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20727 Courses

Google Cloud Fundamentals for Azure Professionals

By Nexus Human

Duration 1 Days 6 CPD hours This course is intended for This course is intended for the following participants: Individuals planning to deploy applications and create application environments on Google Cloud Platform Developers, systems operations professionals, and solution architects getting started with Google Cloud Platform Executives and business decision makers evaluating the potential of Google Cloud Platform to address their business needs. Overview This course teaches participants the following skills: Identify Google Cloud counterparts for Azure IaaS, Azure PaaS, Azure SQL, Azure Blob Storage, Azure Application Insights, and Azure Data Lake Configure accounts, billing, projects, networks, subnets, firewalls, VMs, disks, auto scaling, load balancing,storage, databases, IAM, and more Manage and monitor applications Explain feature and pricing model differences This 1-day instructor led course introduces Azure professionals to the core capabilities of Google Cloud in the four technology pillars: networking, compute, storage, and database. It is designed for Azure system administrators, Solution Architects and SysOps Administrators familiar with Azure features and setup; and want to gain experience configuring Google Cloud products immediately. With presentations, demos, and hands-on labs, participants get details of similarities, differences, and initial how-tos quickly. Introducing Google Cloud Explain the advantages of Google Cloud. Define the components of Google's network infrastructure, including: Points of presence, data centers, regions, and zones. Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS). Getting Started with Google Cloud Identify the purpose of projects on Google Cloud. Understand how Azure's resource hierarchy differs from Google Cloud's Understand the purpose of and use cases for Identity and Access Management. Understand how Azure AD differs from Google Cloud IAM. List the methods of interacting with Google Cloud. Launch a solution using Cloud Marketplace. Virtual Machines in the Cloud Identify the purpose and use cases for Google Compute Engine Understand the basics of networking in Google Cloud. Understand how Azure VPC differs from Google VPC. Understand the similarities and differences between Azure VM and Google Compute Engine. Understand how typical approaches to load-balancing in Google Cloud differ from those in Azure. Deploy applications using Google Compute Engine Storage in the Cloud Understand the purpose of and use cases for: Cloud Storage, Cloud SQL, Cloud Bigtable and Cloud Datastore. Understand how Azure Blob compares to Cloud Storage. Compare Google Cloud?s managed database services with Azure SQL. Learn how to choose among the various storage options on Google Cloud. Load data from Cloud Storage into BigQuery Containers in the Cloud Define the concept of a container and identify uses for containers. Identify the purpose of and use cases for Google Container Engine and Kubernetes. Understand how Azure Kubernetes Service differs from from Google Kubernetes Engine. Provision a Kubernetes cluster using Kubernetes Engine. Deploy and manage Docker containers using kubectl Applications in the Cloud Understand the purpose of and use cases for Google App Engine. Contrast the App Engine Standard environment with the App Engine Flexible environment. Understand how App Engine differs from Azure App Service. Understand the purpose of and use cases for Google Cloud Endpoints. Developing, Deploying and Monitoring in the Cloud Understand options for software developers to host their source code. Understand the purpose of template-based creation and management of resources. Understand how Google Cloud Deployment Manager differs from Azure Resource Manager. Understand the purpose of integrated monitoring, alerting, and debugging Understand how Google Monitoring differs from Azure Application Insights and Azure Log Analytics. Create a Deployment Manager deployment. Update a Deployment Manager deployment. View the load on a VM instance using Google Monitoring. Big Data and Machine Learning in the Cloud Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms. Understand how Google Cloud BigQuery differs from Azure Data Lake. Understand how Google Cloud Pub/Sub differs from Azure Event Hubs and Service Bus. Understand how Google Cloud?s machine-learning APIs differ from Azure's. Load data into BigQuery from Cloud Storage. Perform queries using BigQuery to gain insight into data Summary and Review Review the products that make up Google Cloud and remember how to choose among them Understand next steps for training and certification Understand, at a high level, the process of migrating from Azure to Google Cloud.

Google Cloud Fundamentals for Azure Professionals
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Google Cloud Fundamentals - Core Infrastructure

By Nexus Human

Duration 1 Days 6 CPD hours This course is intended for Individuals planning to deploy applications and create application environments on Google Cloud. Developers, systems operations professionals, and solution architects getting started with Google Cloud. Executives and business decision makers evaluating the potential of Google Cloud to address their business needs. Overview Identify the purpose and value of Google Cloud products and services. Interact with Google Cloud services. Describe ways in which customers have used Google Cloud. Choose among and use application deployment environments on Google Cloud: App Engine, Google Kubernetes Engine, and Compute Engine. Choose among and use Google Cloud storage options: Cloud Storage, Cloud SQL, Cloud Bigtable, and Firestore. Make basic use of BigQuery, Google's managed data warehouse for analytics. This course uses lectures, demos, and hands-on labs to give you an overview of Google Cloud products and services so that you can learn the value of Google Cloud and how to incorporate cloud-based solutions into your business strategies. Introducing Google Cloud Platform Explain the advantages of Google Cloud Platform. Define the components of Google's network infrastructure, including: Points of presence, data centers, regions, and zones. Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS). Getting Started with Google Cloud Platform Identify the purpose of projects on Google Cloud Platform. Understand the purpose of and use cases for Identity and Access Management. List the methods of interacting with Google Cloud Platform. Lab: Getting Started with Google Cloud Platform. Google Compute Engine and Networking Identify the purpose of and use cases for Google Compute Engine. Understand the basics of networking in Google Cloud Platform. Lab: Deploying Applications Using Google Compute Engine. Google Cloud Platform Storage Options Understand the purpose of and use cases for: Google Cloud Storage, Google Cloud SQL, and Google Cloud Bigtable. Learn how to choose between the various storage options on Google Cloud Platform. Lab: Integrating Applications with Google Cloud Storage. Google Container Engine Define the concept of a container and identify uses for containers. Identify the purpose of and use cases for Google Container Engine and Kubernetes. Introduction to Hybrid and Multi-Cloud computing (Anthos). Lab: Deploying Applications Using Google Container Engine. Google App Engine and Google Cloud Datastore Understand the purpose of and use cases for Google App Engine and Google Cloud Datastore. Contrast the App Engine Standard environment with the App Engine Flexible environment. Understand the purpose of and use cases for Google Cloud Endpoints. Lab: Deploying Applications Using App Engine and Cloud Datastore. Deployment and Monitoring Understand the purpose of template-based creation and management of resources. Understand the purpose of integrated monitoring, alerting, and debugging. Lab: Getting Started with Stackdriver and Deployment Manager. Big Data and Machine Learning Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms. Lab: Getting Started with BigQuery. Summary and Review Summary and Review. What's Next?.

Google Cloud Fundamentals - Core Infrastructure
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F5 Networks Configuring BIG-IQ

By Nexus Human

Duration 2 Days 12 CPD hours This course is intended for This course is intended for system and network administrators or operators responsible for the installation, setup, configuration, and administration of the BIG-IQ system or management of BIG-IP devices and F5 products running on those devices. This course uses lectures and hands-on exercises to give participants real-time experience in configuring and using the BIG-IQ© product. Students are introduced to BIG-IQ, its interface, and its various functionality. We first look at administering and operating the BIG-IQ system itself, then detail how it is used to remotely manage BIG-IP devices running BIG-IP Local Traffic Manager (LTM). We then look configuring a BIG-IQ Data Collection Device (DCD) system and see how it is used for the remote storage and examination of BIG-IP log events and statistics. Module 1: BIG-IQ Overview BIG-IQ Centralized Management BIG-IQ Components BIG-IQ Core Functionality REST API BIG-IQ Data Collection Device (DCD) BIG-IP Cloud Edition (CE) Setting up the BIG-IQ System Module 2: Administering the BIG-IQ System Controlling Access to the BIG-IQ Creating, Authenticating, Configuring Users Backups Local Host Settings Configuring DNS, NTP, and SMTP Monitoring BIG-IQ, DCD, and BIG-IP Events with Alerts Monitoring BIG-IQ with iHealth Post Installation Issues; Licensing, Changing Management IP, Master Key, Restoring Backups Module 3: Managing BIG-IP LTM Devices BIG-IP LTM Device Discovery BIG-IP Device Backup Deploying to BIG-IP Devices Deployment and Deployment Logs Configuration Snapshots Managing BIG-IP Certificates Managing BIG-IP Licenses Monitoring BIG-IP Devices with iHealth Management of QKView Reports from Managed BIG-IP Devices Module 4: Setting Up the BIG-IQ Data Collection Device Custom Roles Types and Groups Setting up User Accounts with custom roles and privileges Managing BIG-IP DSC Discovery and management of BIG-IP Device Clusters (DSC) with BIG-IQ Administering BIG-IQ High Availability Configuration and management of BIG-IQ systems in a High Availability pair

F5 Networks Configuring BIG-IQ
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VMware NSX-T Data Center: Design [V3.2]

By Nexus Human

Duration 5 Days 30 CPD hours This course is intended for Network and security architects and consultants who design the enterprise and data center networks and VMware NSX environments Overview By the end of the course, you should be able to meet the following objectives: Describe and apply a design framework Apply a design process for gathering requirements, constraints, assumptions, and risks Design a VMware vSphere virtual data center to support NSX-T Data Center requirements Create a VMware NSX Manager™ cluster design Create a VMware NSX Edge™ cluster design to support traffic and service requirements in NSX-T Data Center Design logical switching and routing Recognize NSX-T Data Center security best practices Design logical network services Design a physical network to support network virtualization in a software-defined data center Create a design to support the NSX-T Data Center infrastructure across multiple sites Describe the factors that drive performance in NSX-T Data Center This five-day course provides comprehensive training on considerations and practices to design a VMware NSX-T? Data Center environment as part of a software-defined data center strategy. This course prepares the student with the skills to lead the design of NSX-T Data Center offered in release 3.2, including design principles, processes, and frameworks. The student gains a deeper understanding of the NSX-T Data Center architecture and how it can be used to create solutions to address the customer?s business needs. Course Introduction Introduction and course logistics Course objectives Design Concepts Identify design terms Describe framework and project methodology Describe VMware Validated Design? Identify customers? requirements, assumptions, constraints, and risks Explain the conceptual design Explain the logical design Explain the physical design NSX Architecture and Components Recognize the main elements in the NSX-T Data Center architecture Describe the NSX management cluster and the management plane Identify the functions and components of management, control, and data planes Describe the NSX Manager sizing options Recognize the justification and implication of NSX manager cluster design decisions Identify the NSX management cluster design options NSX Edge Design Explain the leading practices for edge design Describe the NSX Edge VM reference designs Describe the bare-metal NSX Edge reference designs Explain the leading practices for edge cluster design Explain the effect of stateful services placement Explain the growth patterns for edge clusters Identify design considerations when using L2 bridging services NSX Logical Switching Design Describe concepts and terminology in logical switching Identify segment and transport zone design considerations Identify virtual switch design considerations Identify uplink profile, VMware vSphere© Network I/O Control profile, and transport node profile design considerations Identify Geneve tunneling design considerations Identify BUM replication mode design considerations NSX Logical Routing Design Explain the function and features of logical routing Describe NSX-T Data Center single-tier and multitier routing architectures Identify guidelines when selecting a routing topology Describe the BGP and OSPF routing protocol configuration options Explain gateway high availability modes of operation and failure detection mechanisms Identify how multitier architectures provide control over stateful service location Identify VRF Lite requirements and considerations Identify the typical NSX scalable architectures NSX Security Design Identify different security features available in NSX-T Data Center Describe the advantages of an NSX Distributed Firewall Describe the use of NSX Gateway Firewall as a perimeter firewall and as an intertenant firewall Determine a security policy methodology Recognize the NSX-T Data Center security best practices NSX Network Services Identify the stateful services available in different edge cluster high availability modes Describe failover detection mechanisms Explain the design considerations for integrating VMware NSX© Advanced Load Balancer? with NSX-T Data Center Describe stateful and stateless NSX-T Data Center NAT Identify benefits of NSX-T Data Center DHCP Identify benefits of metadata proxy Describe IPSec VPN and L2 VPN Physical Infrastructure Design Identify the components of a switch fabric design Assess Layer 2 and Layer 3 switch fabric design implications Review guidelines when designing top-of-rack switches Review options for connecting transport hosts to the switch fabric Describe typical designs for VMware ESXi? compute hypervisors with two pNICs Describe typical designs for ESXi compute hypervisors with four or more pNICs Describe a typical design for a KVM compute hypervisor with two pNICs Differentiate dedicated and collapsed cluster approaches to SDDC design NSX Multilocation Design Explain scale considerations in an NSX-T Data Center multisite design Describe the main components of the NSX Federation architecture Describe the stretched networking capability in Federation Describe stretched security use cases in Federation Compare Federation disaster recovery designs NSX Optimization Describe Geneve Offload Describe the benefits of Receive Side Scaling and Geneve Rx Filters Explain the benefits of SSL Offload Describe the effect of Multi-TEP, MTU size, and NIC speed on throughput Explain the available N-VDS enhanced datapath modes and use cases List the key performance factors for compute nodes and NSX Edge nodes

VMware NSX-T Data Center: Design [V3.2]
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Google Cloud Platform Big Data and Machine Learning Fundamentals

By Nexus Human

Duration 1 Days 6 CPD hours This course is intended for This class is intended for the following: Data analysts, Data scientists, Business analysts getting started with Google Cloud Platform. Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports. Executives and IT decision makers evaluating Google Cloud Platform for use by data scientists. Overview This course teaches students the following skills:Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform.Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.Employ BigQuery and Cloud Datalab to carry out interactive data analysis.Train and use a neural network using TensorFlow.Employ ML APIs.Choose between different data processing products on the Google Cloud Platform. This course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. Introducing Google Cloud Platform Google Platform Fundamentals Overview. Google Cloud Platform Big Data Products. Compute and Storage Fundamentals CPUs on demand (Compute Engine). A global filesystem (Cloud Storage). CloudShell. Lab: Set up a Ingest-Transform-Publish data processing pipeline. Data Analytics on the Cloud Stepping-stones to the cloud. Cloud SQL: your SQL database on the cloud. Lab: Importing data into CloudSQL and running queries. Spark on Dataproc. Lab: Machine Learning Recommendations with Spark on Dataproc. Scaling Data Analysis Fast random access. Datalab. BigQuery. Lab: Build machine learning dataset. Machine Learning Machine Learning with TensorFlow. Lab: Carry out ML with TensorFlow Pre-built models for common needs. Lab: Employ ML APIs. Data Processing Architectures Message-oriented architectures with Pub/Sub. Creating pipelines with Dataflow. Reference architecture for real-time and batch data processing. Summary Why GCP? Where to go from here Additional Resources Additional course details: Nexus Humans Google Cloud Platform Big Data and Machine Learning Fundamentals 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 Google Cloud Platform Big Data and Machine Learning Fundamentals 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.

Google Cloud Platform Big Data and Machine Learning Fundamentals
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Google Cloud Fundamentals for AWS Professionals

By Nexus Human

Duration 1 Days 6 CPD hours This course is intended for This course is intended for the following participants: Individuals planning to deploy applications and create application environments on Google Cloud Developers, systems operations professionals, and solution architects getting started with Google Cloud. Executives and business decision makers evaluating the potential of Google Cloud to address their business needs. Overview This course teaches participants the following skills: Identify Google Cloud counterparts for AWS IaaS, AWS PaaS, AWS SQL, AWS Blob Storage, AWS Application Insights, and AWS Data Lake Configure accounts, billing, projects, networks, subnets, firewalls, VMs, disks, auto scaling, load balancing, storage, databases, IAM, and more Manage and monitor applications Explain feature and pricing model differences This course with labs introduces AWS professionals to the core capabilities of Google Cloud Platform (GCP) in the four technology pillars: networking, compute, storage, and database. It is designed for AWS Solution Architects and SysOps Administrators familiar with AWS features and setup and want to gain experience configuring GCP products immediately. With presentations, demos, and hands-on labs, participants will get details of similarities, differences, and initial how-tos quickly. Introducing Google Cloud Explain the advantages of Google Cloud. Define the components of Google's network infrastructure,including: Points of presence, data centers, regions, and zones. Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) Getting Started with Google Cloud Identify the purpose of projects on Google Cloud Platform. Understand how AWS?s resource hierarchy differs from Google Cloud?s. Understand the purpose of and use cases for Identity and Access Management. Understand how AWS IAM differs from Google Cloud IAM. List the methods of interacting with Google Cloud Platform. Launch a solution using Cloud Marketplace. Virtual Machines in the Cloud Identify the purpose and use cases for Google Compute Engine. Understand the basics of networking in Google Cloud Platform. Understand how Amazon VPC differs from Google VPC. Understand the similarities and differences between Amazon EC2 and Google Compute Engine. Understand how typical approaches to load-balancing in Google Cloud differ from those in AWS. Deploy applications using Google Compute Engine. Storage in the Cloud Understand the purpose of and use cases for: Cloud Storage,Cloud SQL, Cloud Bigtable and Cloud Datastore. Understand how Amazon S3 and Amazon Glacier compare to Cloud Storage. Compare Google Cloud?s managed database services with Amazon RDS and Amazon Aurora. Learn how to choose among the various storage options on Google Cloud Platform. Load data from Cloud Storage into BigQuery. Perform a query on the data in BigQuery. Containers in the Cloud Define the concept of a container and identify uses for containers. Identify the purpose of and use cases for Google Container Engine and Kubernetes. Understand how Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS) differ from GKE. Provision a Kubernetes cluster using Kubernetes Engine. Deploy and manage Docker containers using kubectl Applications in the Cloud Understand the purpose of and use cases for Google App Engine. Contrast the App Engine Standard environment with the App Engine Flexible environment. Understand how App Engine differs from Amazon Elastic Beanstalk. Understand the purpose of and use cases for Google Cloud Endpoints. Developing, Deploying and Monitoring in the Cloud Understand options for software developers to host their source code. Understand the purpose of template-based creation and management of resources. Understand how Cloud Deployment Manager differs from AWS CloudFormation. Understand the purpose of integrated monitoring, alerting, and debugging. Understand how Google Monitoring differs from Amazon CloudWatch and AWS CloudTrail. Create a Deployment Manager deployment. Update a Deployment Manager deployment. View the load on a VM instance using Google Monitoring. Big Data and Machine Learning in the Cloud Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms. Understand how Google Cloud BigQuery differs from AWS Data Lake. Understand how Google Cloud Pub/Sub differs from AWS Event Hubs and Service Bus. Understand how Google Cloud?s machine-learning APIs differ from AWS's. Load data into BigQuery from Cloud Storage. Perform queries using BigQuery to gain insight into data. Summary and Review Review the products that make up Google Cloud and remember how to choose among them Understand next steps for training and certification Understand, at a high level, the process of migrating from AWS to Google Cloud. Additional course details: Nexus Humans Google Cloud Fundamentals for AWS Professionals 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 Google Cloud Fundamentals for AWS Professionals 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.

Google Cloud Fundamentals for AWS Professionals
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Architecting with Google Compute Engine

By Nexus Human

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.

Architecting with Google Compute Engine
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CertNexus Data Ethics for Business Professionals (DEBIZ)

By Nexus Human

Duration 1 Days 6 CPD hours This course is intended for This course is designed for business leaders and decision makers, including C-level executives, project and product managers, HR leaders, Marketing and Sales leaders, and technical sales consultants, who have a vested interest in the representation of ethical values in technology solutions. Other individuals who want to know more about data ethics are also candidates for this course. This course is also designed to assist learners in preparing for the CertNexus DEBIZ™ (Exam DEB-110) credential. The power of extracting value from data utilizing Artificial Intelligence, Data Science and Machine Learning exposes the learning differences between humans and machines. Humans can apply ethical principles throughout the decision-making process to avoid discrimination, societal harm, and marginalization to maintain and even enhance acceptable norms. Machines make decisions autonomously. So how do we train them to apply ethical principles as they learn from decisions they make? This course provides business professionals and consumers of technology core concepts of ethical principles, how they can be applied to emerging data driven technologies and the impact to an organization which ignores ethical use of technology. Introduction to Data Ethics Defining Data Ethics The Case for Data Ethics Identifying Ethical Issues Improving Ethical Data Practices Ethical Principles Ethical Frameworks Data Privacy Accountability Transparency and Explainability Human-Centered Values and Fairness Inclusive Growth, Sustainable Development, and Well-Being Applying Ethical Principles to Emerging Technology Improving Ethical Data Practices Sources of Ethical Risk Mitigating Bias Mitigating Discrimination Safety and Security Mitigating Negative Outputs Data Surveillance Assessing Risk Ethical Risks in sharing data Applying professional critical judgement Business Considerations Data Legislation Impact of Social and Behavioral Effects Trustworthiness Impact on Business Reputation Organizational Values and the Data Value Chain Building a Data Ethics Culture/Code of Ethics Balancing organizational goals with Ethical Practice Additional course details: Nexus Humans CertNexus Data Ethics for Business Professionals (DEBIZ) 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 CertNexus Data Ethics for Business Professionals (DEBIZ) 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.

CertNexus Data Ethics for Business Professionals (DEBIZ)
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Linux Professional Institute Certification (LPIC-1) 102

By Nexus Human

Duration 5 Days 30 CPD hours This course is intended for Linux Professional Institute Certification (LPIC-1) 102 training is suitable for individuals with roles of: System administrator Network administrator Technician DevOps Overview Upon successful completion of this course, students will be able to: customize shell environments to meet users' needs customize existing scripts or write simple new Bash scripts install and configure X11 add, remove, suspend and change user accounts use cron and systemd timers to run jobs at regular intervals and to use at to run jobs at a specific time localize a system in a different language than English properly maintain the system time and synchronize the clock via NTP manage print queues and user print jobs using CUPS and the LPD compatibility interface manage the persistent network configuration of a Linux host configure DNS on a client host review system configuration to ensure host security in accordance with local security policies know how to set up a basic level of host security use public key techniques to secure data and communication. This course prepares students to take the 102 exam of the LPI level 1 certification. Shells and Shell Scripting Customize and use the shell environment Customize or write simple scripts User Interfaces and Desktops Install and configure X11 Graphical Desktops Accessibility Administrative Tasks Manage user and group accounts and related system files Automate system administration tasks by scheduling jobs Localisation and internationalisation Essential System Services Maintain system time System logging Mail Transfer Agent (MTA) basics Manage printers and printing Networking Fundamentals Fundamentals of internet protocols Persistent network configuration Basic network troubleshooting Configure client side DNS Security Perform security administration tasks Setup host security Securing data with encryption Additional course details: Nexus Humans Linux Professional Institute Certification (LPIC-1) 102 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 Linux Professional Institute Certification (LPIC-1) 102 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.

Linux Professional Institute Certification (LPIC-1) 102
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Linux Professional Institute Certification (LPIC-2) 202

By Nexus Human

Duration 5 Days 30 CPD hours This course is intended for Linux Professional Institute Certification (LPIC-2) 202 training is suitable for individuals with roles of: System administrator Network administrator Technician DevOps Overview Upon successful completion of this course, students will be able to: configure BIND to function as an authoritative and as a recursive, caching-only DNS server install and configure a web server install and configure a proxy server, including access policies, authentication and resource usage set up a Samba server for various clients configure a DHCP server configure PAM to support authentication using various available methods perform queries and updates to an LDAP server configure a basic OpenLDAP server including knowledge of LDIF format and essential access controls manage an e-mail server, including the configuration of e-mail aliases, e-mail quotas and virtual e-mail domains configure an FTP server for anonymous downloads and uploads receive security alerts from various sources, install, configure and run intrusion detection systems and apply security patches and bugfixes configure a VPN (Virtual Private Network) and create secure point-to-point or site-to-site connections. This course prepares students to take the 202 exam of the LPI level 2 certification. To gain LPIC-2 certification, an individual should have an active LPIC-1 certification. Domain Name Server Basic DNS server configuration Create and maintain DNS zones Securing a DNS server HTTP Services Basic Apache configuration Apache configuration for HTTPS Implementing Squid as a caching proxy Implementing Nginx as a web server and a reverse proxy File Sharing Samba Server Configuration NFS Server Configuration Network Client Management DHCP configuration PAM authentication LDAP client usage Configuring an OpenLDAP server E-Mail Services Using e-mail servers Managing E-Mail Delivery Managing Mailbox Access System Security Configuring a router Managing FTP servers Secure shell (SSH) Security tasks OpenVPN Additional course details: Nexus Humans Linux Professional Institute Certification (LPIC-2) 202 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 Linux Professional Institute Certification (LPIC-2) 202 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.

Linux Professional Institute Certification  (LPIC-2) 202
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