the jobs run on the correct minion systems Use remote execution modules to install the packages, transfer files, manage services, and manage users on minion systems Manage configuration control on the minion systems with states, pillars, requisites, and declarations Use Jinja and YAML code to manage the minion systems with the state files Enforce the desired state across minion systems automatically Use SaltStack SecOps to update the compliance and vulnerability content libraries Use SaltStack SecOps to enforce compliance and remediation on the infrastructure with industry standards Use SaltStack SecOps to provide automated vulnerability scanning and remediation on your infrastructure This two-day, hands-on training course provides you with the advanced knowledge, skills, and tools to achieve competency in using VMware vRealize© Automation SaltStack© SecOps. SaltStack SecOps allows you to scan your system for compliance against security benchmarks, detect system vulnerabilities, and remediate your results. This course enables you to create the SaltStack SecOps custom compliance libraries and use SaltStack SecOps. In addition, this course provides you with the fundamentals of how to use VMware vRealize© Automation SaltStack© Config to install software and manage system configurations. Course Introduction Introductions and course logistics Course objectives SaltStack Config Architecture Identify the SaltStack Config deployment types Identify the components of SaltStack Config Describe the role of each SaltStack Config component SaltStack Config Security Describe local user authentication Describe LDAP and Active Directory authentication Describe the roles and permissions in vRealize Automation for SaltStack Config Describe the roles and permissions in SaltStack Config Describe the SecOps permissions in SaltStack Config Describe the advanced permissions available in SaltStack Config Targeting Minions Describe targeting and its importance Target minions by minion ID Target minions by glob Target minions by regular expressions Target minions by lists Target minions by compound matching Target minions by complex logical matching Remote Execution and Job Management Describe remote execution and its importance Describe functions and arguments Create and manage jobs Use the Activities dashboard Configuration Control Through States, Pillars, Requisites, and Declarations Define the SaltStack states Describe file management in SaltStack Config Create the SaltStack state files Identify the components of a SaltStack state Describe pillar data and the uses of pillar data Configure pillar data on the SaltStack Config master server Use pillar data in variables in the state files Describe the difference between IDs and names in the state files Use the correct execution order Use requisites in the state files Using Jinja and YAML Describe the SaltStack Config renderer system Use YAML in the state files Use Jinja in the state files Use Jinja conditionals, lists, and loops Using SaltStack SecOps Comply Describe the SaltStack SecOps Comply architecture Describe CIS and DISA STIG benchmarks Describe the SaltStack SecOps Comply security library Describe the remediation differences between SaltStack SecOps and VMware Carbon Black© Create and manage the policies Create and manage the custom checks Run assessments on the minion systems Use SaltStack SecOps to remediate the noncompliant systems Manage the SaltStack SecOps Comply configuration options Manage the benchmark content ingestion Using SaltStack SecOps Protect Describe Common Vulnerabilities and Exposures (CVEs) Use the Protect dashboard Create and manage the policies Update the vulnerability library Run the vulnerability scans Remediate the vulnerabilities Manage the vulnerability exemptions

Duration 2 Days 12 CPD hours This course is intended for This introductory-level course is ideal for project managers, team leaders, and collaboration-focused roles who are already familiar with Jira and are looking to integrate Confluence into their project workflows. Overview Throughout the course you will learn to: Master the fundamentals of Confluence, including understanding its history, navigation, and the distinction between pages and blogs. Gain proficiency in creating, editing, copying, moving, and deleting pages, along with managing file directories and executing advanced editing features. Develop the ability to use and create blueprints and templates, aiding in the standardization and productivity enhancement of your team's work. Understand the collaborative features of Confluence such as sharing links, commenting, mentioning, liking, and watching content to promote a culture of teamwork and collaboration in your organization. Learn how to effectively integrate Confluence with Jira, linking issues and filters, and using auto-links for smoother project management. OPTIONAL: Acquire skills in Confluence administration, including managing notifications and watchers, linking to other applications, customizing the look and feel of your workspace, and creating various types of spaces (public, private, team, etc.) Boost your project management and team collaboration skills with our hands-on, interactive course, Getting Started with Confluence (with Jira). Confluence, as a powerful project collaboration tool, seamlessly integrates with Jira, allowing you to create, share, and collaborate on projects in a more efficient and visually appealing way. This course will equip you with the skills to manage projects, improve workflow efficiency, and promote transparency in your organization. You will gain practical knowledge about Confluence's core features such as creating and editing pages, managing file directories, using tasks, macros, and gadgets, and differentiating between pages and blogs.Working in a hands-on learning environment guided by our expert instructor, you?ll gain experience with Confluence's unique features like using and creating blueprints and templates, enhancing standardization and productivity in your team. The program includes a deep dive into collaborative features of Confluence and its integration with Jira, which will enhance your ability to foster a collaborative environment. Administrative aspects like managing notifications, watchers, linking to other applications, and creating various types of spaces will also be covered.You?ll leave the course with the skills to apply Confluence within your existing Jira environment effectively, ready to use its collaborative tools and features to streamline workflows and boost project productivity. Introduction History Navigation Space Directory Shortcuts Pages VS Blogs Pages Creating Pages Editing Pages File Directory Advanced Editing (Markup, Undefined links, etc.) Copying and Moving Pages Deleting Pages Tasks Macros/Gadgets Macro overview and use Using JIRA Gadgets Editing Existing Macros Blueprints/Templates Working with Blueprints Creating/Using Templates Collaboration Sharing Links Commenting Mentioning 'Liking' Content 'Watching' Content JIRA Integration Linking your JIRA and Confluence Instances Linking Issues and Filters Auto Links Administration Page vs Space vs System Admin Notifications Watchers Linking to Other Applications Workbox Notifications Look and Feel Creating Spaces Public Space Private Space Team Space Technical Documentation Meeting Minutes Blog Additional course details: Nexus Humans Introduction to Confluence (TTDV7545) 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 Confluence (TTDV7545) 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 Channel Partner / Reseller Customer Employee Overview At course completion students will be able to: - Explain the need for QoS, describe the fundamentals of QoS policy, and identify and describe the different models that are used for ensuring QoS in a network - Explain the use of MQC and AutoQoS to implement QoS on the network and describe some of the mechanisms used to monitor QoS implementations - Given a converged network and a policy defining QoS requirements, classify and mark network traffic to implement the policy - Use Cisco QoS queuing mechanisms to manage network congestion - Use Cisco QoS congestion avoidance mechanisms to reduce the effects of congestion on the network - Use Cisco QoS traffic policing and traffic shaping mechanisms to effectively limit the rate of network traffic - Given a low speed WAN link, use Cisco link efficiency mechanisms to improve the badwidth efficiency of the link - Describe the recommended best practices and methods used for end-to-end QoS deployment in the enterprise This course provides students with knowledge of IP QoS requirements, conceptual models such as best effort, IntServ, and DiffServ, and the implementation of QoS on Cisco platforms. Introduction to QoS Review Converged Networks Understand QoS Describe Best-Effort and Integrated Services Models Describe the Differentiated Services Model Module Summary Module Self-Check Implement and Monitor QoS MQC Introduction Monitor QoS Define Campus AutoQoS Define WAN AutoQoS Module Summary Module Self-Check Lab 2-1: IP SLA Setup and QoS Baseline Measurement Lab 2-2: Configuring QoS with Cisco AutoQoS Classification and Marking Classification and Marking Overview Case Study 3-1: Classification and Marking MQC for Classification and Marking NBAR for Classification Use of QoS Preclassify Campus Classification and Marking Module Summary Module Self-Check Lab 3-1: Classification and Marking Using MQC Lab 3-2: Using NBAR for Classification Lab 3-3: Configuring QoS Preclassify Lab 3-4: Campus Classification and Marking Using MQC Congestion Management Queuing Introduction Configure WFQ Configure CBWFQ and LLQ Configure Campus Congestion Management Module Summary Module Self-Check Lab 4-1: Configuring Fair Queuing Lab 4-2: Configuring LLQ-CBWFQ Lab 4-3: Configuring Campus-Based Queuing Mechanisms Congestion Avoidance Congestion Avoidance Introduction Configure Class-Based WRED Case Study 5-1: WRED Traffic Profiles Configure ECN Describe Campus-Based Congestion Avoidance Module Summary Module Self-Check Lab 5-1: Configuring DSCP-Based WRED Lab 5-2: Configuring WTD Thresholds Traffic Policing and Shaping Traffic Policing and Shaping Overview Configure Class-Based Policing Campus Policing Configure Class-Based Shaping Configure Class-Based Shaping on Frame Relay Interfaces Configure Frame Relay Voice-Adaptive Traffic Shaping and Fragmentation Module Summary Module Self-Check Lab 6-1: Configuring Class-Based Policing Lab 6-2: Configuring Class-Based Shaping Link Efficiency Mechanisms Link Efficiency Mechanisms Overview Configure Class-Based Header Compression Configure LFI Module Summary Module Self-Check Lab 7-1: Configuring Class-Based Header Compression Lab 7-2: Configuring LFI Deploying End-to-End QoS Apply Best Practices for QoS Policy Design End-to-End QoS Deployments Module Summary Module Self-Check Lab 8-1: Mapping Enterprise QoS Policy to the Service Provider Policy Additional course details: Nexus Humans Cisco Implementing Cisco Quality of Service v2.5 (QOS) 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 Implementing Cisco Quality of Service v2.5 (QOS) 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 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 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 3 Days 18 CPD hours This course is intended for Typical candidates for this course are IT Professionals who deploy small-to-medium scale enterprise network solutions based on Aruba products and technologies. Overview After you successfully complete this course, expect to be able to: Explain how Aruba's wireless networking solutions meet customers' requirements Explain fundamental WLAN technologies, RF concepts, and 802.11 Standards Learn to configure the Mobility Master and Mobility Controller to control access to the Employee and Guest WLAN Control secure access to the WLAN using Aruba Firewall Policies and Roles Recognize and explain Radio Frequency Bands and channels, and the standards used to regulate them Describe the concept of radio frequency coverage and interference and successful implementation and diagnosis of WLAN systems Identify and differentiate antenna technology options to ensure optimal coverage in various deployment scenarios Describe RF power technology including, signal strength, how it is measured and why it is critical in designing wireless networks Learn to configure and optimize Aruba ARM and Client Match and Client Insight features Learn how to perform network monitoring functions and troubleshooting This course teaches the knowledge, skills and practical experience required to set up and configure a basic Aruba WLAN utilizing the OS 8.X architecture and features. Using lecture and labs, this course provides the technical understanding and hands-on experience of configuring a single Mobility Master with one controller and AP Aruba WLAN. Participants will learn how to use Aruba hardware and ArubaOS to install and build a complete, secure controller network with multiple SSIDs. This course provides the underlying material required to prepare candidates for the Aruba Certified Mobility Associate (ACMA) certification exam. WLAN Fundamentals Describes the fundamentals of 802.11, RF frequencies and channels Explain RF Patterns and coverage including SNR Roaming Standards and QOS requirements Mobile First Architecture An introduction to Aruba Products including controller types and modes OS 8.X Architecture and features License types and distribution Mobility Master Mobility Controller Configuration Understanding Groups and Subgroups Different methods to join MC with MM Understanding Hierarchical Configuration Secure WLAN configuration Identifying WLAN requirements such as SSID name, encryption, authentication Explain AP groups structure and profiles Configuration of WLAN using the Mobility Master GUI AP Provisioning Describes the communication between AP and Mobility controller Explain the AP booting sequence and requirements Explores the APs controller discovery mechanisms Explains how to secure AP to controller communication using CPSec Describes AP provisioning and operations WLAN Security Describes the 802.11 discovery, authentication and association Explores the various authentication methods, 802.1x with WPA/WPA2, Mac auth Describes the authentication server communication Explains symmetric vs asymmetric Keys, encryption methods WIPS is described along with rogue discovery and protection Firewall Roles and Policies An introduction into Firewall Roles and policies Explains Aruba?s Identity based Firewall Configuration of Policies and Rules including aliases Explains how to assign Roles to users Dynamic RF Management Explain how ARM calibrates the network selecting channels and power settings Explores OS 8.X Airmatch to calibrate the network How Client Match and ClientInsight match steers clients to better APs Guest Access Introduces Aruba?s solutions for Guest Access and the Captive portal process Configuration of secure guest access using the internal Captive portal The configuration of Captive portal using Clearpass and its benefits Creating a guest provisioning account Troubleshooting guest access Network Monitoring and Troubleshooting Using the MM dashboard to monitor and diagnose client, WLAN and AP issues Traffic analysis using APPrf with filtering capabilities A view of Airwaves capabilities for monitoring and diagnosing client, WLAN and AP issues Additional course details: Nexus Humans Aruba Mobility Fundamentals, Rev. 20.11 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 Aruba Mobility Fundamentals, Rev. 20.11 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 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.