126 Shell courses in Edinburgh delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This course is intended for system and network administrators responsible for installation, setup, configuration, and administration of the BIG-IP LTM system. This course gives network professionals a functional understanding of BIG-IP Local Traffic Manager, introducing students to both commonly used and advanced BIG-IP LTM features and functionality. Incorporating lecture, extensive hands-on labs, and classroom discussion, the course helps students build the well-rounded skill set needed to manage BIG-IP LTM systems as part of a flexible and high performance application delivery network. Module 1: Setting Up the BIG-IP System Introducing the BIG-IP System Initially Setting Up the BIG-IP System Archiving the BIG-IP Configuration Leveraging F5 Support Resources and Tools Module 2: Reviewing Local Traffic Configuration Reviewing Nodes, Pools, and Virtual Servers Reviewing Address Translation Reviewing Routing Assumptions Reviewing Application Health Monitoring Reviewing Traffic Behavior Modification with Profiles Reviewing the TMOS Shell (TMSH) Reviewing Managing BIG-IP Configuration Data Module 3: Load Balancing Traffic with LTM Exploring Load Balancing Options Using Priority Group Activation and Fallback Host Comparing Member and Node Load Balancing Module 4: Modifying Traffic Behavior with Persistence Reviewing Persistence Introducing SSL Persistence Introducing SIP Persistence Introducing Universal Persistence Introducing Destination Address Affinity Persistence Using Match Across Options for Persistence Module 5: Monitoring Application Health Differentiating Monitor Types Customizing the HTTP Monitor Monitoring an Alias Address and Port Monitoring a Path vs. Monitoring a Device Managing Multiple Monitors Using Application Check Monitors Using Manual Resume and Advanced Monitor Timer Settings Module 6: Processing Traffic with Virtual Servers Understanding the Need for Other Virtual Server Types Forwarding Traffic with a Virtual Server Understanding Virtual Server Order of Precedence Path Load Balancing Module 7: Processing Traffic with SNATs Overview of SNATs Using SNAT Pools SNATs as Listeners SNAT Specificity VIP Bounceback Additional SNAT Options Network Packet Processing Module 8: Modifying Traffic Behavior with Profiles Profiles Overview TCP Express Optimization TCP Profiles Overview HTTP Profile Options OneConnect Offloading HTTP Compression to BIG-IP HTTP Caching Stream Profiles F5 Acceleration Technologies Module 9: Selected Topics VLAN, VLAN Tagging, and Trunking Restricting Network Access SNMP Features Segmenting Network Traffic with Route Domains Module 10: Deploying Application Services with iApps Simplifying Application Deployment with iApps Using iApps Templates Deploying an Application Service Leveraging the iApps Ecosystem on DevCentral Module 11: Customizing Application Delivery with iRules and Local Traffic Policies Getting Started with iRules Configuring and Managing Policy Rules Module 12: Securing Application Delivery with LTM Understanding Today?s Threat Landscape Integrating LTM Into Your Security Strategy Defending Your Environment Against SYN Flood Attacks Defending Your Environment Against Other Volumetric Attacks Addressing Application Vulnerabilities with iRules and Local Traffic Policies Detecting and Mitigating Other Common HTTP Threats Module 13: Final Lab Project About the Final Lab Project

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Architects and operators who build and manage data analytics pipelines Overview In this course, you will learn to: Compare the features and benefits of data warehouses, data lakes, and modern data architectures Design and implement a batch data analytics solution Identify and apply appropriate techniques, including compression, to optimize data storage Select and deploy appropriate options to ingest, transform, and store data Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights Secure data at rest and in transit Monitor analytics workloads to identify and remediate problems Apply cost management best practices In this course, you will learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service. You will learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloging, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon EMR. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Introduction to Amazon EMR Using Amazon EMR in analytics solutions Amazon EMR cluster architecture Interactive Demo 1: Launching an Amazon EMR cluster Cost management strategies Module 2: Data Analytics Pipeline Using Amazon EMR: Ingestion and Storage Storage optimization with Amazon EMR Data ingestion techniques Module 3: High-Performance Batch Data Analytics Using Apache Spark on Amazon EMR Apache Spark on Amazon EMR use cases Why Apache Spark on Amazon EMR Spark concepts Interactive Demo 2: Connect to an EMR cluster and perform Scala commands using the Spark shell Transformation, processing, and analytics Using notebooks with Amazon EMR Practice Lab 1: Low-latency data analytics using Apache Spark on Amazon EMR Module 4: Processing and Analyzing Batch Data with Amazon EMR and Apache Hive Using Amazon EMR with Hive to process batch data Transformation, processing, and analytics Practice Lab 2: Batch data processing using Amazon EMR with Hive Introduction to Apache HBase on Amazon EMR Module 5: Serverless Data Processing Serverless data processing, transformation, and analytics Using AWS Glue with Amazon EMR workloads Practice Lab 3: Orchestrate data processing in Spark using AWS Step Functions Module 6: Security and Monitoring of Amazon EMR Clusters Securing EMR clusters Interactive Demo 3: Client-side encryption with EMRFS Monitoring and troubleshooting Amazon EMR clusters Demo: Reviewing Apache Spark cluster history Module 7: Designing Batch Data Analytics Solutions Batch data analytics use cases Activity: Designing a batch data analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures

Duration 2 Days 12 CPD hours This course is intended for This course assumes that you have successfully completed the Administering BIG-IP course, or equivalent, and have hands-on experience working in a production BIG-IP environment for several months. You should have a solid understanding of the environment in which the BIG-IP is deployed. This course is meant for BIG-IP administrators, network engineers, applications engineers, etc., who will be responsible for troubleshooting problems associated with their BIG-IP system. This course gives networking professionals hands-on knowledge of how to troubleshoot a BIG-IP system using a number of troubleshooting techniques as well as troubleshooting and system tools. This course includes lectures, labs, and discussions. Module 1: Setting Up the BIG-IP System Introducing the BIG-IP System Initially Setting Up the BIG-IP System Archiving the BIG-IP System Configuration Module 2: Reviewing Local Traffic Configuration Reviewing Nodes, Pools, and Virtual Servers Reviewing Address Translation Reviewing Routing Assumptions Reviewing Application Health Monitoring Reviewing Traffic Behavior Modification with Profiles Reviewing the TMOS Shell (TMSH) Reviewing Managing BIG-IP Configuration Data Reviewing High Availability (HA) Module 3: Troubleshooting Methodology Step-By-Step Process Step 1: State the Problem Step 2: Specify the Problem Step 3: Map the System Step 4: Develop Possible Causes Step 5: Test Theories Step 6: Iterate Until Root Cause Identified Documenting a Problem Putting Troubleshooting Steps to Use Module 4: Working with F5 Support Leveraging F5 Support Resources AskF5.com DevCentral iHealth Leveraging F5 Labs Working with F5 Technical Support Running End User Diagnostics (EUD) - Hardware Only New Platform Diagnostic Tools Always-On Management (AOM) Subsystem Requesting Return Materials Authorization F5?s Software Version Policy Managing the BIG-IP License for Upgrades Managing BIG-IP Disk Space Upgrading BIG-IP Software Module 5: Troubleshooting ? Bottom to Top Introducing Differences between BIG-IP and LINUX Tools Troubleshooting with Layer 1/Layer 2 Tools Troubleshooting with Layer 2/Layer 3 Tools Troubleshooting with Layer 3 Tools Troubleshooting with LINUX Tools Troubleshooting Memory and CPU Troubleshooting with watch Troubleshooting with Additional tmsh commands Module 6: Troubleshooting Tools tcpdump Wireshark ssldump Fiddler diff KDiff3 cURL Module 7: Using System Logs Configuring Logging Log Files Understanding BIG-IP Daemons Functions Triggering an iRule Deploying and Testing iRules Application Visibility and Reporting Module 8: Troubleshooting Lab Projects Network Configurations for Project Additional course details: Nexus Humans F5 Networks Troubleshooting BIG-IP 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 F5 Networks Troubleshooting BIG-IP 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 4 Days 24 CPD hours This course is intended for This course is best suited to systems administrators and IT managers. Overview Skills gained in this training include:Determining the correct hardware and infrastructure for your clusterProper cluster configuration and deployment to integrate with the data centerConfiguring the FairScheduler to provide service-level agreements for multiple users of a clusterBest practices for preparing and maintaining Apache Hadoop in productionTroubleshooting, diagnosing, tuning, and solving Hadoop issues Cloudera University?s four-day administrator training course for Apache Hadoop provides participants with a comprehensive understanding of all the steps necessary to operate and maintain a Hadoop cluster. The Case for Apache Hadoop Why Hadoop? Core Hadoop Components Fundamental Concepts HDFS HDFS Features Writing and Reading Files NameNode Memory Considerations Overview of HDFS Security Using the Namenode Web UI Using the Hadoop File Shell Getting Data into HDFS Ingesting Data from External Sources with Flume Ingesting Data from Relational Databases with Sqoop REST Interfaces Best Practices for Importing Data YARN & MapReduce What Is MapReduce? Basic MapReduce Concepts YARN Cluster Architecture Resource Allocation Failure Recovery Using the YARN Web UI MapReduce Version 1 Planning Your Hadoop Cluster General Planning Considerations Choosing the Right Hardware Network Considerations Configuring Nodes Planning for Cluster Management Hadoop Installation and Initial Configuration Deployment Types Installing Hadoop Specifying the Hadoop Configuration Performing Initial HDFS Configuration Performing Initial YARN and MapReduce Configuration Hadoop Logging Installing and Configuring Hive, Impala, and Pig Hive Impala Pig Hadoop Clients What is a Hadoop Client? Installing and Configuring Hadoop Clients Installing and Configuring Hue Hue Authentication and Authorization Cloudera Manager The Motivation for Cloudera Manager Cloudera Manager Features Express and Enterprise Versions Cloudera Manager Topology Installing Cloudera Manager Installing Hadoop Using Cloudera Manager Performing Basic Administration Tasks Using Cloudera Manager Advanced Cluster Configuration Advanced Configuration Parameters Configuring Hadoop Ports Explicitly Including and Excluding Hosts Configuring HDFS for Rack Awareness Configuring HDFS High Availability Hadoop Security Why Hadoop Security Is Important Hadoop?s Security System Concepts What Kerberos Is and How it Works Securing a Hadoop Cluster with Kerberos Managing and Scheduling Jobs Managing Running Jobs Scheduling Hadoop Jobs Configuring the FairScheduler Impala Query Scheduling Cluster Maintainence Checking HDFS Status Copying Data Between Clusters Adding and Removing Cluster Nodes Rebalancing the Cluster Cluster Upgrading Cluster Monitoring & Troubleshooting General System Monitoring Monitoring Hadoop Clusters Common Troubleshooting Hadoop Clusters Common Misconfigurations Additional course details: Nexus Humans Cloudera Administrator Training for Apache Hadoop 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 Cloudera Administrator Training for Apache Hadoop course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This class is intended for the following participants: Cloud architects, administrators, and SysOps/DevOps personnel Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform. Overview This course teaches participants the following skills: Understand how software containers work Understand the architecture of Kubernetes Understand the architecture of Google Cloud Platform Understand how pod networking works in Kubernetes Engine Create and manage Kubernetes Engine clusters using the GCP Console and gcloud/ kubectl commands Launch, roll back and expose jobs in Kubernetes Manage access control using Kubernetes RBAC and Google Cloud IAM Managing pod security policies and network policies Using Secrets and ConfigMaps to isolate security credentials and configuration artifacts Understand GCP choices for managed storage services Monitor applications running in Kubernetes Engine This class introduces participants to deploying and managing containerized applications on Google Kubernetes Engine (GKE) and the other services provided by Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as pods, containers, deployments, and services; as well as networks and application services. This course also covers deploying practical solutions including security and access management, resource management, and resource monitoring. Introduction to Google Cloud Platform Use the Google Cloud Platform Console Use Cloud Shell Define cloud computing Identify GCPs compute services Understand regions and zones Understand the cloud resource hierarchy Administer your GCP resources Containers and Kubernetes in GCP Create a container using Cloud Build Store a container in Container Registry Understand the relationship between Kubernetes and Google Kubernetes Engine (GKE) Understand how to choose among GCP compute platforms Kubernetes Architecture Understand the architecture of Kubernetes: pods, namespaces Understand the control-plane components of Kubernetes Create container images using Google Cloud Build Store container images in Google Container Registry Create a Kubernetes Engine cluster Kubernetes Operations Work with the kubectl command Inspect the cluster and Pods View a Pods console output Sign in to a Pod interactively Deployments, Jobs, and Scaling Create and use Deployments Create and run Jobs and CronJobs Scale clusters manually and automatically Configure Node and Pod affinity Get software into your cluster with Helm charts and Kubernetes Marketplace GKE Networking Create Services to expose applications that are running within Pods Use load balancers to expose Services to external clients Create Ingress resources for HTTP(S) load balancing Leverage container-native load balancing to improve Pod load balancing Define Kubernetes network policies to allow and block traffic to pods Persistent Data and Storage Use Secrets to isolate security credentials Use ConfigMaps to isolate configuration artifacts Push out and roll back updates to Secrets and ConfigMaps Configure Persistent Storage Volumes for Kubernetes Pods Use StatefulSets to ensure that claims on persistent storage volumes persist across restarts Access Control and Security in Kubernetes and Kubernetes Engine Understand Kubernetes authentication and authorization Define Kubernetes RBAC roles and role bindings for accessing resources in namespaces Define Kubernetes RBAC cluster roles and cluster role bindings for accessing cluster-scoped resources Define Kubernetes pod security policies Understand the structure of GCP IAM Define IAM roles and policies for Kubernetes Engine cluster administration Logging and Monitoring Use Stackdriver to monitor and manage availability and performance Locate and inspect Kubernetes logs Create probes for wellness checks on live applications Using GCP Managed Storage Services from Kubernetes Applications Understand pros and cons for using a managed storage service versus self-managed containerized storage Enable applications running in GKE to access GCP storage services Understand use cases for Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Bigtable, Cloud Firestore, and Bigquery from within a Kubernetes application

Duration 3 Days 18 CPD hours This course is intended for Cloud Solutions Architects, DevOps Engineers. Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with a focus on Google Compute Engine. Overview Configure VPC networks and virtual machines Administer Identity and Access Management for resources Implement data storage services in GCP Manage and examine billing of GCP resources Monitor resources using Stackdriver services Connect your infrastructure to GCP Configure load balancers and autoscaling for VM instances Automate the deployment of GCP infrastructure services Leverage managed services in GCP This class introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud Platform, with a focus on Compute Engine. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems, and application services. This course also covers deploying practical solutions including securely interconnecting networks, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring. Introduction to Google Cloud Platform List the different ways of interacting with GCP Use the GCP Console and Cloud Shell Create Cloud Storage buckets Use the GCP Marketplace to deploy solutions Virtual Networks List the VPC objects in GCP Differentiate between the different types of VPC networks Implement VPC networks and firewall rules Design a maintenance server Virtual Machines Recall the CPU and memory options for virtual machines Describe the disk options for virtual machines Explain VM pricing and discounts Use Compute Engine to create and customize VM instances Cloud IAM Describe the Cloud IAM resource hierarchy Explain the different types of IAM roles Recall the different types of IAM members Implement access control for resources using Cloud IAM Storage and Database Services Differentiate between Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Firestore and Cloud Bigtable Choose a data storage service based on your requirements Implement data storage services Resource Management Describe the cloud resource manager hierarchy Recognize how quotas protect GCP customers Use labels to organize resources Explain the behavior of budget alerts in GCP Examine billing data with BigQuery Resource Monitoring Describe the Stackdriver services for monitoring, logging, error reporting, tracing, and debugging Create charts, alerts, and uptime checks for resources with Stackdriver Monitoring Use Stackdriver Debugger to identify and fix errors Interconnecting Networks Recall the GCP interconnect and peering services available to connect your infrastructure to GCP Determine which GCP interconnect or peering service to use in specific circumstances Create and configure VPN gateways Recall when to use Shared VPC and when to use VPC Network Peering Load Balancing and Autoscaling Recall the various load balancing services Determine which GCP load balancer to use in specific circumstances Describe autoscaling behavior Configure load balancers and autoscaling Infrastructure Automation Automate the deployment of GCP services using Deployment Manager or Terraform Outline the GCP Marketplace Managed Services Describe the managed services for data processing in GCP Additional course details: Nexus Humans Architecting with Google Compute Engine 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 Architecting with Google Compute Engine course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 2 Days 12 CPD hours This course is intended for Experienced system administrators, system engineers, and system integrators. Overview Configure and manage VMware ESXi? networking and storage for a large and sophisticated enterprise Use VMware vSphere© Client?, VMware vSphere© Web Client, and VMware vSphere© ESXi? Shell to manage vSphere Use VMware vSphere© Auto Deploy? and host profiles to provision ESXi hosts Optimize the performance of all vSphere components Use VMware vRealize© Log Insight? to monitor system logs Deploy VMware vCenter© Server Appliance? to be highly available and optimized for performance Migrate a Windows vCenter Server system to vCenter Server Appliance 6.5 Harden the vSphere environment against security threats Encrypt virtual machines for additional security This advanced course provides students with advanced knowledge of configuring and operating a highly available and scalable virtual infrastructure. Course Introduction Introductions and course logistics Course objectives Identify additional resources for after this course Identify other VMware Education offerings Describe the user interfaces available in vSphere 6.5 Network Scalability Configure and manage vSphere distributed switches Explain distributed switch features such as port mirroring, LACP, QoS tagging, and NetFlow Storage Scalability Explain VMware vSphere© Storage APIs - Array Integration and VMware vSphere© API for Storage Awareness? Configure and assign virtual machine storage policies Configure VMware vSphere© Storage DRS? and VMware vSphere© Storage I/O Control Create and use virtual volumes in vSphere Host and Management Scalability Explain the uses of VMware vCenter© Converter? Define and use content libraries Describe and use host profiles Describe and use VMware vSphere© ESXi? Image Builder CLI and vSphere Auto Deploy CPU Optimization Explain the CPU scheduler operation, NUMA support, and other features that affect CPU performance Use esxtop to monitor key CPU performance metrics Memory Optimization Explain ballooning, memory compression, and host-swapping techniques for memory reclamation when memory is overcommitted Use esxtop to monitor key memory performance metrics Storage Optimization Describe storage queue types and other factors that affect storage performance Use esxtop to monitor key storage performance metrics 8 Network Optimization Network Optimization Explain the performance features of network adapters Explain the performance features of vSphere networking Use esxtop to monitor key network performance metrics Analyzing vSphere Explain how Proactive DRS enhances virtual machine availability Use vRealize Log Insight to identify and troubleshoot issues vCenter Server Availability and Performance Describe the high availability options for vCenter Server and VMware Platform Services Controller? Describe and use VMware vCenter Server© High Availability Identify the factors that influence vCenter Server performance Migrate a Windows vCenter Server 5.5 system to vCenter Server Appliance 6.5 vSphere Security Configure ESXi host access and authorization Secure ESXi, vCenter Server, and virtual machines Use VMware Certificate Authority to configure vSphere certificate management Configure vSphere to encrypt virtual machines, core dumps Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware vSphere 6.5 Optimize and Upgrade 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 vSphere 6.5 Optimize and Upgrade course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 2 Days 12 CPD hours This course is intended for This introductory-level course is intended for Business Analysts and Data Analysts (or anyone else in the data science realm) who are already comfortable working with numerical data in Excel or other spreadsheet environments. No prior programming experience is required, and a browser is the only tool necessary for the course. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Throughout the hands-on course students, will learn to leverage Python scripting for data science (to a basic level) using the most current and efficient skills and techniques. Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore (to a basic level): How to work with Python interactively in web notebooks The essentials of Python scripting Key concepts necessary to enter the world of Data Science via Python This course introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it?s often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice. An Overview of Python Why Python? Python in the Shell Python in Web Notebooks (iPython, Jupyter, Zeppelin) Demo: Python, Notebooks, and Data Science Getting Started Using variables Builtin functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control White space Conditional expressions Relational and Boolean operators While loops Alternate loop exits Sequences, Arrays, Dictionaries and Sets About sequences Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions Generator Expressions Nested sequences Working with Dictionaries Working with Sets Working with files File overview Opening a text file Reading a text file Writing to a text file Reading and writing raw (binary) data Functions Defining functions Parameters Global and local scope Nested functions Returning values Essential Demos Sorting Exceptions Importing Modules Classes Regular Expressions The standard library Math functions The string module Dates and times Working with dates and times Translating timestamps Parsing dates from text Formatting dates Calendar data Python and Data Science Data Science Essentials Pandas Overview NumPy Overview SciKit Overview MatPlotLib Overview Working with Python in Data Science Additional course details: Nexus Humans Python for Data Science: Hands-on Technical Overview (TTPS4873) 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 Python for Data Science: Hands-on Technical Overview (TTPS4873) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is for Azure Administrators who migrate and manage SAP solutions on Azure. Azure Administrators manage the cloud services that span storage, networking, and compute cloud capabilities, with a deep understanding of each service across the full IT lifecycle. They take end-user requests for new cloud applications and make recommendations on services to use for optimal performance and scale, as well as provision, size, monitor and adjust as appropriate. This role requires communicating and coordinating with vendors. Azure Administrators use the Azure Portal and as they become more proficient they use PowerShell and the Command Line Interface. Overview After completing this course, students will be able to: Migrate and SAP HANA, S/4HANA, SAP NetWeaver to Azure Leverage Azure Portal, Cloud Shell, Azure PowerShell, CLI, and Resource Manager Use intersite connectivity features including VNet Peering and VNet-to-VNet connections Work with Azure Active Directory (AAD) and Azure AD Connect As an IT Professionals experienced in SAP solutions, you will discover how to leverage Azure resources that include deployment and configuration of virtual machines, virtual networks, storage accounts, and Azure AD that includes implementing and managing hybrid identities. You will also be introduced to concepts, scenarios, procedures, and hands-on labs that will empower you to best plan and implement migration and operation of an SAP solution on Azure. You will also receive guidance on subscriptions, create and scale virtual machines, implement storage solutions, configure virtual networking, back up and share data, connect Azure and on-premises sites, manage network traffic, implement Azure Active Directory, secure identities, and monitor your solution. Introduction Contains an overview of the SAP and Microsoft partnership. Foundations of SAP on Azure Contains brief lessons on Azure compute, Azure storage, Azure networking, SAP HANA for Azure (Large Instances), identity services, governance and manageability, backup and data protection services, and migration services. SAP Certified Offerings on Azure Contains lessons on general prerequisites (SAP support in public cloud environments), deployment options of Azure for SAP workloads, SAP product-specific support for Azure, operating System support of Azure for SAP workloads, storage support of Azure for SAP workloads, networking support for SAP, database support for SAP, high availability and disaster recovery support for SAP, and monitoring requirements for SAP. Lab : Online Lab: Implementing Linux clustering on Azure VMs Lab : Online Lab: Implementing Windows clustering on Azure VMs SAP on Azure Reference Architecture Contains lessons on SAP NetWeaver with AnyDB, SAP S4 HANA, and SAP HANA on Azure (Large Instances) on Azure VMs. Planning for Implementing SAP Solutions on Azure Contains lessons on Azure VM compute, network, and storage considerations. As well as Azure VM high availability and disaster recovery, Azure VM backup considerations, Azure VM monitoring considerations, Azure VM security considerations, and Azure VM authentication and access control considerations. Planning for Migrating SAP Workloads to Azure Contains lessons on strategies for migrating SAP systems to Microsoft Azure and SAP a workload planning and deployment checklist. Implementing Azure VM-based SAP Solutions Contains lessons on Azure VM deployment methodologies, single-instance implementations (2-tier or 3-tier), implementing HA SAP NetWeaver with AnyDB on Azure VMs, implementing HA SAP HANA on Azure VMs, configure the Azure Enhanced Monitoring Extension for SAP, and implementing AD and Azure AD-based authentication. Module 8-Deploying HANA Large Instances (HLI) Contains a lesson on implementing HANA Large Instances (HLI). Migrating SAP Workloads to Azure Contains lessons on migration options, DMO methodologies, cloud migration options, and Very Large Database Migration to Azure. Lab : Online Lab-Implement SAP architecture on Azure VMs running Linux Lab : Online Lab-Implement SAP architecture on Azure VMs running Windows Maintaining SAP on Azure Contains lessons on, remote management, performing backups and restores, OS and workload updates, vertical and horizontal scaling, and Disaster Recovery (DR). Monitoring and Troubleshooting SAP on Azure Contains lessons on monitoring Azure VMs, monitoring SAP HANA on Azure (Large Instances), and integrating SAP solutions with Microsoft cloud services.

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