4824 Courses

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Duration 5 Days 30 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 features Learn how to perform network monitoring functions and troubleshooting AR-AMF teaches knowledge, skills & practical exp. to set up & config a basic AR WLAN utilizing OS 8.X architecture & features.using lecture & labs,AR-AMF provides tech. & hands-on exp. of config. a single Mobility Master with 1 controller & AP WLAN 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 the new OS 8.X Airmatch to calibrate the network How Client Match and Client Insight match steers clients to better Aps Dynamic RF Management Explain how ARM calibrates the network selecting channels and power settings Explores the new OS 8.X Airmatch to calibrate the network How Client Match and Client Insight 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

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 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.