19799 Disc courses

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

Duration 5 Days 30 CPD hours This course is intended for Network designers Network administrators Network engineers Systems engineers Data center engineers Consulting systems engineers Technical solutions architects Field engineers Cisco integrators and partners Server administrator Network manager Overview After taking this course, you should be able to: Implement routing and switching protocols in Data Center environment Implement overlay networks in data center Introduce high-level Cisco Application Centric Infrastructure (Cisco ACI™) concepts and Cisco Virtual Machine manager (VMM) domain integration Describe Cisco Cloud Service and deployment models Implement Fibre Channel fabric Implement Fibre Channel over Ethernet (FCoE) unified fabric Implement security features in data center Implement software management and infrastructure monitoring Implement Cisco UCS Fabric Interconnect and Server abstraction Implement SAN connectivity for Cisco Unified Computing System™ (Cisco UCS) Describe Cisco HyperFlex™ infrastructure concepts and benefits Implement Cisco automation and scripting tools in data center Evaluate automation and orchestration technologies This course helps you prepare for the CiscoÿCCNPÿData Center and CCIEÿData Center certifications. In this course, you will master the skills and technologies you need to implement data center compute, LAN and SAN infrastructure. You will also learn the essentials of automation and security in data centers. You will gain hands-on experience deploying, securing, operating, and maintaining Cisco data center. Implementing Data Center Switching Protocols* Spanning Tree Protocol Port Channels Overview Implementing First-Hop Redundancy Protocols* Hot Standby Router Protocol (HSRP) Overview Virtual Router Redundancy Protocol (VRRP) Overview Implementing Routing in Data Center* Open Shortest Path First (OSPF) v2 and Open Settlement Protocol (OSP) v3 Border Gateway Protocol Implementing Multicast in Data Center* IP Multicast in Data Center Networks Internet Group Management Protocol (IGMP) and Multicast Listener Discovery (MLD) Implementing Data Center Overlay Protocols Cisco Overlay Transport Virtualization Virtual Extensible LAN Implementing Network Infrastructure Security* User Accounts and Role Based Access Control (RBAC) Authentication, Authorization, and Accounting (AAA) and SSH on Cisco NX-OS Describing Cisco Application-Centric Infrastructure Cisco ACI Overview, Initialization, and Discovery Cisco ACI Management Describing Cisco ACI Building Blocks and VMM Domain Integration Tenant-Based Components Cisco ACI Endpoints and Endpoint Groups (EPG) Describing Packet Flow in Data Center Network* Data Center Traffic Flows Packet Flow in Cisco Nexus Switches Describing Cisco Cloud Service and Deployment Models Cloud Architectures Cloud Deployment Models Describing Data Center Network Infrastructure Management, Maintenance, and Operations* Time Synchronization Network Configuration Management Explaining Cisco Network Assurance Concepts* Need for Network Assurance Cisco Streaming Telemetry Overview Implementing Fibre Channel Fabric Fibre Channel Basics Virtual Storage Area Network (VSAN) Overview Implementing Storage Infrastructure Services Distributed Device Aliases Zoning Implementing FCoE Unified Fabric Fibre Channel over Ethernet Describing FCoE Implementing Storage Infrastructure Security* User Accounts and RBAC Authentication, Authorization, and Accounting Describing Data Center Storage Infrastructure Maintenance and Operations* Time Synchronization Software Installation and Upgrade Describing Cisco UCS Server Form Factors* Cisco UCS B-Series Blade Servers Cisco UCS C-Series Rack Servers Implementing Cisco Unified Computing Network Connectivity Cisco UCS Fabric Interconnect Cisco UCS B-Series Connectivity Implementing Cisco Unified Computing Server Abstraction Identity Abstraction Service Profile Templates Implementing Cisco Unified Computing SAN Connectivity iSCSI Overview Fibre Channel Overview Implementing Unified Computing Security User Accounts and RBAC Options for Authentication Introducing Cisco HyperFlex Systems* Hyper converged and Integrated Systems Overview Cisco HyperFlex Solution Describing Data Center Unified Computing Management, Maintenance, and Operations* Compute Configuration Management Software Updates Implementing Cisco Data Center Automation and Scripting Tools* Cisco NX-OS Additional course details: Nexus Humans Cisco Implementing and Operating Cisco Data Center Core Technologies (DCCOR) v1.2 training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Cisco Implementing and Operating Cisco Data Center Core Technologies (DCCOR) v1.2 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 Anyone who plans to work with Kubernetes at any level or tier of involvement Any company or individual who wants to advance their knowledge of the cloud environment Application Developers Operations Developers IT Directors/Managers Overview All topics required by the CKAD exam, including: Deploy applications to a Kubernetes cluster Pods, ReplicaSets, Deployments, DaemonSets Self-healing and observable applications Multi-container Pod Design Application configuration via Configmaps, Secrets Administrate cluster use for your team A systematic understanding of Kubernetes architecture Troubleshooting and debugging tools Kubernetes networking and services Kubernetes is a Cloud Orchestration Platform providing reliability, replication, and stability while maximizing resource utilization for applications and services. By the conclusion of this hands-on training, you will go back to work with all necessary commands and practical skills to empower your team to succeed, as well as gain knowledge of important concepts like Kubernetes architecture and container orchestration. We prioritize covering all objectives and concepts necessary for passing the Certified Kubernetes Application Developer (CKAD) exam. You will command and configure a high availability Kubernetes environment (and later, build your own!) capable of demonstrating all ?K8s'' features discussed and demonstrated in this course. Your week of intensive, hands-on training will conclude with a mock CKAD exam that matches the real thing. Kubernetes Architecture Components Understand API deprecations Containers Define, build and modify container images Pods Master Services Node Services K8s Services YAML Essentials Creating a K8s Cluster kubectl Commands Kubernetes Resources Kubernetes Namespace Kubernetes Contexts Pods What is a Pod? Create, List, Delete Pods How to Access Running Pods Kubernetes Resources Managing Cloud Resource Consumption Multi-Container Pod Design Security Contexts Init Containers Understand multi-container Pod design patterns (e.g. sidecar, init and others) Pod Wellness Tracking Networking Packet Forwarding ClusterIP and NodePort Services Provide and troubleshoot access to applications via services Ingress Controllers Use Ingress rules to expose applications NetworkPolicy resource Demonstrate basic understanding of NetworkPolicies Network Plugins Defining the Service Mesh Service mesh configuration examples ReplicaSets Services ReplicaSet Function Deploying ReplicaSets Deployments Deployment Object Updating/Rolling Back Deployments Understand Deployments and how to perform rolling updates Deployment Strategies Use Kubernetes primitives to implement common deployment strategies (e.g. blue/green or canary) Scaling ReplicaSets Autoscaling Labels and Annotations Labels Annotations Node Taints and Tolerations Jobs The K8s Job and CronJob Understand Jobs and CronJobs Immediate vs. scheduled internal use Application Configuration Understanding and defining resource requirements, limits and quotas Config Maps Create & consume Secrets Patching Custom Resource Definition Discover and use resources that extend Kubernetes (CRD) Managing ConfigMaps and Secrets as Volumes Storage Static and dynamic persistent volumes via StorageClass K8s volume configuration Utilize persistent and ephemeral volumes Adding persistent storage to containers via persistent volume claims Introduction to Helm Helm Introduction Charts Use the Helm package manager to deploy existing packages Application Security Understand authentication, authorization and admission control Understand ServiceAccounts Understand SecurityContexts Application Observability and Maintenance Use provided tools to monitor Kubernetes applications How to Troubleshoot Kubernetes Basic and Advanced Logging Techniques Utilize container logs Accessing containers with Port-Forward Debugging in Kubernetes Hands on Labs: Define, build and modify container images Deploy Kubernetes using Ansible Isolating Resources with Kubernetes Namespaces Cluster Access with Kubernetes Context Listing Resources with kubectl get Examining Resources with kubectl describe Create and Configure Basic Pods Debugging via kubectl port-forward Imperative vs. Declarative Resource Creation Performing Commands inside a Pod Understanding Labels and Selectors Insert an Annotation Create and Configure a ReplicaSet Writing a Deployment Manifest Perform rolling updates and rollbacks with Deployments Horizontal Scaling with kubectl scale Implement probes and health checks Understanding and defining resource requirements, limits and quotas Understand Jobs and CronJobs Best Practices for Container Customization Persistent Configuration with ConfigMaps Create and Consume Secrets Understand the Init container multi-container Pod design pattern Using PersistentVolumeClaims for Storage Dynamically Provision PersistentVolumes with NFS Deploy a NetworkPolicy Provide and troubleshoot access to applications via services Use Ingress rules to expose applications Understand the Sidecar multi-container Pod design pattern Setting up a single tier service mesh Tainted Nodes and Tolerations Use the Helm package manager to deploy existing packages A Completed Project Install Jenkins Using Helm and Run a Demo Job Custom Resource Definitions (CRDs) Patching Understanding Security Contexts for Cluster Access Control Utilize container logs Advanced Logging Techniques Troubleshooting Calicoctl Deploy a Kubernetes Cluster using Kubeadm Monitoring Applications in Kubernetes Resource-Based Autoscaling Create ServiceAccounts for use with the Kubernetes Dashboard Saving Your Progress With GitHub CKAD Practice Drill Alta Kubernetes Course Specific Updates Sourcing Secrets from HashiCorp Vault Example CKAD Test Questions

Duration 3 Days 18 CPD hours This course is intended for Experienced system administrators or network administrators and security professionals Overview By the end of the course, you should be able to meet the following objectives: Describe NSX Advanced Load Balancer architecture Describe the NSX Advanced Load Balancer components and main functions Explain the NSX Advanced Load Balancer key features and benefits Describe NSX Advanced Load Balancer Web Application Firewall architecture Describe the NSX Advanced Load Balancer Web Application Firewall components and main functions Explain the NSX Advanced Load Balancer Web Application Firewall key features and benefits Explain and configure Local Load Balancing constructors such as Virtual Services, Pools, Health Monitors and related components Understand and modify application behavior leveraging Profiles, Policies and DataScripts Configure and customize the NSX Advanced Load Balancer Web Application Firewall Describe and leverage NSX Advanced Load Balancer REST API interfaces and related automation capabilities Describe and configure NSX Advanced Load Balancer Web Application Firewall application and infrastructure monitoring Gather relevant information and perform basic troubleshooting of Web Application Firewall applications leveraging built-in NSX Advanced Load Balancer tooling This three-day course provides comprehensive training on how to configure, maintain and troubleshoot the Web Application Firewall component of the VMware NSX Advanced Load Balancer (Avi Networks) solution as well as provide an understanding of additional security related functionality. This course covers key NSX Advanced Load Balancer (Avi Networks) Web Application Firewall features and functionality offered in the NSX Advanced Load Balancer 18.2 release, including the overall infrastructure, virtual services and application components as well as application troubleshooting and solution monitoring. Access to a software-defined data center environment is provided through hands-on labs to reinforce the skills and concepts presented in the course. Course Introduction Introductions and course logistics Course objectives Introduction to NSX Advanced Load Balancer Introduce NSX Advanced Load Balancer Discuss NSX Advanced Load Balancer use cases and benefits Explain NSX Advanced Load Balancer architecture and components Explain the management, control, data, and consumption planes and their respective functions Introduction to NSX ALB Web Application Firewall Introduce the NSX Advanced Load Balancer Web Application Firewall Discuss NSX Advanced Load Balancer Web Application Firewall use cases and benefits Virtual Services Configuration Concepts Explain Virtual Service components Explain Virtual Service types Explain and configure basic virtual services components such as Application Profiles, Network Profiles, Pools and Health Monitors Attacking and Defending Web Applications Introduce the processes and methodologies used when attacking and defending web applications Introduce the tools used to attack web applications Explain with examples terminology such as Reflected XSS and SQL injection Profiles and Policies Explain and deep dive on Advanced Virtual Service creation Explain and deep dive on Application Profiles and Types such as L4, DNS, Syslog and HTTP Explain and configure advanced application HTTP Profile options Deep dive on Network Profiles and Types Explain and configure SSL Profiles and Certificates Explain and Configure HTTP and DNS policies DDOS Protection Introduce the NSX Advanced Load Balancer rate limiting functionality Explain the NSX Advanced Load Balancer rate limiting functionality Hands on examples of rate limiting in action Customizing Application Delivery with Datascripts Introduce the concept of datascripts to manipulate data Explain the various components and inspection points IWAF Deep Dive Describe the building blocks of the iWAF implementation Explain the various iWAF components Introduce both Positive and Negative security models Explain the iWAF Policies, profiles and rule sets IWAF Core Rule Set Explain the history and rationale of the core rule set Describe the NSX ALB (Avi) Core Rule Set IWAF Custom Rules Describe the power and complexity available via custom rules Explain the rule language Implement various use cases Explain common errors and possible solutions IWAF Operations Describe the iWAF application onboarding process Tuning the iWAF policies Working with iWAF logs and analytics Explaining false positive mitigation tactics IWAF Best Practices Provide guidance on how to get the best results Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware NSX Advanced Load Balancer: Web Application Firewall Security 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 NSX Advanced Load Balancer: Web Application Firewall Security 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 1 Days 6 CPD hours This course is intended for This introductory-level course is great for experienced technical professionals working in a wide range of industries, such as software development, data science, marketing and advertising, finance, healthcare, and more, who are looking to use the latest AI and machine learning techniques in their day to day. The hands-on labs in this course use Python, so you should have some familiarity with Python scripting basics. Overview Working in an interactive learning environment, led by our engaging OpenAI expert you'll: Understand the capabilities and products offered by OpenAI and how to access them through the OpenAI API. set up an OpenAI environment on Azure, including creating an Azure virtual machine and configuring the environment to connect to Azure resources. Gain hands-on experience building a GPT-3 based chatbot on Azure and implement advanced natural language processing capabilities. Use the OpenAI API to access GPT-3 and generate high-quality text Learn how to use Whisper to improve the quality of text generation. Understand the capabilities of DALL-E and use it to generate images for unique and engaging visuals. Geared for technical professionals, Quick Start to Azure AI Basics for Technical Users is a fun, fast paced course designed to quickly get you up to speed with OpenAI?s powerful tools and functionality, and to provide hands-on experience in setting up an OpenAI environment on Azure. Guided by our AI expert, you?ll explore the capabilities of OpenAI's GPT-3, Whisper and DALL-E, and build a chatbot on Azure. It will provide you with the knowledge and resources to continue your journey in AI and machine learning and have a good understanding of the potential of OpenAI and Azure for your projects. First, you?ll dive into the world of OpenAI, learning about its products and the capabilities they offer. You'll also discover how Azure's offerings for AI and machine learning can complement OpenAI's tools and resources, providing you with a powerful combination for your projects. And don't worry if you're new to Azure, we'll walk you through the process of setting up an account and creating a resource group. As you progress through the course, you'll get the chance to work with OpenAI's GPT-3, one of the most advanced large language models available today. You'll learn how to use the OpenAI API to access GPT-3 and discover how to use it to generate high-quality text quickly and easily. And that's not all, you'll also learn how to build a GPT-3 based chatbot on Azure, giving you the opportunity to implement advanced natural language processing capabilities in your chatbot projects. The course will also cover OpenAI Whisper, an OpenAI tool that can improve the quality of text generation, allowing you to create more coherent and natural language content. And you will learn about OpenAI DALL-E, an OpenAI tool that can generate images, giving you the ability to create unique and engaging visuals to enhance your content and projects. Introduction to OpenAI and Azure Explore OpenAI and its products, as well as Azure's offerings for AI and Machine Learning, allowing you to understand the tools and resources available to you for your AI projects. Explore OpenAI and its products Explore Azure and its offerings for AI and Machine Learning Get Hands-On: Setting up an OpenAI environment on Azure Walk through the process of setting up an OpenAI environment on Azure, giving you the hands-on experience needed to start building your own projects using OpenAI and Azure. Create an Azure virtual machine and installing the OpenAI SDK Configure the OpenAI environment and connecting to Azure resources Explore OpenAI GPT-3 Learn about GPT-3, one of OpenAI's most powerful language models, and how to use it to generate high quality text, giving you the ability to create natural language content quickly and easily. Review GPT-3 and its capabilities Use the OpenAI API to access GPT-3 Get Hands-on: Building a GPT-3 based chatbot on Azure Learn how to build a GPT-3 based chatbot on Azure, giving you the opportunity to learn how to implement advanced natural language processing capabilities in your chatbot projects. Setup an Azure Function and creating a chatbot Integrate GPT-3 with the chatbot OpenAI Whisper Explore Whisper, an OpenAI tool that can improve the quality of text generation, allowing you to create more coherent and natural language content. Explore Whisper and its capabilities Use Whisper to improve the quality of text generation OpenAI DALL-E Explore DALL-E, an OpenAI tool that can generate images, giving you the ability to create unique and engaging visuals to enhance your content and projects. Explore DALL-E and its capabilities Use the OpenAI API to access DALL-E What?s Next: Keep Going! Other ways OpenAI can impact your day to day Explore great places to check for expanded tools and add-ons for Azure OpenAI Where to go for help and support Quick Look at Generative AI and its Business Implications Understanding Generative AI Generative AI in Business Ethical considerations of Generative AI

Duration 5 Days 30 CPD hours This course is intended for Network designers Network administrators Network engineers Systems engineers Data center engineers Consulting systems engineers Technical solutions architects Field engineers Cisco integrators and partners Server administrator Network manager Overview After taking this course, you should be able to: Implement routing and switching protocols in Data Center environment Implement overlay networks in data center Introduce high-level Cisco Application Centric Infrastructure (Cisco ACI™) concepts and Cisco Virtual Machine manager (VMM) domain integration Describe Cisco Cloud Service and deployment models Implement Fibre Channel fabric Implement Fibre Channel over Ethernet (FCoE) unified fabric Implement security features in data center Implement software management and infrastructure monitoring Implement Cisco UCS Fabric Interconnect and Server abstraction Implement SAN connectivity for Cisco Unified Computing System™ (Cisco UCS) Describe Cisco HyperFlex™ infrastructure concepts and benefits Implement Cisco automation and scripting tools in data center Evaluate automation and orchestration technologies The Implementing and Operating Cisco Data Center Core Technologies (DCCOR) v1.1 course helps you prepare for the Cisco© CCNP© Data Center and CCIE© Data Center certifications for advanced-level data center roles. In this course, you will master the skills and technologies you need to implement data center compute, LAN and SAN infrastructure. You will also learn the essentials of automation and security in data centers. You will gain hands-on experience deploying, securing, operating, and maintaining Cisco data center infrastructure including: Cisco MDS Switches and Cisco Nexus Switches; Cisco Unified Computing System? (Cisco UCS©) B-Series Blade Servers, and Cisco UCS C-Series Rack Servers. Implementing Data Center Switching Protocols Spanning Tree Protocol Port Channels Overview Implementing First-Hop Redundancy Protocols Hot Standby Router Protocol (HSRP) Overview Virtual Router Redundancy Protocol (VRRP) Overview Implementing Routing in Data Center Open Shortest Path First (OSPF) v2 and Open Settlement Protocol (OSP) v3 Border Gateway Protocol Implementing Multicast in Data Center IP Multicast in Data Center Networks Internet Group Management Protocol (IGMP) and Multicast Listener Discovery (MLD) Implementing Data Center Overlay Protocols Cisco Overlay Transport Virtualization Virtual Extensible LAN Implementing Network Infrastructure Security User Accounts and Role Based Access Control (RBAC) Authentication, Authorization, and Accounting (AAA) and SSH on Cisco NX-OS Describing Cisco Application-Centric Infrastructure Cisco ACI Overview, Initialization, and Discovery Cisco ACI Management Describing Cisco ACI Building Blocks and VMM Domain Integration Tenant-Based Components Cisco ACI Endpoints and Endpoint Groups (EPG) Describing Packet Flow in Data Center Network Data Center Traffic Flows Packet Flow in Cisco Nexus Switches Describing Cisco Cloud Service and Deployment Models Cloud Architectures Cloud Deployment Models Describing Data Center Network Infrastructure Management, Maintenance, and Operations Time Synchronization Network Configuration Management Explaining Cisco Network Assurance Concepts Need for Network Assurance Cisco Streaming Telemetry Overview Implementing Fibre Channel Fabric Fibre Channel Basics Virtual Storage Area Network (VSAN) Overview Implementing Storage Infrastructure Services Distributed Device Aliases Zoning Implementing FCoE Unified Fabric Fibre Channel over Ethernet Describing FCoE Implementing Storage Infrastructure Security User Accounts and RBAC Authentication, Authorization, and Accounting Describing Data Center Storage Infrastructure Maintenance and Operations Time Synchronization Software Installation and Upgrade Describing Cisco UCS Server Form Factors Cisco UCS B-Series Blade Servers Cisco UCS C-Series Rack Servers Implementing Cisco Unified Computing Network Connectivity Cisco UCS Fabric Interconnect Cisco UCS B-Series Connectivity Implementing Cisco Unified Computing Server Abstraction Identity Abstraction Service Profile Templates Implementing Cisco Unified Computing SAN Connectivity iSCSI Overview Fibre Channel Overview Implementing Unified Computing Security User Accounts and RBAC Options for Authentication Introducing Cisco HyperFlex Systems Hyperconverged and Integrated Systems Overview Cisco HyperFlex Solution Describing Data Center Unified Computing Management, Maintenance, and Operations Compute Configuration Management Software Updates Implementing Cisco Data Center Automation and Scripting Tools Cisco NX-OS Programmability Scheduler Overview Describing Cisco Integration with Automation and Orchestration Software Platforms Cisco and Ansible Integration Overview Cisco and Puppet Integration Overview Describing Cisco Data Center Automation and Orchestration Technologies (Self-study) Power On Auto Provisioning Cisco Data Center Network Manager Overview Additional course details: Nexus Humans Cisco Implementing Cisco Data Center Core Technologies v1.1 (DCCOR) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Cisco Implementing Cisco Data Center Core Technologies v1.1 (DCCOR) 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 1 Days 6 CPD hours This course is intended for This course is designed for a non-technical audience and doesn't require any prior coding or technical experience. The handson exercises will be done using pre-built OpenAI tools and interfaces that are user-friendly and easy to use. Overview Working in an interactive learning environment, led by our engaging expert, you will: Get comfortable with the basics of prompt engineering and discover how it can make a difference in various business tasks, such as enhancing customer support, creating content, and fine-tuning sales pitches. Develop the knack for crafting, refining, and perfecting prompts suited to specific business situations by understanding context, user intent, and what makes a prompt great. Learn how to smoothly incorporate prompt engineering solutions into your existing business workflows, including pinpointing the right processes, integrating with your current software, and keeping data privacy and security in check. Become proficient in advanced techniques and best practices in prompt engineering, like making use of APIs, customizing language models, and collaborating with your teammates across different departments. Keep up with the latest developments in prompt engineering and be ready to adapt to changing business needs and trends, ensuring that you stay relevant and continue to grow in the dynamic business world. Prompt engineering is the process of designing and refining input prompts to get desired output from advanced language models, such as OpenAI Codex or GPT-4. It involves creating effective questions or statements that guide the AI model to generate useful responses for a specific task or purpose, like enhancing customer support, generating content, and fine-tuning sales pitches, making it an essential skill set for a wide range of business applications. Quick Start to Prompt Engineering for Everyday Business Users is a one-day, workshop style hands-on course that where you'll learn how to create effective prompts, integrate prompt engineering solutions into existing workflows, and uncover advanced techniques and best practices. Guided by our engaging, expert instructor, you?ll experiment with innovative tools and develop practical skills that can be immediately applied to a variety of projects. Whether you're aiming to enhance customer interactions, simplify content creation, or refine internal communication, this immersive learning experience will equip you with the knowledge to make a meaningful impact on your organization. Introduction to Prompt Engineering Understand the fundamentals of prompt engineering and its applications in the business world. What is prompt engineering? Importance of prompt engineering in business Key concepts and terminology Examples of prompt engineering in business scenarios Overview of popular prompt engineering tools (e.g., OpenAI Codex, GPT-4) Activity: Hands-on exploration of prompt engineering tools: Participants will engage in a fun scavenger hunt activity, where they will experiment with different prompt engineering tools to answer a set of questions. Developing Effective Prompts Learn how to create and refine prompts for a variety of business applications. Anatomy of a good prompt Understanding context and user intent Techniques for prompt iteration and optimization Generating specific and creative responses Handling sensitive information and biases Activity: Prompt development workshop: Participants will practice developing and refining prompts in a collaborative, game-like environment, where they will compete to create the most effective prompts for given business scenarios. Integrating Prompt Engineering into Business Processes Discover how to incorporate prompt engineering solutions into existing workflows. Identifying business processes that can benefit from prompt engineering Integrating prompt engineering with existing software and tools Evaluating the success and impact of prompt engineering solutions Ensuring data privacy and security Scaling prompt engineering solutions across an organization Activity: Business process integration simulation: Participants will work in teams to create a plan for integrating a prompt engineering solution into a simulated business process, with a focus on creativity and practicality. Advanced Techniques and Best Practices Gain insights into advanced techniques and best practices for prompt engineering in a business context. Leveraging APIs for prompt engineering Customizing and fine-tuning language models Adapting to changing business requirements and trends Collaborating with cross-functional teams Staying up-to-date with prompt engineering advancements Activity: Advanced prompt engineering challenge: Participants will take part in a friendly competition, using advanced techniques to solve complex business-related prompt engineering challenges. Additional course details: Nexus Humans QuickStart to Prompt Engineering for Everyday Business Users (TTAI2009) 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 QuickStart to Prompt Engineering for Everyday Business Users (TTAI2009) 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 intended for: System administrators and operators who are operating in the AWS Cloud Informational technology workers who want to increase the system operations knowledge. Overview In this course, you will learn to: Recognize the AWS services that support the different phases of Operational Excellence, a WellArchitected Framework pillar. Manage access to AWS resources using AWS Accounts and Organizations and AWS Identity and Access Management (IAM). Maintain an inventory of in-use AWS resources using AWS services such as AWS Systems Manager, AWS CloudTrail, and AWS Config. Develop a resource deployment strategy utilizing metadata tags, Amazon Machine Images, and Control tower to deploy and maintain an AWS cloud environment. Automate resource deployment using AWS services such as AWS CloudFormation and AWS Service Catalog. Use AWS services to manage AWS resources through SysOps lifecycle processes such as deployments and patches. Configure a highly available cloud environment that leverages AWS services such as Amazon Route 53 and Elastic Load Balancing to route traffic for optimal latency and performance. Configure AWS Auto Scaling and Amazon Elastic Compute Cloud auto scaling to scale your cloud environment based on demand. Use Amazon CloudWatch and associated features such as alarms, dashboards, and widgets to monitor your cloud environment. Manage permissions and track activity in your cloud environment using AWS services such as AWS CloudTrail and AWS Config. Deploy your resources to an Amazon Virtual Private Cloud (Amazon VPC), establish necessary connectivity to your Amazon VPC, and protect your resources from disruptions of service. State the purpose, benefits, and appropriate use cases for mountable storage in your AWS cloud environment. Explain the operational characteristics of object storage in the AWS cloud, including Amazon Simple Storage Service (Amazon S3) and Amazon S3 Glacier. Build a comprehensive costing model to help gather, optimize, and predict your cloud costs using services such as AWS Cost Explorer and the AWS Cost & Usage Report. This course teaches systems operators and anyone performing system operations functions how to install, configure, automate, monitor, secure, maintain and troubleshoot the services, networks, and systems on AWS necessary to support business applications. The course also covers specific AWS features, tools, andbest practices related to these functions. Module 1: Introduction to System Operations on AWS Systems operations AWS Well-Architected Framework AWS Well-Architected Tool Module 2a: Access Management Access management Resources, accounts, and AWS Organizations Module 2b: System Discovery Methods to interact with AWS services Introduction to monitoring services Tools for automating resource discovery Inventory with AWS Systems Manager and AWS Config Troubleshooting scenario Hands-On Lab: Auditing AWS Resources with AWS Systems Manager and AWS Config Module 3: Deploying and Updating Resources Systems operations in deployments Tagging strategies Deployment using Amazon Machine Images (AMIs) Deployment using AWS Control Tower Troubleshooting scenario Module 4: Automating Resource Deployment Deployment using AWS CloudFormation Deployment using AWS Service Catalog Troubleshooting scenario Hands-On Lab: Infrastructure as Code Module 5: Manage Resources AWS Systems Manager Troubleshooting scenario Hands-On Lab: Operations as Code Module 6a: Configure Highly Available Systems Distributing traffic with Elastic Load Balancing Amazon Route 53 Module 6b: Automate Scaling Scaling with AWS Auto Scaling Scaling with Spot Instances Managing licenses with AWS License Manager Troubleshooting scenario Module 7: Monitor and Maintaining System Health Monitoring and maintaining healthy workloads Monitoring distributed applications Monitoring AWS infrastructure Monitoring your AWS account Troubleshooting scenario Hands-On Lab: Monitoring Applications and Infrastructure Module 8: Data Security and System Auditing Maintain a strong identity and access foundation Implement detection mechanisms Automate incident remediation Troubleshooting scenario Hands-On Lab: Securing the Environment Module 9: Operate Secure and Resilient Networks Building a secure Amazon Virtual Private Cloud (Amazon VPC) Networking beyond the VPC Troubleshooting scenario Module 10a : Mountable Storage Configuring Amazon Elastic Block Storage (Amazon EBS) Sizing Amazon EBS volumes for performance Using Amazon EBS snapshots Using Amazon Data Lifecycle Manager to manage your AWS resources Creating backup and data recovery plans Configuring shared file system storage Module 10b: Object Storage Deploying Amazon Simple Storage Service (Amazon S3) with Access Logs, Cross-Region Replication, and S3 Intelligent-Tiering Hands-On Lab: Automating with AWS Backup for Archiving and Recovery Module 11: Cost Reporting, Alerts, and Optimization Gain AWS expenditure awareness Use control mechanisms for cost management Optimize your AWS spend and usage Hands-On Lab: Capstone lab for SysOps Additional course details: Nexus Humans Systems Operations on AWS 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 Systems Operations on AWS 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 geared for experienced skilled Java developers, software developers, data scientists, machine learning experts or others who wish to transtion their coding skills to Scala, learning how to code in Scala and apply it in a practical way. This is not a basic class. Overview Working in a hands-on learning environment led by our expert instructor you'll: Get comfortable with Scala's core principles and unique features, helping you navigate the language confidently and boosting your programming skills. Discover the power of functional programming and learn techniques that will make your code more efficient, maintainable, and enjoyable to write. Become proficient in creating dynamic web applications using the Play Framework, and easily connect to databases with the user-friendly Slick library. Master concurrency programming with Akka, empowering you to build scalable and fault-tolerant applications that excel in performance. Enhance your testing skills using ScalaTest and ScalaCheck, ensuring the reliability and quality of your Scala applications, while having fun in the process. Explore the fascinating world of generative AI and GPT technologies, and learn how to integrate them into your projects, adding a touch of innovation and intelligence to your Scala solutions. If your team requires different topics, additional skills or a custom approach, our team will collaborate with you to adjust the course to focus on your specific learning objectives and goals. Discover the power of Scala programming in our comprehensive, hands-on technical training course designed specifically for experienced object-oriented (OO) developers. Scala is a versatile programming language that combines the best of both OO and functional programming paradigms, making it ideal for a wide range of projects, from web applications to big data processing and machine learning. By mastering Scala, you'll be able to develop more efficient, scalable, and maintainable applications. Fast Track to Scala Programming for OO / Java Developers is a four day hands-on course covers the core principles of Scala, functional programming, web application development, database connectivity, concurrency programming, testing, and interoperability between Scala and Java. Additionally, you'll explore cutting-edge generative AI and GPT technologies, learning how to integrate them into your Scala applications for intelligent suggestions or automation. Throughout the course you?ll explore the latest tools and best practices in the Scala ecosystem, gaining valuable knowledge and experience that can be directly applied to your day-to-day work. With 50% of the course content dedicated to hands-on labs, you'll gain practical experience applying the concepts you've learned across various projects, such as building functional web applications, connecting to databases, designing modular components, and implementing concurrency. Upon completing the course, you'll have a solid understanding of the language and its features, empowering you to confidently apply your new skills in data science and machine learning projects. You'll exit well-prepared to create efficient, scalable, and maintainable Scala applications, regardless of the complexity of your projects. Introduction to Scala Scala features and benefits Comparing Scala with Java and other OO languages Installing Scala and setting up the development environment Object-Oriented Programming in Scala Classes and objects Traits, mixins, and inheritance Companion objects and factories Encapsulation and polymorphism Functional Programming Basics Pure functions and referential transparency Higher-order functions and currying Immutability and persistent data structures Pattern matching and recursion Having Fun with Functional Data Structures Lists, sets, and maps in Scala Folding and reducing operations Stream processing and lazy evaluation For-comprehensions Building Web Applications in Functional Style Introduction to Play Framework Functional web routing and request handling JSON handling with Play-JSON Middleware and functional composition Connecting to a Database Introduction to Slick library Database configuration and setup Querying and updating with Slick Transactions and error handling Building Scalable and Extensible Components Modular architecture and design patterns Dependency injection with MacWire Type classes and type-level programming Implicit parameters and conversions Concurrency Programming & Akka Introduction to Akka framework and Actor model Actor systems and message passing Futures and Promises Supervision and fault tolerance Building Confidence with Testing Introduction to ScalaTest and ScalaCheck Unit testing and property-based testing Test-driven development in Scala Mocking and integration testing Interoperability between Scala and Java Calling Java code from Scala Using Java libraries in Scala projects Converting Java collections to Scala collections Writing Scala code that can be called from Java Using Generative AI and GPT Technologies in Scala Programming Overview of GPT and generative AI Integrating GPT with Scala applications Use cases and practical examples Additional course details: Nexus Humans Fast Track to Scala Programming Essentials for OO / Java Developers (TTSCL2104) 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 Fast Track to Scala Programming Essentials for OO / Java Developers (TTSCL2104) 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 in an intermediate and beyond-level course is geared for experienced Python developers looking to delve into the exciting field of Natural Language Processing. It is ideally suited for roles such as data analysts, data scientists, machine learning engineers, or anyone working with text data and seeking to extract valuable insights from it. If you're in a role where you're tasked with analyzing customer sentiment, building chatbots, or dealing with large volumes of text data, this course will provide you with practical, hands on skills that you can apply right away. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Master the fundamentals of Natural Language Processing (NLP) and understand how it can help in making sense of text data for valuable insights. Develop the ability to transform raw text into a structured format that machines can understand and analyze. Discover how to collect data from the web and navigate through semi-structured data, opening up a wealth of data sources for your projects. Learn how to implement sentiment analysis and topic modeling to extract meaning from text data and identify trends. Gain proficiency in applying machine learning and deep learning techniques to text data for tasks such as classification and prediction. Learn to analyze text sentiment, train emotion detectors, and interpret the results, providing a way to gauge public opinion or understand customer feedback. The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. Launch into the Universe of Natural Language Processing The journey begins: Unravel the layers of NLP Navigating through the history of NLP Merging paths: Text Analytics and NLP Decoding language: Word Sense Disambiguation and Sentence Boundary Detection First steps towards an NLP Project Unleashing the Power of Feature Extraction Dive into the vast ocean of Data Types Purification process: Cleaning Text Data Excavating knowledge: Extracting features from Texts Drawing connections: Finding Text Similarity through Feature Extraction Engineer Your Text Classifier The new era of Machine Learning and Supervised Learning Architecting a Text Classifier Constructing efficient workflows: Building Pipelines for NLP Projects Ensuring continuity: Saving and Loading Models Master the Art of Web Scraping and API Usage Stepping into the digital world: Introduction to Web Scraping and APIs The great heist: Collecting Data by Scraping Web Pages Navigating through the maze of Semi-Structured Data Unearth Hidden Themes with Topic Modeling Embark on the path of Topic Discovery Decoding algorithms: Understanding Topic-Modeling Algorithms Dialing the right numbers: Key Input Parameters for LSA Topic Modeling Tackling complexity with Hierarchical Dirichlet Process (HDP) Delving Deep into Vector Representations The Geometry of Language: Introduction to Vectors in NLP Text Manipulation: Generation and Summarization Playing the creator: Generating Text with Markov Chains Distilling knowledge: Understanding Text Summarization and Key Input Parameters for TextRank Peering into the future: Recent Developments in Text Generation and Summarization Solving real-world problems: Addressing Challenges in Extractive Summarization Riding the Wave of Sentiment Analysis Unveiling emotions: Introduction to Sentiment Analysis Tools Demystifying the Textblob library Preparing the canvas: Understanding Data for Sentiment Analysis Training your own emotion detectors: Building Sentiment Models Optional: Capstone Project Apply the skills learned throughout the course. Define the problem and gather the data. Conduct exploratory data analysis for text data. Carry out preprocessing and feature extraction. Select and train a model. ? Evaluate the model and interpret the results. Bonus Chapter: Generative AI and NLP Introduction to Generative AI and its role in NLP. Overview of Generative Pretrained Transformer (GPT) models. Using GPT models for text generation and completion. Applying GPT models for improving autocomplete features. Use cases of GPT in question answering systems and chatbots. Bonus Chapter: Advanced Applications of NLP with GPT Fine-tuning GPT models for specific NLP tasks. Using GPT for sentiment analysis and text classification. Role of GPT in Named Entity Recognition (NER). Application of GPT in developing advanced chatbots. Ethics and limitations of GPT and generative AI technologies.