39510 Courses delivered Online

Duration 5 Days 30 CPD hours This course is intended for This course is for IT Professionals with expertise in designing and implementing solutions running on Microsoft Azure. They should have broad knowledge of IT operations, including networking, virtualization, identity, security, business continuity, disaster recovery, data platform, budgeting, and governance. Azure Solution Architects use the Azure Portal and as they become more adept they use the Command Line Interface. Candidates must have expert-level skills in Azure administration and have experience with Azure development processes and DevOps processes. Overview Secure identities with Azure Active Directory and users and groups. Implement identity solutions spanning on-premises and cloud-based capabilities Apply monitoring solutions for collecting, combining, and analyzing data from different sources. Manage subscriptions, accounts, Azure policies, and Role-Based Access Control. Administer Azure using the Resource Manager, Azure portal, Cloud Shell, and CLI. Configure intersite connectivity solutions like VNet Peering, and virtual network gateways. Administer Azure App Service, Azure Container Instances, and Kubernetes. This course teaches Solutions Architects how to translate business requirements into secure, scalable, and reliable solutions. Lessons include virtualization, automation, networking, storage, identity, security, data platform, and application infrastructure. This course outlines how decisions in each theses area affects an overall solution. Implement Azure Active Directory Overview of Azure Active Directory Users and Groups Domains and Custom Domains Azure AD Identity Protection Implement Conditional Access Configure Fraud Alerts for MFA Implement Bypass Options Configure Guest Users in Azure AD Configure Trusted IPs Manage Multiple Directories Implement and Manage Hybrid Identities Install and Configure Azure AD Connect Configure Password Sync and Password Writeback Configure Azure AD Connect Health Implement Virtual Networking Virtual Network Peering Implement VNet Peering Implement VMs for Windows and Linux Select Virtual Machine Size Configure High Availability Implement Azure Dedicated Hosts Deploy and Configure Scale Sets Configure Azure Disk Encryption Implement Load Balancing and Network Security Implement Azure Load Balancer Implement an Application Gateway Understand Web Application Firewall Implement Azure Firewall Implement Azure Front Door Implementing Azure Traffic Manager Implement Storage Accounts Storage Accounts Blob Storage Storage Security Managing Storage Accessing Blobs and Queues using AAD Implement NoSQL Databases Configure Storage Account Tables Select Appropriate CosmosDB APIs Implement Azure SQL Databases Configure Azure SQL Database Settings Implement Azure SQL Database Managed Instances High-Availability and Azure SQL Database In this module, you will learn how to Create an Azure SQL Database (single database) Create an Azure SQL Database Managed Instance Recommend high-availability architectural models used in Azure SQL Database Automate Deployment and Configuration of Resources Azure Resource Manager Templates Save a Template for a VM Evaluate Location of New Resources Configure a Virtual Hard Disk Template Deploy from a template Create and Execute an Automation Runbook Implement and Manage Azure Governance Create Management Groups, Subscriptions, and Resource Groups Overview of Role-Based Access Control (RBAC) Role-Based Access Control (RBAC) Roles Azure AD Access Reviews Implement and Configure an Azure Policy Azure Blueprints Manage Security for Applications Azure Key Vault Azure Managed Identity Manage Workloads in Azure Migrate Workloads using Azure Migrate VMware - Agentless Migration VMware - Agent-Based Migration Implement Azure Backup Azure to Azure Site Recovery Implement Azure Update Management Implement Container-Based Applications Azure Container Instances Configure Azure Kubernetes Service Implement an Application Infrastructure Create and Configure Azure App Service Create an App Service Web App for Containers Create and Configure an App Service Plan Configure Networking for an App Service Create and Manage Deployment Slots Implement Logic Apps Implement Azure Functions Implement Cloud Infrastructure Monitoring Azure Infrastructure Security Monitoring Azure Monitor Azure Workbooks Azure Alerts Log Analytics Network Watcher Azure Service Health Monitor Azure Costs Azure Application Insights Unified Monitoring in Azure

Duration 5 Days 30 CPD hours This course is intended for Experienced system administrators and network administrators Network and security professionals who work with enterprise and data center networks Overview By the end of the course, you should be able to meet the following objectives: Use the native tools available in NSX-T Data Center to identify and troubleshoot the problems related to the NSX-T Data Center environment Use VMware vRealize Log Insight™ and VMware vRealize Network Insight™ to identify and troubleshoot the problems related to the NSX-T Data Center environment Explain the NSX-T Data Center infrastructure components and the communications between them Identify, analyze, and troubleshoot problems related to the management, control, and data planes in NSX-T Data Center Identify, analyze, and troubleshoot problems related to infrastructure preparation in NSX-T Data Center Identify, analyze, and troubleshoot problems related to logical switching and logical routing in NSX-T Data Center Identify, analyze, and troubleshoot network security problems related to the NSX-T Data Center Distributed and Gateway firewalls Identify, analyze, and troubleshoot problems related to VPN and the VMware NSX Advanced Load Balancer™ Identify the components and packet flows involved in the NSX-T Data Center datapath and troubleshoot related problems This five-day, hands-on training course provides the advanced knowledge, skills, and tools to achieve competency in operating and troubleshooting the VMware NSX-T? Data Center environment. In this course, you are introduced to workflows of various networking and security constructs along with several operational and troubleshooting tools that help you manage and troubleshoot your NSX-T Data Center environment.In addition, you are presented with various types of technical problems, which you will identify, analyze, and solve through a systematic process. Course Introduction Introduction and course logistics Course objectives NSX-T Data Center Operations and Tools Explain and validate the native troubleshooting tools (dashboards, Traceflow, live traffic analysis, port mirroring) for the NSX-T Data Center environment Configure syslog, IPFIX, and log collections for the NSX-T Data Center environment Integrate NSX-T Data Center with vRealize Log Insight and vRealize Network Insight Validate and review the API methods available to configure the NSX-T Data Center environment Troubleshooting the NSX Management Cluster Describe the NSX Management cluster architecture, components, and communication channels Identify the workflows involved in configuring the NSX Management cluster Validate and troubleshoot the NSX Management cluster formation Troubleshooting Infrastructure Preparation Describe the data plane architecture, components, and communication channels Explain and troubleshoot VMware ESXi? transport node preparation issues Explain and troubleshoot KVM transport node preparation issues Explain and troubleshoot VMware NSX© Edge? transport node preparation issue Troubleshooting Logical Switching Describe the architecture of logical switching List the modules and processes involved in configuring logical switching Explain the importance of N-VDS and VDS in transport nodes Describe the procedure to migrate from N-VDS to VDS Review the architecture and workflows involved in attaching workloads to segments Identify and troubleshoot common logical switching issues Troubleshooting Logical Routing Review the architecture of logical routing and NSX Edge nodes Explain the workflows involved in the configuration of Tier-0 and Tier-1 gateways Explain the high availability modes and validate logical router placements Identify and troubleshoot common logical routing issues using both BGP and OSPF Troubleshooting Security Review the architecture of the Distributed Firewall Explain the workflows involved in configuring the Distributed Firewall Review the architecture of the Gateway Firewall Explain the workflows involved in configuring the Gateway Firewall Identify and troubleshoot common distributed firewall and Gateway Firewall issues Troubleshooting the NSX Advanced Load Balancer and VPN Services Review the NSX Advanced Load Balancer architecture and components Identify and troubleshoot common NSX Advanced Load Balancer issues Review of IPsec and L2 VPN architecture and components Identify and troubleshoot common IPsec and L2 VPN issues Datapath Walkthrough Verify and validate the path of the packet on the NSX datapath (East-West and South-North) Identify and perform packet captures at various points in the datapath Use NSX CLI and native hypervisor commands to retrieve configurations involved in the NSX datapath

Duration 3 Days 18 CPD hours This course is intended for This is an introductory- level course appropriate for those who are developing applications using relational databases, or who are using SQL to extract and analyze data from databases and need to use the full power of SQL queries. Overview This course combines expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our expert practitioner, attendees will learn to: Maximize the potential of SQL to build powerful, complex and robust SQL queries Query multiple tables with inner joins, outer joins and self joins Construct recursive common table expressions Summarize data using aggregation and grouping Execute analytic functions to calculate ranks Build simple and correlated subqueries Thoroughly test SQL queries to avoid common errors Select the most efficient solution to complex SQL problems A company?s success hinges on responsible, accurate database management. Organizations rely on highly available data to complete all sorts of tasks, from creating marketing reports and invoicing customers to setting financial goals. Data professionals like analysts, developers and architects are tasked with creating, optimizing, managing and analyzing data from databases ? with little room for error. When databases aren?t built or maintained correctly, it?s easy to mishandle or lose valuable data. Our SQL Programming and Database Training Series provides students with the skills they require to develop, analyze and maintain data and in correctly structured, modern and secure databases. SQL is the cornerstone of all relational database operations. In this hands-on course, you learn to exploit the full potential of the SELECT statement to write robust queries using the best query method for your application, test your queries, and avoid common errors and pitfalls. It also teaches alternative solutions to given problems, enabling you to choose the most efficient solution in each situation. Introduction: Quick Tools Review Introduction to SQL and its development environments Using SQL*PLUS Using SQL Developer Using the SQL SELECT Statement Capabilities of the SELECT statement Arithmetic expressions and NULL values in the SELECT statement Column aliases Use of concatenation operator, literal character strings, alternative quote operator, and the DISTINCT keyword Use of the DESCRIBE command Restricting and Sorting Data Limiting the Rows Rules of precedence for operators in an expression Substitution Variables Using the DEFINE and VERIFY command Single-Row Functions Describe the differences between single row and multiple row functions Manipulate strings with character function in the SELECT and WHERE clauses Manipulate numbers with the ROUND, TRUNC and MOD functions Perform arithmetic with date data Manipulate dates with the date functions Conversion Functions and Expressions Describe implicit and explicit data type conversion Use the TO_CHAR, TO_NUMBER, and TO_DATE conversion functions Nest multiple functions Apply the NVL, NULLIF, and COALESCE functions to data Decode/Case Statements Using the Group Functions and Aggregated Data Group Functions Creating Groups of Data Having Clause Cube/Rollup Clause SQL Joins and Join Types Introduction to JOINS Types of Joins Natural join Self-join Non equijoins OUTER join Using Subqueries Introduction to Subqueries Single Row Subqueries Multiple Row Subqueries Using the SET Operators Set Operators UNION and UNION ALL operator INTERSECT operator MINUS operator Matching the SELECT statements Using Data Manipulation Language (DML) statements Data Manipulation Language Database Transactions Insert Update Delete Merge Using Data Definition Language (DDL) Data Definition Language Create Alter Drop Data Dictionary Views Introduction to Data Dictionary Describe the Data Dictionary Structure Using the Data Dictionary views Querying the Data Dictionary Views Dynamic Performance Views Creating Sequences, Synonyms, Indexes Creating sequences Creating synonyms Creating indexes Index Types Creating Views Creating Views Altering Views Replacing Views Managing Schema Objects Managing constraints Creating and using temporary tables Creating and using external tables Retrieving Data Using Subqueries Retrieving Data by Using a Subquery as Source Working with Multiple-Column subqueries Correlated Subqueries Non-Correlated Subqueries Using Subqueries to Manipulate Data Using the Check Option Subqueries in Updates and Deletes In-line Views Data Control Language (DCL) System privileges Creating a role Object privileges Revoking object privileges Manipulating Data Overview of the Explicit Default Feature Using multitable INSERTs Using the MERGE statement Tracking Changes in Data

Duration 3 Days 18 CPD hours This course is intended for The primary audience for this course is as follows: Customers configuring and maintaining CUCM 8.x, 9.x, 10.x, 11.0, or 12.x. PBX System Administrators transitioning to CUCM administration IP networking professionals taking on responsibility for CUCM administration Workers being cross-trained for CUCM administration coverage The secondary audience for this course is as follows: Cisco Unified Communications system channel partners and resellers Overview Upon completing this course, the learner will be able to meet these overall objectives: Demonstrate an overall understanding of the Cisco Unified Communications Manager (CUCM) 12.x (or earlier version) system and its environment Configure CUCM to support IP Phones in multiple locations Configure CUCM to route calls to internal and PSTN destinations Configure User accounts and multi-level administration Understand User Web Page functionality Configure user features, including Hunt Groups, Call Pickup, and Call Park. Understand the capabilities of and demonstrate the Bulk Administration Tool Understand the SMART Licensing model for Cisco Unified Communications Understand and demonstrate the use of the Unified Reporting tool Understand and demonstrate the use of the Dialed Number Analyzer Communications Manager Administration for Version 12.5 (CMA v12.5) is an instructor-led course presented to system administrators and customers involved with the day-to-day operation of the Cisco Unified Communications Manager product. This course introduces you to the CUCM system, the necessary procedures for administering IP Phones and Users, understanding the Dial Plan and implementing Features. In addition to instructor-led lectures and discussions, you will configure CUCM and Cisco IP Phones in the lab, either in a live classroom or WebEx remote classroom environment. While the Cisco Unified Communications Manager software used in the class is version 12.5.1, the course material applies to versions 8.x, 9.x, 10.x, 11.x, or 12.x. The concepts and the lab tasks are the same for most of the Cisco Unified Communications Manager software versions CUCM System Basics Introduction to IP Telephony Traditional Voice vs. IP Telephony Clustering Overview Intra-Cluster Communications CUCM Redundancy Options Deployment Models Campus (Single Site) Deployment Centralized Call Processing Deployment Distributed Call Processing Deployment Clustering over the IP WAN Call Processing Deployment Hybrid Call Processing Deployment Basics of CUCM Configuration Administrative Interfaces Administration and Serviceability Unified Reporting and the Enterprise License Manager Disaster Recovery System and Unified OS Administration Navigation Bar Command Line Interface Server Redundancy: CM Groups CM Group Configuration Date/Time Group Regions and Codecs Locations Device Pool Configuration Service Parameters Configuration Enterprise Parameters Configuration Supporting Phones and Users Configuring CUCM to Support Phones Cisco Unified IP Phone Model Ranges Specialized Cisco IP 89xx and 99xx phones Cisco Jabber Client Phone Button Templates Softkey Template Cisco IP Phone Registration Device Defaults Phone Configuration Manual Phone Configuration Auto-Registration Self-Provisioning Using the Bulk Administration Tool (BAT) Deploying new phones and users Overview of the Auto-Register Phone Tool Configuring CUCM to Support Users Understanding CUCM Users Manual User Creation User Import with BAT Importing Users with LDAP Sync LDAP Authentication Understanding User Administration Configuring User Administration Working with Access Control Groups Assigning End Users to Access Control Groups User Web Pages Understanding the Dial Plan Dial Plan Overview Introduction to the Dial Plan Understanding Dial Plan Components Route Lists, Route Groups and Devices Call Routing Understanding Digit Analysis Basics of Dial Plan Configuration Basics of the Dial Plan Dial Plan Configuration Translation Patterns Route Plan Report Advanced Dial Plan Configuration Understanding Digit Manipulation External Phone Number Masks Transformation Masks Discard Digits Instructions: PreDot Class of Control Overview of Class of Control Partitions and Calling Search Space Traditional vs. Line/Device Approach Configuring Partitions and CSSs Time of Day Routing PLAR Application Forced Authorization Codes CUCM Features Media Resources Overview of Media Resources Conference Bridge Music on Hold Transcoder Annunciator Overview of Media Resource Management Configuring Media Resources User Features Configuring Call Coverage in Cisco Unified Communications Manager Call Coverage in Cisco Unified Communications Manager Hunt Group Overview Hunt Group Configuration Final Forwarding Shared Lines Call Pickup Directed and Group Call Pickup Call Park Lab Outline Configuring the System to Support Cisco IP Phones Creating and Associating Users Configuring Basic Dial Plan Elements Configuring Complex Dial Plan Elements Implementing Class of Control Configuring Media Resources Configuring Hunt Groups and Call Coverage Configuring Call Pickup and Call Park

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

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

Duration 5 Days 30 CPD hours This course is intended for This course is recommended for IT Professionals and Consultants. Overview Identify risks and areas for improvement in a Citrix Virtual Apps and Desktops environment by assessing relevant information in an existing deployment. Determine core Citrix Virtual Apps and Desktops design decisions and align them to business requirements to achieve a practical solution. Design a Citrix Virtual Apps and Desktops disaster recovery plan and understand different disaster recovery considerations. This advanced 5-day training course teaches the design principles for creating a Citrix Virtual Apps and Desktops virtualization solution. In this training, you will also learn how to assess existing environments, explore different scenarios, and make design decisions based on business requirements. This course covers the Citrix Consulting approach to design and covers the key design decisions through lectures, lab exercises, and interactive discussions. You will also learn about additional considerations and advanced configurations for multi-location solutions and disaster recovery planning. This training will help you prepare for the Citrix Certified Expert in Virtualization (CCE-V) exam. Module 1: Methodology & Assessment The Citrix Consulting Methodology Citrix Consulting Methodology Use Business Drivers Prioritize Business Drivers User Segmentation User Segmentation Process App Assessment Introduction App Assessment Analysis Why Perform a Capabilities Assessment? Common Capabilities Assessment Risks Module 2: User Layer Endpoint Considerations Peripherals Considerations Citrix Workspace App Version Considerations Citrix Workspace App Multiple Version Considerations Network Connectivity and the User Experience Bandwidth and Latency Considerations Graphics Mode Design Considerations HDX Transport Protocols Considerations Media Content Redirection Considerations Session Interruption Management Session Reliability Feature Considerations Session Interruption Management Auto-Client Reconnect Feature Considerations Session Interruption Management ICA Keep-Alive Feature Considerations Module 3: Access Layer Access Matrix Access Layer Access Layer Communications Double-Hop Access Layer Considerations Citrix Cloud Access Layer Considerations Use Cases for Multiple Stores Define Access Paths per User Group Define Number of URLs Configuration and Prerequisites for Access Paths Citrix Gateway Scalability Citrix Gateway High Availability StoreFront Server Scalability StoreFront Server High Availability Module 4: Resource Layer - Images Flexcast Models VDA Machine Scalability VDA Machine Sizing with NUMA VDA Machine Sizing VDA Machine Scalability Cloud Considerations Scalability Testing and Monitoring Secure VDA Machines Network Traffic Secure VDA Machines Prevent Breakouts Secure VDA Machines Implement Hardening Secure VDA Machines Anti-Virus Review of Image Methods Citrix Provisioning Overall Benefits and Considerations Citrix Provisioning Target Device Boot Methods Citrix Provisioning Read Cache and Sizing Citrix Provisioning Write Cache Type Citrix Provisioning vDisk Store Location Citrix Provisioning Network Design Citrix Provisioning Scalability Considerations Citrix Machine Creation Services Overall Benefits and Considerations Citrix Machine Creation Services Cloning Types Citrix Machine Creation Services Storage Locations & Sizing Citrix Machine Services Read and Write Cache App Layering Considerations Image Management Methods Module 5: Resource Layer - Applications and Personalization Application Delivery Option Determine the Optimal Deployment Method for an App General Application Concerns Profile Strategy Profile Types Review Citrix Profile Management Design Considerations Citrix Profile Management Scaling Citrix Profile Management Permissions Policies Review Optimize Logon Performance with Policies Printing Considerations Module 6: Control Layer Pod Architecture Introduction Pod Architecture Considerations Citrix Virtual Apps and Desktops Service Design Considerations Implement User Acceptance Testing Load Balancing the Machine Running the VDA Citrix Director Design Considerations Management Console Considerations Change Control Delivery Controller Scalability and High Availability Control Layer Security Configuration Logging Considerations Session Recording Module 7: Hardware/Compute Layer Hypervisor Host Hardware Considerations Separating Workloads Considerations Workload Considerations VMs Per Host and Hosts Per Pool Citrix Hypervisor Scalability VM Considerations in Azure and Amazon Web Services Storage Tier Considerations Storage I/O Considerations Storage Architecture Storage RAID & Disk Type Storage Sizing LUNs Storage Bandwidth Storage in Public Cloud Datacenter Networking Considerations Securing Hypervisor Administrative Access Secure the Physical Datacenter Secure the Virtual Datacenter Module 8: Module 8: High Availability and Multiple Location Environments Redundancy vs. Fault Tolerance vs. High Availability Multi-Location Architecture Considerations Multi-Site Architecture Considerations Global Server Load Balancing Optimal Gateway Routing Zone Preference and Failover StoreFront Resource Aggregation StoreFront Subscription Sync Hybrid Environment Options Citrix Provisioning Across Site Site Database Scalability and High Availability Citrix Provisioning Across Sites Considerations Citrix Machine Creation Across Sites App Layering Across Sites Managing Roaming Profiles and Citrix Workspace App Configurations Across Devices Profile Management Multi-Site Replication Considerations Folder Redirections and Other User Data in a Multi-Location Environment Application Data Considerations Cloud-Based Storage Replication Options Multi-Location Printing Considerations Zone Considerations Active Directory Considerations Module 9: Disaster Recovery Tiers of Disaster Recovery Disaster Recovery Considerations Business Continuity Planning and Testing Citrix Standard of Business Continuity

Duration 3 Days 18 CPD hours This course is intended for The ideal audience for the RPA and UiPath Boot Camp is beginners in the field of RPA and individuals in roles such as developers, project managers, operation analysts, and tech enthusiasts looking to familiarize themselves with automation technologies. It's also perfectly suited for business professionals keen on understanding and implementing automated solutions within their organizations to optimize processes. 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 Automation Learning expert instructor, students will explore: Gain a thorough understanding of Robotic Process Automation (RPA) and its applications using UiPath, setting a solid foundation for future learning and application. Learn to record and play in UiPath Studio, a key skill that enables automating complex tasks in a user-friendly environment. Master the art of designing and controlling workflows using Sequencing, Flowcharting, and Control Flow, helping to streamline and manage automation processes effectively. Acquire practical skills in data manipulation, from variable management to CSV/Excel and data table conversions, empowering you to handle data-rich tasks with confidence. Develop competence in managing controls and exploring various plugins and extensions, providing a broader toolkit for handling diverse automation projects. Get hands-on experience with exception handling, debugging, logging, code management, and bot deployment, fundamental skills that ensure your automated processes are reliable and efficient. How to deploy and control Bots with UiPath Orchestrator The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. What is Robotic Process Automation? Scope and techniques of automation Robotic process automation About UiPath The future of automation Record and Play UiPath stack Downloading and installing UiPath Studio Learning UiPath Studio Task recorder Step-by-step examples using the recorder Sequence, Flowchart, and Control Flow Sequencing the workflow Activities Control flow, various types of loops, and decision making Step-by-step example using Sequence and Flowchart Step-by-step example using Sequence and Control flow Data Manipulation Variables and scope Collections Arguments ? Purpose and use Data table usage with examples Clipboard management File operation with step-by-step example CSV/Excel to data table and vice versa (with a step-by-step example) Taking Control of the Controls Finding and attaching windows Finding the control Techniques for waiting for a control Act on controls ? mouse and keyboard activities Working with UiExplorer Handling events Revisit recorder Screen Scraping When to use OCR Types of OCR available How to use OCR Avoiding typical failure points Tame that Application with Plugins and Extensions Terminal plugin SAP automation Java plugin Citrix automation Mail plugin PDF plugin Web integration Excel and Word plugins Credential management Extensions ? Java, Chrome, Firefox, and Silverlight Handling User Events and Assistant Bots What are assistant bots? Monitoring system event triggers Monitoring image and element triggers Launching an assistant bot on a keyboard event Exception Handling, Debugging, and Logging Exception handling Common exceptions and ways to handle them Logging and taking screenshots Debugging techniques Collecting crash dumps Error reporting Managing and Maintaining the Code Project organization Nesting workflows Reusability of workflows Commenting techniques State Machine When to use Flowcharts, State Machines, or Sequences Using config files and examples of a config file Integrating a TFS server Deploying and Maintaining the Bot Publishing using publish utility Overview of Orchestration Server Using Orchestration Server to control bots Using Orchestration Server to deploy bots License management Publishing and managing updates

Duration 5 Days 30 CPD hours This course is intended for Telco cloud system administrators and telco network operations engineers Professionals who work with telco or enterprise and data center networks Designers and operations engineers who manage telco workloads Overview By the end of the course, you should be able to meet the following objectives: List VMware Telco Cloud Automation deployment options and procedures Define Infrastructure Automation and describe infrastructure deployment Describe the VMware Telco Cloud Automation infrastructure settings Configure containers as a service functionality Describe partner integration options and procedures Instantiate network services and network functions Describe the authorization model of VMware Telco Cloud Automation Define platform life cycle management (LCM) for VMware Telco Cloud Automation Enumerate troubleshooting concepts and day two operations for VMware Telco Cloud Automation Describe the use of APIs within VMware Telco Cloud Automation List examples of how VMware Telco Cloud Automation can be used in a CICD environment This five-day, hands-on training course provides you with the advanced knowledge, skills, and tools to achieve competency in operating and troubleshooting the VMware Telco Cloud Automation environment. In this course, you are introduced to VMware Telco Cloud Automation infrastructure settings, deployment options and procedures. You will explore containers as a service and understand the workflow details of partner integration processes. You will learn about infrastructure automation and its importance in VMware Telco Cloud Automation. You will onboard and instantiate network functions and network services using hands-on lab exercises.In addition, this course teaches life cycle management workflows as well as several types of technical problems in VMware Telco Cloud Automation, which you will identify, analyze, and solve through a systematic process. Course Introduction Introductions and course logistics Course objectives VMware Telco Cloud Automation Installation Describe day zero operations for VMware Telco Cloud Automation Describe the VMware Telco Cloud Automation architecture List the steps to perform VMware Telco Cloud Automation deployment List the steps to perform VMware Telco Cloud Automation control plane integration Describe VMware Telco Cloud Automation control plane scaling Describe the requirements for other applications such as vRealize Orchestrator and Harbor Describe where, when, and how to use VMware Telco Cloud Automation tagging Day 1 Operations: Infrastructure Automation Describe infrastructure automation List the use cases of infrastructure automation List the benefits of infrastructure automation Describe the infrastructure requirements of infrastructure automation Describe the infrastructure automation domains List the steps to deploy an infrastructure using infrastructure automation Day 1 Operations: Infrastructure Settings Describe the VMware Telco Cloud Automation infrastructure options Describe VMware Telco Cloud Automation infrastructure requirements Outline the role of virtual infrastructure and VMware Telco Cloud Automation Identify the benefits of public and private infrastructures List the steps to integrate a VM-based virtual infrastructure List the steps to integrate a container-based virtual infrastructure Describe private infrastructure requirements Day 1 Operations: Containers as a Service Define containers as a service (CaaS) List the challenges of CNF deployment without automation Describe the Kubernetes and Tanzu Kubernetes Grid architectures List steps to create a Kubernetes cluster template Describe the process for deploying node pools and groups List the steps to support anti-affinity of workload cluster nodes Describe cluster monitoring List CaaS scale options Day 1 Operations: Partner Integration Describe partner integration and the types of partners Describe Harbor and the various Harbor platforms List the steps to interface with a Harbor platform Compare and contrast specialized VNF managers (S-VNFMs) and generic VNF managers (G-VNFMs) Explain how to add an S-VNFM Define S-VNFM use cases List the benefits and challenges of using Airgap Day 1 Operations: Network Functions ad Network Services Describe the roles of network services and network functions List the types of descriptors Describe the role of TOSCA Describe the role of onboarding List the steps to onboard network functions and network services Examine the results of the onboarding process List the steps to instantiate network functions and network services Examine the results of the instantiation process Day 2 Operations: Authorization Model Explain the resources that can be accessed in vSphere Define the role of a vCenter Server system in credential management Define the role of Keycloak in credential management Describe the procedures to create, delete, and modify rules using vCenter Server Explain how to control and verify access to vSphere resources List the roles in VMware Telco Cloud Automation Explain the tasks and list the levels of permissions needed in VMware Telco Cloud Automation List all the permissions and filters that can be implemented in VMware Telco Cloud Automation Day 2 Operations: Life Cycle Management Explain the life cycle stages in VMware Telco Cloud Automation control plane Explain the life cycle stages in VMware Telco Cloud Automation Define an upgrade schedule Apply an upgrade schedule for life cycle management of the VMware Telco Cloud Automation control plane Apply an upgrade schedule for life cycle management in VMware Telco Cloud Automation Describe network function and network service life cycle management events Execute network function and network service healing Perform network function and network service termination Day 2 Operations: Troubleshooting List the components of the VMware Telco Cloud Automation dashboard Explain the features of fault management in VMware Telco Cloud Automation Explain the features of performance management in VMware Telco Cloud Automation Describe the use of fault management of VMware Telco Cloud Automation for VNFs and CNFs Describe the use of performance management of VMware Telco Cloud Automation for VNFs and CNFs Describe the use of CCLI for troubleshooting Define the procedures to integrate vRealize Operations Manager with VMware Telco Cloud Automation Describe how to use vRealize Operations Day Two Operations: API Management Define the VMware Telco Cloud Automation API Explain the API architecture Describe VMware Telco Cloud Automation API use cases Describe how to request security tokens for implementation Explain how to implement commands through external systems using APIs Day Two Operations: Continuous Integration and Continuous Delivery Describe continuous integration and continuous delivery (CICD) List the benefits and challenges of CICD Describe how VMware Telco Cloud Automation can be used in a CICD environment Explore VMware Telco Cloud Automation CICD examples

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