5450 Practitioner courses delivered Online

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with solid Python skills who wish to learn and use basic machine learning algorithms and concepts 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. Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below Getting Started & Optional Python Quick Refresher Statistics and Probability Refresher and Python Practice Probability Density Function; Probability Mass Function; Naive Bayes Predictive Models Machine Learning with Python Recommender Systems KNN and PCA Reinforcement Learning Dealing with Real-World Data Experimental Design / ML in the Real World Time Permitting: Deep Learning and Neural Networks Machine Learning Essentials with Python is a foundation-level, three-day hands-on course that teaches students core skills and concepts in modern machine learning practices. This course is geared for attendees experienced with Python, but new to machine learning, who need introductory level coverage of these topics, rather than a deep dive of the math and statistics behind Machine Learning. Students will learn basic algorithms from scratch. For each machine learning concept, students will first learn about and discuss the foundations, its applicability and limitations, and then explore the implementation and use, reviewing and working with specific use casesWorking in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:Popular machine learning algorithms, their applicability and limitationsPractical application of these methods in a machine learning environmentPractical use cases and limitations of algorithms Getting Started Installation: Getting Started and Overview LINUX jump start: Installing and Using Anaconda & Course Materials (or reference the default container) Python Refresher Introducing the Pandas, NumPy and Scikit-Learn Library Statistics and Probability Refresher and Python Practice Types of Data Mean, Median, Mode Using mean, median, and mode in Python Variation and Standard Deviation Probability Density Function; Probability Mass Function; Naive Bayes Common Data Distributions Percentiles and Moments A Crash Course in matplotlib Advanced Visualization with Seaborn Covariance and Correlation Conditional Probability Naive Bayes: Concepts Bayes? Theorem Naive Bayes Spam Classifier with Naive Bayes Predictive Models Linear Regression Polynomial Regression Multiple Regression, and Predicting Car Prices Logistic Regression Logistic Regression Machine Learning with Python Supervised vs. Unsupervised Learning, and Train/Test Using Train/Test to Prevent Overfitting Understanding a Confusion Matrix Measuring Classifiers (Precision, Recall, F1, AUC, ROC) K-Means Clustering K-Means: Clustering People Based on Age and Income Measuring Entropy LINUX: Installing GraphViz Decision Trees: Concepts Decision Trees: Predicting Hiring Decisions Ensemble Learning Support Vector Machines (SVM) Overview Using SVM to Cluster People using scikit-learn Recommender Systems User-Based Collaborative Filtering Item-Based Collaborative Filtering Finding Similar Movie Better Accuracy for Similar Movies Recommending movies to People Improving your recommendations KNN and PCA K-Nearest-Neighbors: Concepts Using KNN to Predict a Rating for a Movie Dimensionality Reduction; Principal Component Analysis (PCA) PCA with the Iris Data Set Reinforcement Learning Reinforcement Learning with Q-Learning and Gym Dealing with Real-World Data Bias / Variance Tradeoff K-Fold Cross-Validation Data Cleaning and Normalization Cleaning Web Log Data Normalizing Numerical Data Detecting Outliers Feature Engineering and the Curse of Dimensionality Imputation Techniques for Missing Data Handling Unbalanced Data: Oversampling, Undersampling, and SMOTE Binning, Transforming, Encoding, Scaling, and Shuffling Experimental Design / ML in the Real World Deploying Models to Real-Time Systems A/B Testing Concepts T-Tests and P-Values Hands-on With T-Tests Determining How Long to Run an Experiment A/B Test Gotchas Capstone Project Group Project & Presentation or Review Deep Learning and Neural Networks Deep Learning Prerequisites The History of Artificial Neural Networks Deep Learning in the TensorFlow Playground Deep Learning Details Introducing TensorFlow Using TensorFlow Introducing Keras Using Keras to Predict Political Affiliations Convolutional Neural Networks (CNN?s) Using CNN?s for Handwriting Recognition Recurrent Neural Networks (RNN?s) Using an RNN for Sentiment Analysis Transfer Learning Tuning Neural Networks: Learning Rate and Batch Size Hyperparameters Deep Learning Regularization with Dropout and Early Stopping The Ethics of Deep Learning Learning More about Deep Learning Additional course details: Nexus Humans Machine Learning Essentials with Python (TTML5506-P) 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 Machine Learning Essentials with Python (TTML5506-P) 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 System administrators and system integrators responsible for designing, implementing, and managing VMware Aria Automation Overview By the end of the course, you should be able to meet the following objectives: Describe the VMware Aria Automation architecture and use cases in cloud environments Describe the key services of VMware Cloud Automation Services™ Manage VMware Aria Automation entities on VMware and third-party virtual and cloud infrastructures Install VMware Aria Automation with VMware Aria Suite Lifecycle Configure and manage cloud accounts, projects, flavor mappings, image mappings, network profiles, storage profiles, volumes, tags, and services Create, modify, manage, and deploy VMware Aria Automation Templates Customize services and virtual machines with cloudConfig and cloudbase-init Configure and manage VMware Aria Automation Consumption Configure and manage ABX actions, custom properties, event broker subscriptions, and VMware Aria Automation Orchestrator workflows Connect to a Kubernetes cluster and manage namespaces Use VMware Aria Automation Config to configure and deploy systems Use logs and CLI commands to monitor and troubleshoot VMware Aria Automation During this five-day course, you focus on installing, configuring, and managing VMware Aria Automation 8.10? on-premises systems. You learn how it can be used to automate the delivery of virtual machines, applications, and personalized IT services across different data centers and hybrid cloud environments. The course covers how VMware Aria Automation Consumption? can aggregate content in native formats from multiple clouds and platforms into a common catalog.This course also covers interfacing VMware Aria Automation with other systems using VMware Aria Orchestrator and how to use VMware Aria Automation to manage Kubernetes systems and leverage other systems. In this course, you will use VMware Aria Automation Config? as a configuration management tool. Course Introduction Introductions and course logistics Course objectives VMware Aria Automation Overview and Architecture Describe the purpose and functionality of VMware Aria Automation Identify the key services offered by VMware Aria Automation Describe the VMware Aria Automation architecture Describe the use of VMware Workspace ONE Access? Describe the relationship between Kubernetes clusters, container, and VMware Aria Automation services Installing VMware Aria Automation List the different VMware Aria Automation deployment types Describe the purpose of Easy Installer Describe the VMware Aria Automation installation process Authentication and Authorization Identify the steps to integrating Workspace ONE© Access with Active Directory Describe the features of Workspace ONE Access Describe the user roles available in VMware Aria Automation Identify the key tasks performed by each user role Define custom roles Configure branding and multitenancy Basic Initial Configuration Create a basic configuration with a cloud account, cloud zone, project, flavor mapping, and image mapping VMware Aria Automation Templates Configure and deploy a basic VMware Aria Automation template Create a VMware Aria Automation template that can run on any cloud Use cloudConfig and cloudbase-init to run commands, create users, and install software Use YAML for inputs, variables, and conditional deployments Tags Configure tags Describe functions of tags Manage tags Storage Configuration Configure storage profiles Use tags and storage profiles Integrating NSX With VMware Aria Automation List the capabilities and use cases of VMware NSX© Describe the NSX architecture and components Integrate NSX with VMware Aria Automation List the supported network profiles in VMware Aria Automation Use the NSX components to design a multitier application with VMware Aria Automation Templates Identify the network and security options available in design canvas Create and manage on-demand networks and security groups Configure NSX Day 2 actions Integrating with Public Clouds Configure and use VMware Cloud Foundation? accounts Integrate VMware Cloud Director? account Configure and use an AWS cloud account Configure and use an Azure cloud account Configure and use a Google Cloud Platform cloud account Integrate VMware Cloud on AWS cloud account Using VMware Aria Automation Consumption Release a VMware Aria Automation template Define content source and content sharing Define VMware Aria Automation policy enforcement Use custom forms for catalog items VMware Aria Automation Extensibility Describe VMware Aria Automation extensibility Use event topics Create a subscription Call a VMware Aria Automation Orchestrator workflow Create ABX actions Using Kubernetes Clusters Introduction to Kubernetes Connect to an existing Kubernetes Cluster Create a VMware Aria Automation template with Kubernetes components Using VMware Aria Automation Config for Configuration Management Describe VMware Aria Automation Config Use VMware Aria Automation Config for software deployment Use VMware Aria Automation Config for configuration management Use VMware Aria Automation Config with event-driven orchestration VMware Aria Automation Troubleshooting and Integration Demonstrate how to monitor deployment history Demonstrate basic troubleshooting Execute CLI commands Explain how to collect logs Describe integration with VMware Aria Operations for Logs Describe integration with VMware Aria Operations

Duration 2 Days 12 CPD hours This course is intended for System administrators and consultants, application owners, and system architects Overview By the end of the course, you should be able to meet the following objectives: Describe VMware Carbon Black Cloud platform Describe data flows on VMware Carbon Black Cloud Create and edit a custom role in VMware Carbon Black Cloud Recognize the impact of a user role on a console user Describe the VMware Carbon Black Cloud sensor resource usage Explain sensor usage in VMware Carbon Black Cloud Identify configuration settings for endpoints in sensor policy settings Determine requirements for initial deployment of sensors Recognize the differences between attended and unattended sensor installation methods Identify the correct deployment strategy for a given scenario Recognize the deployment process for VMware Carbon Black Cloud Workload™ Identify eligible workloads in a VMware vSphere environment Describe VMware Carbon Black Cloud sensor deployment Manage VMware vSphere workloads Identify sensor status in RepCLI This two-day hands-on training course provides you with the knowledge, skills, and tools to achieve competency in planning and deploying VMware Carbon Black Cloud in your environment. This course explains the VMware Carbon Black Cloud components, managing users and roles in VMware Carbon Black Cloud, configuring policies to support sensor deployment and management, and presents methods for deploying sensors across endpoints and workloads. Course Introduction Introductions and course logistics Course objectives Introduction to VMware Carbon Black Cloud Describe the VMware Carbon Black Cloud platform Describe VMware Carbon Black Cloud operating systems requirements Identify interesting files according to VMware Carbon Black Cloud Identify events collected Describe data flows Managing VMware Carbon Black Cloud Roles and Users Describe the use of roles in VMware Carbon Black Cloud Describe RBAC capabilities Create and edit a custom role Manage new console users Recognize the impact of a user role on a console user Describe authentication mechanisms VMware Carbon Black Cloud Sensors Describe the VMware Carbon Black Cloud sensor resource usage List the supported operating systems for VMware Carbon Black Cloud sensors Explain sensor usage in VMware Carbon Black Cloud Preparing for Deployment Identify configuration settings for endpoints in sensor policy settings Organize sensors using sensor groups to assign the desired policy based on specific criteria Compare VDI sensor settings as compared to traditional endpoint sensor settings Determine requirements for the initial deployment of sensors Evaluate the policy impact on sensors Identify best practices for deploying sensors Installing Sensors Describe how to send an installation request Recognize the features and limitations of an installation code and company code Recognize the process for successfully completing an attended installation Recognize the differences between attended and unattended sensor installation methods Identify the correct deployment strategy for a given scenario Generate logs with unattended installations Generate sensor logs Check network connectivity for sensor installation Deploying Workloads Recognize the deployment process for VMware Carbon Black Cloud Workload Identify eligible workloads in a vSphere environment Recognize how to enable the VMware Carbon Black Cloud sensor on a VM workload Managing Sensors Describe VMware Carbon Black Cloud sensor deployment Explain the differences in sensor status Describe sensor update capabilities Explain sensor actions Manage vSphere workloads Post-deployment Validation Describe the process of a sensor background scan Recognize a properly registered sensor installation Identify sensor status in RepCLI Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware Carbon Black Cloud: Plan and Deploy 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 VMware Carbon Black Cloud: Plan and Deploy course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for This course is designed for professionals in job roles such as: Communication engineers Project managers Network engineers Software engineers System architects The Developing Applications for Cisco Webex and Webex Devices (DEVWBX) v1.1 course prepares you to use the programmability features of Webex©, Cisco© enterprise solution for video conferencing, online meetings, online training, webinars, web conferencing, cloud calling, and collaboration. Through a combination of lessons and hands-on labs, you will learn about Webex Application Programming Interface (API) Foundation, meetings, devices, teams, messaging, embedding Cisco Webex, administration, and compliance. You will learn how to leverage Webex APIs to extend the functionalities of teams, meetings, and devices, and explore how these APIs can help automate, administer, and enforce compliance. This course prepares you for the 300-920 Developing Applications for Cisco Webex and Webex Devices (DEVWBX) exam. Introducing Webex APIs Foundations Webex as an Extensible Platform Building Cisco Webex Teams Applications Introduction to Webex Messaging Developing with Webex Meetings XML API Describe the Capabilities of Cisco Webex Meetings APIs Automating and Extending Cisco Collaboration Devices with xAPI Overview, Capabilities and Transport Methods for Cisco Endpoint Device Programmability Embedding Cisco Webex Benefits of Embedding Cisco Webex into Other Applications Managing Administration and Compliance with Cisco Webex APIs Administer a Cisco Webex Organization

Duration 3 Days 18 CPD hours This course is intended for Experienced system administrators and network administrators Customers, cloud architects, systems engineers, data center administrators Network administrators with experience in managed services or managing a Telco Cloud environment Overview By the end of the course, you should be able to meet the following objectives: Deploy VMware Telco Cloud Service Assurance Manage VMware Telco Cloud Service Assurance to satisfy Telco cloud provider needs Discuss configurable options for VMware Telco Cloud Service Assurance Identify and configure different data sources which are used with VMware Telco Cloud Service Assurance Configure different collectors in VMware Telco Cloud Service Assurance Identify the Root Cause Analysis options with VMware Telco Cloud Service Assurance Discuss data collection in VMware Telco Cloud Service Assurance Explain root cause analysis in VMware Telco Cloud Service Assurance Navigate through the logs for troubleshooting This three-day, hands-on training course provides the knowledge, skills, and tools to achieve competency in installing, configuring, and managing the VMware Telco Cloud Service Assurance environment. In this course, you are introduced to the installation methods of VMware Telco Cloud Service Assurance? across various supported platforms and troubleshooting tools that help you install, manage, and troubleshoot your VMware Telco Cloud Service Assurance environment. In addition, you are presented with various types of configuration options, which you will identify, analyze, and navigate through as you explore the UI and configurable options of the product. Course Introduction Introduction and course logistics Course objectives Introduction to VMware Telco Cloud Service Assurance Describe the features of VMware Telco Cloud Service Assurance List the capabilities of VMware Telco Cloud Service Assurance Discuss the use cases of VMware Telco Cloud Service Assurance Describe the role played by VMware Telco Cloud Service Assurance components in delivering service assurance Deploying VMware Telco Cloud Service Assurance Explain different deployment options of VMware Telco Cloud Service Assurance Identify different deployment methods of VMware Telco Cloud Service Assurance Discuss different phases in deploying VMware Telco Cloud Service Assurance Identify different footprints available for HA based and non-HA based installation of VMware Telco Cloud Service Assurance Describe the SMARTs components of VMware Telco Cloud Service Assurance Deploy VMware Telco Cloud Service Assurance User Access Control Describe the features Role-based Access Control (RBAC) Outline the role of Keycloak in implementing RBAC in VMware Telco Cloud Service Assurance Configure user federation in Keycloak Use the VMware Telco Cloud Service Assurance UI to manage RBAC Create policies in VMware Telco Cloud Service Assurance that align with job roles Services and User Interface Configurations Describe the architecture of logical switching Describe the core services on a TCSA cluster Discuss the Global Manager or Service Assurance Manager (SAM), IP Domain Manager, Server Manager (ESM) Discuss VMware Telco Cloud Service Assurance UI Overview Explain Working with Notifications Elaborate Configuring Summary's Describe Accessing Notification Details Explain Viewing and configuring Topologies List Customizing Topologies Describe Topology Explorer Explain Collecting Troubleshooting Information Discuss Custom models Describe how compute resources are provided to VMware Telco Cloud Service Assurance Describe how storage is provided to VMware Telco Cloud Service Assurance Configure and manage VMware Telco Cloud Service Assurance Discuss configurable options for VMware Telco Cloud Service Assurance Day 1 and Day 2 Operations Review the architecture of logical routing and NSX Edge nodes Identify different data sources to be used with VMware Telco Cloud Service Assurance Configure different collectors with VMware Telco Cloud Service Assurance Describe Alarms and Thresholds Demonstrate how to configure alarms with VMware Telco Cloud Service Assurance Explain how to setup thresholds and timelines in VMware Telco Cloud Service Assurance Define Catalog management and sharing catalogs inside and between organizations. Identify the steps to import or upload data into catalogs. Explain the purpose of catalogs and How to Create a catalog organization. Describe the Purpose and Usage of Open Virtualization Format (OVA) and Custom vApp or VM Properties. Discuss vApp Templates Logs and Troubleshooting Review the architecture of the Distributed Firewall Discuss VMware Telco Cloud Service Assurance installations logs List Smarts installation logs Explain backup and restore options of VMware Telco Cloud Service Assurance Identify the approach for troubleshooting containerized services Discuss monitoring services

Duration 5 Days 30 CPD hours This course is intended for Ideal candidates include network professionals who are looking to build their foundational knowledge of the ClearPass product portfolio. Overview After you successfully complete this course, expect to be able to: Ability to setup ClearPass as a AAA server Demonstrate Configuration Guest, OnGurad, Onboard and Profiling features Integrate with External AD Server Understand Monitoring and Reporting Demonstrate Scaling and deployment of best practices Configure AAA services for both wired and wireless networks Demonstrate the configuration of Aruba Downloadable User Roles. Demonstrate the configuration of Dynamic Segmentation with Aruba switches. This course prepares participants with foundational skills in Network Access Control using the ClearPass product portfolio. This 5-day classroom session includes both instructional modules and labs to teach participants about the major features of the ClearPass portfolio. Participants will learn how to setup ClearPass as an AAA server, and configure the Policy Manager, Guest, OnGuard and Onboard feature sets. In addition, this course covers integration with external Active Directory servers, Monitoring and Reporting, as well as deployment best practices. The student will gain insight into configuring authentication with ClearPass on both wired and wireless networks. Intro to ClearPass BYOD High Level Overview Posture and Profiling Guest and Onboard ClearPass for AAA Policy Service Rules Authentication Authorization and Roles Enforcement Policy and Profiles Authentication and Security Concepts Authentication Types Servers Radius COA Active Directory Certificates Intro to NAD NAD Devices Adding NAD to ClearPass Network Device Groups Network Device Attributes Aruba Controller as NAD Aruba Switch Aruba Instant Monitoring and Troubleshooting Monitoring Troubleshooting Logging Policy Simulation ClearPass Insight Insight Dashboard Insight Reports Insight Alerts Insight Search Insight Administration Insight Replication Active Directory Adding AD as Auth Source Joining AD domain Using AD services External Authentication Multiple AD domains LDAP Static Host Lists SQL Database External Radius Server Guest Guest Account creation Web Login pages Guest Service configuration Self-registration pages Configuring NADS for Guest Guest Manager Deep Dive Web Login Deep Dive Sponsor Approval MAC Caching Onboard Intro to Onboard Basic Onboard Setup Onboard Deepdive Single SSID Onboarding Dual SSID Onboarding Profiling Intro to Profiling Endpoint Analysis Deep Dive Posture Intro to Posture Posture Deployment Options OnGuard Agent Health Collection OnGuard workflow 802.1x with Posture using Persistent/dissolvable agent OnGuard web Login Monitoring and Updates Operation and Admin Users Operations Admin Users Clustering and Redundancy Clustering Redundancy LAB Licensing ClearPass Licensing Base License Applications ClearPass Exchange Intro Examples General HTTP Palo Alto Firewall Configuration Case Study Objectives Discussion Advanced Labs Overview Wired Port Authentication 802.1X for access layer switch ports Profiling on Wired Network Configuration of Dynamic Segmentation Aruba Downloadable User Roles Downloadable User Role Enforcement in ClearPass Aruba Controller/Gateway configuration Aruba Switch configuration Troubleshooting

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Solutions architects IT professionals Overview In this course, you will learn to: Apply data lake methodologies in planning and designing a data lake Articulate the components and services required for building an AWS data lake Secure a data lake with appropriate permission Ingest, store, and transform data in a data lake Query, analyze, and visualize data within a data lake In this course, you will learn how to build an operational data lake that supports analysis of both structured and unstructured data. You will learn the components and functionality of the services involved in creating a data lake. You will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data. The course lectures and labs further your learning with the exploration of several common data lake Introduction to data lakes Describe the value of data lakes Compare data lakes and data warehouses Describe the components of a data lake Recognize common architectures built on data lakes Data ingestion, cataloging, and preparation Describe the relationship between data lake storage and data ingestion Describe AWS Glue crawlers and how they are used to create a data catalog Identify data formatting, partitioning, and compression for efficient storage and query Lab 1: Set up a simple data lake Data processing and analytics Recognize how data processing applies to a data lake Use AWS Glue to process data within a data lake Describe how to use Amazon Athena to analyze data in a data lake Building a data lake with AWS Lake Formation Describe the features and benefits of AWS Lake Formation Use AWS Lake Formation to create a data lake Understand the AWS Lake Formation security model Lab 2: Build a data lake using AWS Lake Formation Additional Lake Formation configurations Automate AWS Lake Formation using blueprints and workflows Apply security and access controls to AWS Lake Formation Match records with AWS Lake Formation FindMatches Visualize data with Amazon QuickSight Lab 3: Automate data lake creation using AWS Lake Formation blueprints Lab 4: Data visualization using Amazon QuickSight Architecture and course review Post course knowledge check Architecture review Course review

Duration 1 Days 6 CPD hours This course is intended for This course is intended for anybody interested in learning what is Azure Services, considering a job or career in Azure Services, or considering obtaining a Microsoft certification in Azure Services Overview Upon successful completion of this course, students will be aware of the key topics and concepts taught in the full two-day AZ-900T00 Microsoft Azure Fundamentals Course. This course is a robust introduction to key topics and concepts in the full two-day AZ-900T00: Microsoft Azure Fundamentals course.ÿ The 2-day AZ-900T00 course includes hands-on labs and is the core foundation class that many other Azure courses build off. Core Azure Concepts Introduction to Azure fundamentals Azure fundamental concepts Core Azure architectural components Overview of Core Azure Services Azure database and analytics services Azure compute services Azure Storage services Azure networking services Overview of Core Solutions and Management Tools on Azure Artificial Intelligence Monitoring service for visibility, insight, and outage mitigation Introduction to tools used to manage and configure your Azure environment Azure IoT service for your application Overview of General Security and Network Security Features Protect against security threats on Azure Secure network connectivity on Azure Overview of Identity, Governance, Privacy, and Compliance Features Examine privacy, compliance, and data protection standards on Azure Overview of Azure Cost Management and Service Level Agreements Manage your Azure costs Azure services, SLAs, and service lifecycle

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: DevOps engineers DevOps architects Operations engineers System administrators Developers Overview In this course, you will learn to: Use DevOps best practices to develop, deliver, and maintain applications and services at high velocity on AWS List the advantages, roles and responsibilities of small autonomous DevOps teams Design and implement an infrastructure on AWS that supports DevOps development projects Leverage AWS Cloud9 to write, run and debug your code Deploy various environments with AWS CloudFormation Host secure, highly scalable, and private Git repositories with AWS CodeCommit Integrate Git repositories into CI/CD pipelines Automate build, test, and packaging code with AWS CodeBuild Securely store and leverage Docker images and integrate them into your CI/CD pipelines Build CI/CD pipelines to deploy applications on Amazon EC2, serverless applications, and container-based applications Implement common deployment strategies such as 'all at once,' 'rolling,' and 'blue/green' Integrate testing and security into CI/CD pipelines Monitor applications and environments using AWS tools and technologies DevOps Engineering on AWS teaches you how to use the combination of DevOps cultural philosophies, practices, and tools to increase your organization?s ability to develop, deliver, and maintain applications and services at high velocity on AWS. This course covers Continuous Integration (CI), Continuous Delivery (CD), infrastructure as code, microservices, monitoring and logging, and communication and collaboration. Hands-on labs give you experience building and deploying AWS CloudFormation templates and CI/CD pipelines that build and deploy applications on Amazon Elastic Compute Cloud (Amazon EC2), serverless applications, and container-based applications. Labs for multi-pipeline workflows and pipelines that deploy to multiple environments are also included. Module 0: Course overview Course objective Suggested prerequisites Course overview breakdown Module 1: Introduction to DevOps What is DevOps? The Amazon journey to DevOps Foundations for DevOps Module 2: Infrastructure automation Introduction to Infrastructure Automation Diving into the AWS CloudFormation template Modifying an AWS CloudFormation template Demonstration: AWS CloudFormation template structure, parameters, stacks, updates, importing resources, and drift detection Module 3: AWS toolkits Configuring the AWS CLI AWS Software Development Kits (AWS SDKs) AWS SAM CLI AWS Cloud Development Kit (AWS CDK) AWS Cloud9 Demonstration: AWS CLI and AWS CDK Hands-on lab: Using AWS CloudFormation to provision and manage a basic infrastructure Module 4: Continuous integration and continuous delivery (CI/CD) with development tools CI/CD Pipeline and Dev Tools Demonstration: CI/CD pipeline displaying some actions from AWS CodeCommit, AWS CodeBuild, AWS CodeDeploy and AWS CodePipeline Hands-on lab: Deploying an application to an EC2 fleet using AWS CodeDeploy AWS CodePipeline Demonstration: AWS integration with Jenkins Hands-on lab: Automating code deployments using AWS CodePipeline Module 5: Introduction to Microservices Introduction to Microservices Module 6: DevOps and containers Deploying applications with Docker Amazon Elastic Container Service and AWS Fargate Amazon Elastic Container Registry and Amazon Elastic Kubernetes service Demonstration: CI/CD pipeline deployment in a containerized application Module 7: DevOps and serverless computing AWS Lambda and AWS Fargate AWS Serverless Application Repository and AWS SAM AWS Step Functions Demonstration: AWS Lambda and characteristics Demonstration: AWS SAM quick start in AWS Cloud9 Hands-on lab: Deploying a serverless application using AWS Serverless Application Model (AWS SAM) and a CI/CD Pipeline Module 8: Deployment strategies Continuous Deployment Deployments with AWS Services Module 9: Automated testing Introduction to testing Tests: Unit, integration, fault tolerance, load, and synthetic Product and service integrations Module 10: Security automation Introduction to DevSecOps Security of the Pipeline Security in the Pipeline Threat Detection Tools Demonstration: AWS Security Hub, Amazon GuardDuty, AWS Config, and Amazon Inspector Module 11: Configuration management Introduction to the configuration management process AWS services and tooling for configuration management Hands-on lab: Performing blue/green deployments with CI/CD pipelines and Amazon Elastic Container Service (Amazon ECS) Module 12: Observability Introduction to observability AWS tools to assist with observability Hands-on lab: Using AWS DevOps tools for CI/CD pipeline automations Module 13: Reference architecture (Optional module) Reference architectures Module 14: Course summary Components of DevOps practice CI/CD pipeline review AWS Certification

Duration 2 Days 12 CPD hours This course is intended for Todas aquellas personas que tengan relaci¢n con proyectos que requieran de una gesti¢n gil: Clientes, Promotores, Project Managers, Proveedores o Subcontratas, Equipo del Proyecto: Perfiles T‚cnicos, Perfiles de apoyo o Staff. En definitiva a cualquier persona que tenga relaci¢n con un proyecto gil. Overview Existen proyectos peque¤os, otros enormes, con una complejidad tecnol¢gica extrema otros en cambio muy sencillos. ¨Debemos gestionar todo tipo de proyectos con el mismo ?m‚todo??Desde finales del siglo pasado, se viene analizando la gesti¢n de proyectos cl sica conocida como Gesti¢n de Proyectos Predictiva, comprobando que no puede/debe ser aplicada a todo tipo de proyecto. Existen multitud de proyectos donde el nivel de detalle de las caracter¡sticas de los entregables est asociado al concepto IKIWISI (I?ll Know It When I See It -> Lo sabr‚ cuando lo vea), otros proyectos que tienen muy bien definido el objetivo, pero dadas unas necesidades cambiantes, la manera de abordarlo puede ser bien diferente, otros proyectos que? En definitiva se ha puesto de manifiesto que la gesti¢n de proyectos predictiva, no es del todo til para estos tipos de proyecto. Durante este curso, analizaremos otra forma de hacer las cosas. Veremos c¢mo abordar estos otros tipos de proyectos que requieren de una gesti¢n diferente: una Gesti¢n µgil. Existen proyectos peque¤os, otros enormes, con una complejidad tecnol¢gica extrema otros en cambio muy sencillos. ¨Debemos gestionar todo tipo de proyectos con el mismo ?m‚todo?? Introducci¢n a Agile y Scrum Primeros conceptos Metodolog¡as µgiles Agile Manifesto y Principios µgiles ¨Qu‚ hay bajo el paraguas de Agile? Las 3 grandes aproximaciones a Agile: LEAN, XP y Scrum El entorno de trabajo µgil Roles µgiles Trabajando de forma gil Definir la Visi¢n del Producto Planificar la Release y los Sprints El trabajo del d¡a a d¡a La revisi¢n del producto Preparando la entrega Gestionando de forma gil Gesti¢n del Alcance y los Proveedores Gesti¢n de Tiempos y Costes Gesti¢n del Equipo y las Comunicaciones Gesti¢n de Riesgos y la Calidad Garantizando el ‚xito Construir una base s¢lida Impulsar el cambio