Duration 3 Days 18 CPD hours This course is intended for This course is ideal for developers and engineers including: Cloud administrators Cloud solution architects Customer sales engineers DevOps engineers Sales engineers Systems engineers Technical solutions architects Overview After completing the course, you should be able to: Explain business and technical challenges of going to the cloud Understand benefits of an application-centric hybrid cloud multicloud management platform Navigate Cisco CloudCenter Suite architecture Understand Cisco CloudCenter Suite administrative capabilities including cloud management, multitenancy, governance, and policy enforcement Describe application lifecycle management and provisioning in cloud Describe how to use Cisco CloudCenter Suite to manage the workloads in multicloud The course, Mulitcloud Management with Cisco© CloudCenter Suite (CLDCCS) v1.0 is an intensive training course that teaches you to securely design, automate, and deploy applications across multiple clouds while optimizing cost and compliance with comprehensive reporting, visibility, and policy-enforcement. Through a combination of lessons with hands-on lab exercises, you will learn to simplify the lifecycle management of multicloud applications, workflows, and their infrastructure Understanding Cloud Transitions Overview of Traditional IT Introducing Cisco CloudCenter Suite Cisco CloudCenter Suite Definition Setting Up Cisco CloudCenter Workload Manager Artifact Repository Overview and Configuration Understanding User Administration and Multitenancy in Cisco CloudCenter Suite Cisco CloudCenter Suite User Roles Grasping Application Modeling in Cisco CloudCenter Workload Manager Model an Application Identifying Resource Placement Callouts and Lifecycle Actions in Cisco CloudCenter Workload Manager Resource Placement and Validation Callout Understanding Application Deployment Framework in Cisco CloudCenter Workload Manager Workload Manager Application Parameters Exploring Application Services in Cisco CloudCenter Workload Manager Application Services Framework Integrating Cisco CloudCenter Workload Manager with Cisco Application-Centric Infrastructure Configure CloudCenter Workload Manager for Cisco ACI Introducing Application Management in Cisco CloudCenter Workload Manager Cisco CloudCenter Workload Manager Actions Library Exploring Advanced Features in CloudCenter Workload Manager Scheduling an Application in Cisco CloudCenter Workload Manager Comprehending Policies and Tagless Governance in CloudCenter Workload Manager Cisco CloudCenter Workload Manager Policies Introducing Action Orchestrator and Cost Optimizer in Cisco CloudCenter Suite Action Orchestrator in Cisco CloudCenter Suite Lab outline Explore Cisco CloudCenter Suite Admin GUI Discover Cisco CloudCenter Workload Manager GUI Create Cisco CloudCenter Workload Manager Repository Design Deployment Environments in Cisco CloudCenter Workload Manager Create Images in Cisco CloudCenter Workload Manager Form Cost Bundles and Usage Plans in Cisco CloudCenter Workload Manager Explore Multitenancy in Cisco CloudCenter Suite Model and Deploy Two-Tier Application Model and Deploy Multitier Application Perfect and Arrange Multitier Application on Docker Model and Deploy Application on Kubernetes Cloud Deploy Application in Hybrid Cloud Arrange Application Using Automated Resource Placement Perform Lifecycle Actions on Deployed Applications Create User-Defined Parameters and Explore Macros Understand Application Services in Cisco CloudCenter Workload Manage Benchmark, Schedule, and Share Applications in Cisco CloudCenter Workload Manager Continuous Integration/Continuous Delivery (CI/CD) Project Board Manage Policies in Cisco CloudCenter Workload Manager Manage System Tags and Governance in Cisco CloudCenter Workload Manager Explore Action Orchestrator Explore Cost Optimizer Additional course details: Nexus Humans Cisco Multicloud Management with Cisco CloudCenter Suite (CLDCCS) v1.0 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 Multicloud Management with Cisco CloudCenter Suite (CLDCCS) v1.0 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 Experienced system administrators, system engineers, and system integrators Overview By the end of the course, you should be able to meet the following objectives: Describe the architecture of VMware Cloud on AWS Prepare and deploy VMware Cloud on AWS SDDC Configure the scale-up and scale-down of a VMware Cloud on AWS SDDC Access a VMware vCenter configuration in VMware Cloud on AWS Configure internal, external, and inter-SDDC networking Configure storage integrations and solutions for VMware Cloud on AWS Configure a connection between an on-premises vSphere SDDC and a VMware Cloud on AWS SDDC Migrate VMs between on-premises vSphere and VMware Cloud on AWS SDDCs Describe lifecycle management, troubleshooting scenarios, and disaster recovery solutions for a VMware Cloud on AWS SDDC Describe how VMware add-on solutions support a VMware Cloud on AWS SDDC This four-day, hands-on training course provides you with the knowledge, skills, and tools for deploying and managing a VMware Cloud? on AWS infrastructure. You will explore the common use cases of the VMware Cloud on AWS infrastructure that allows you to modernize, protect, and scale applications based on VMware vSphere© that leverage AWS.In this course, you are introduced to various rapid and easy migration options for workloads based on vSphere to VMware Cloud on AWS. In addition, you are presented with VMware Cloud Disaster Recovery?, which is a Disaster Recovery as-a-service (DRaaS) solution, with fast recovery capabilities, that can be used to cost-effectively protect a broad set of your virtualized applications. Course Introduction Introductions and course logistics Course objectives Introduction to VMware Cloud on AWS Choosing VMware Cloud on AWS Management and operational structure VMware Cloud on AWS Platform and SDDC Deployment Preparation Getting started with VMware Cloud on AWS Preparing AWS infrastructure for a VMware Cloud on AWS deployment Setting up a VMware on Cloud AWS account Billing and pricing on VMware Cloud services Deploying and Scaling and SDDC Deploying and examining SDDC configurations Sizing the SDDC SDDC cluster management SDDC host management Optimizing and maintaining SDDC Cluster using Elastic DRS for VMware Cloud on AWS Accessing and Analyzing vCenter Configurations Accessing vCenter Server in the Cloud SDDC Analyzing resource management settings in the SDDC Exploring vSphere permissions on VMware Cloud on AWS VMware Tanzu? for VMC on AWS Networking in VMware Cloud on AWS Internal SDDC network Networking and security options SDDC Network Administration with NSX Manager Creating virtual machines in the Cloud SDDC Inter-SDDC networking Storage on VMware Cloud on AWS vSAN storage in VMware Cloud on AWS Attaching external storage to a VM running on an SDDC Working with On-Premises vSphere Hybrid-linked mode Migration solutions for VMware Cloud on AWS VM migration with VMware HCX© Maintaining and Troubleshooting VMware Cloud on AWS Accessing API with VMware Cloud on AWS Maintenance and support Common troubleshooting steps Disaster Recovery Solution Site Recovery add-on service VMware Cloud Disaster Recovery? Using Other VMware Products with the SDDC VMware Aria? Operations for Logs (formerly vRealize Log Insight) VMware Horizon© with VMware Cloud on AWS VMware Aria Automation add-on (formerly vRealize Automation) Using VMware Aria Operations with VMware Cloud on AWS Using VMware Aria Operations for Networks (formerly vRealize Network Insight) with VMware Cloud on AWS Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware Cloud on AWS: Design, Configure, Manage 2023 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 Cloud on AWS: Design, Configure, Manage 2023 course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Duration 3 Days 18 CPD hours This course is intended for This class is intended for the following customer job roles: Cloud architects, administrators, and SysOps personnel Cloud developers and DevOps personnel Overview This course teaches participants the following skills: Plan and implement a well-architected logging and monitoring infrastructure Define Service Level Indicators (SLIs) and Service Level Objectives (SLOs) Create effective monitoring dashboards and alerts Monitor, troubleshoot, and improve Google Cloud infrastructure Analyze and export Google Cloud audit logs Find production code defects, identify bottlenecks, and improve performance Optimize monitoring costs This course teaches you techniques for monitoring, troubleshooting, and improving infrastructure and application performance in Google Cloud. Guided by the principles of Site Reliability Engineering (SRE), and using a combination of presentations, demos, hands-on labs, and real-world case studies, attendees gain experience with full-stack monitoring, real-time log management and analysis, debugging code in production, tracing application performance bottlenecks, and profiling CPU and memory usage. Introduction to Google Cloud Monitoring Tools Understand the purpose and capabilities of Google Cloud operations-focused components: Logging, Monitoring, Error Reporting, and Service Monitoring Understand the purpose and capabilities of Google Cloud application performance management focused components: Debugger, Trace, and Profiler Avoiding Customer Pain Construct a monitoring base on the four golden signals: latency, traffic, errors, and saturation Measure customer pain with SLIs Define critical performance measures Create and use SLOs and SLAs Achieve developer and operation harmony with error budgets Alerting Policies Develop alerting strategies Define alerting policies Add notification channels Identify types of alerts and common uses for each Construct and alert on resource groups Manage alerting policies programmatically Monitoring Critical Systems Choose best practice monitoring project architectures Differentiate Cloud IAM roles for monitoring Use the default dashboards appropriately Build custom dashboards to show resource consumption and application load Define uptime checks to track aliveness and latency Configuring Google Cloud Services for Observability Integrate logging and monitoring agents into Compute Engine VMs and images Enable and utilize Kubernetes Monitoring Extend and clarify Kubernetes monitoring with Prometheus Expose custom metrics through code, and with the help of OpenCensus Advanced Logging and Analysis Identify and choose among resource tagging approaches Define log sinks (inclusion filters) and exclusion filters Create metrics based on logs Define custom metrics Link application errors to Logging using Error Reporting Export logs to BigQuery Monitoring Network Security and Audit Logs Collect and analyze VPC Flow logs and Firewall Rules logs Enable and monitor Packet Mirroring Explain the capabilities of Network Intelligence Center Use Admin Activity audit logs to track changes to the configuration or metadata of resources Use Data Access audit logs to track accesses or changes to user-provided resource data Use System Event audit logs to track GCP administrative actions Managing Incidents Define incident management roles and communication channels Mitigate incident impact Troubleshoot root causes Resolve incidents Document incidents in a post-mortem process Investigating Application Performance Issues Debug production code to correct code defects Trace latency through layers of service interaction to eliminate performance bottlenecks Profile and identify resource-intensive functions in an application Optimizing the Costs of Monitoring Analyze resource utilization cust for monitoring related components within Google Cloud Implement best practices for controlling the cost of monitoring within Google Cloud
Duration 4 Days 24 CPD hours This course is intended for This course is intended for security and network administrators who will be responsible for the installation, deployment, tuning, and day-to-day maintenance of the F5 Advanced Web Application Firewall. In this 4 day course, students are provided with a functional understanding of how to deploy, tune, and operate F5 Advanced Web Application Firewall to protect their web applications from HTTP-based attacks. The course includes lecture, hands-on labs, and discussion about different F5 Advanced Web Application Firewall tools for detecting and mitigating threats from multiple attack vectors such web scraping, Layer 7 Denial of Service, brute force, bots, code injection, and zero day exploits. Module 1: Setting Up the BIG-IP System Introducing the BIG-IP System Initially Setting Up the BIG-IP System Archiving the BIG-IP System Configuration Leveraging F5 Support Resources and Tools Module 2: Traffic Processing with BIG-IP Identifying BIG-IP Traffic Processing Objects Overview of Network Packet Flow Understanding Profiles Overview of Local Traffic Policies Visualizing the HTTP Request Flow Module 3: Web Application Concepts Overview of Web Application Request Processing Web Application Firewall: Layer 7 Protection F5 Advanced WAF Layer 7 Security Checks Overview of Web Communication Elements Overview of the HTTP Request Structure Examining HTTP Responses How F5 Advanced WAF Parses File Types, URLs, and Parameters Using the Fiddler HTTP Proxy Module 4: Common Web Application Vulnerabilities A Taxonomy of Attacks: The Threat Landscape What Elements of Application Delivery are Targeted? Common Exploits Against Web Applications Module 5: Security Policy Deployment Defining Learning Comparing Positive and Negative Security Models The Deployment Workflow Policy Type: How Will the Policy Be Applied Policy Template: Determines the Level of Protection Policy Templates: Automatic or Manual Policy Building Assigning Policy to Virtual Server Deployment Workflow: Using Advanced Settings Selecting the Enforcement Mode The Importance of Application Language Configure Server Technologies Verify Attack Signature Staging Viewing Requests Security Checks Offered by Rapid Deployment Defining Attack Signatures Using Data Guard to Check Responses Module 6: Policy Tuning and Violations Post-Deployment Traffic Processing Defining Violations Defining False Positives How Violations are Categorized Violation Rating: A Threat Scale Defining Staging and Enforcement Defining Enforcement Mode Defining the Enforcement Readiness Period Reviewing the Definition of Learning Defining Learning Suggestions Choosing Automatic or Manual Learning Defining the Learn, Alarm and Block Settings Interpreting the Enforcement Readiness Summary Configuring the Blocking Response Page Module 7: Attack Signatures & Threat Campaigns Defining Attack Signatures Attack Signature Basics Creating User-Defined Attack Signatures Defining Simple and Advanced Edit Modes Defining Attack Signature Sets Defining Attack Signature Pools Understanding Attack Signatures and Staging Updating Attack Signatures Defining Threat Campaigns Deploying Threat Campaigns Module 8: Positive Security Policy Building Defining and Learning Security Policy Components Defining the Wildcard Defining the Entity Lifecycle Choosing the Learning Scheme How to Learn: Never (Wildcard Only) How to Learn: Always How to Learn: Selective Reviewing the Enforcement Readiness Period: Entities Viewing Learning Suggestions and Staging Status Violations Without Learning Suggestions Defining the Learning Score Defining Trusted and Untrusted IP Addresses How to Learn: Compact Module 9: Cookies and Other Headers F5 Advanced WAF Cookies: What to Enforce Defining Allowed and Enforced Cookies Configuring Security Processing on HTTP headers Module 10: Reporting and Logging Overview: Big Picture Data Reporting: Build Your Own View Reporting: Chart based on filters Brute Force and Web Scraping Statistics Viewing F5 Advanced WAF Resource Reports PCI Compliance: PCI-DSS 3.0 The Attack Expert System Viewing Traffic Learning Graphs Local Logging Facilities and Destinations How to Enable Local Logging of Security Events Viewing Logs in the Configuration Utility Exporting Requests Logging Profiles: Build What You Need Configuring Response Logging Module 11: Lab Project 1 Lab Project 1 Module 12: Advanced Parameter Handling Defining Parameter Types Defining Static Parameters Defining Dynamic Parameters Defining Dynamic Parameter Extraction Properties Defining Parameter Levels Other Parameter Considerations Module 13: Automatic Policy Building Overview of Automatic Policy Building Defining Templates Which Automate Learning Defining Policy Loosening Defining Policy Tightening Defining Learning Speed: Traffic Sampling Defining Track Site Changes Lesson 14: Web Application Vulnerability Scanner Integration Integrating Scanner Output Importing Vulnerabilities Resolving Vulnerabilities Using the Generic XML Scanner XSD file Lesson 15: Deploying Layered Policies Defining a Parent Policy Defining Inheritance Parent Policy Deployment Use Cases Lesson 16: Login Enforcement and Brute Force Mitigation Defining Login Pages for Flow Control Configuring Automatic Detection of Login Pages Defining Session Tracking Brute Force Protection Configuration Source-Based Brute Force Mitigations Defining Credentials Stuffing Mitigating Credentials Stuffing Lesson 17: Reconnaissance with Session Tracking Defining Session Tracking Configuring Actions Upon Violation Detection Lesson 18: Layer 7 DoS Mitigation Defining Denial of Service Attacks Defining the DoS Protection Profile Overview of TPS-based DoS Protection Creating a DoS Logging Profile Applying TPS Mitigations Defining Behavioral and Stress-Based Detection Lesson 19: Advanced Bot Protection Classifying Clients with the Bot Defense Profile Defining Bot Signatures Defining Proactive Bot Defense Defining Behavioral and Stress-Based Detection Defining Behavioral DoS Mitigation Lesson 20: Form Encryption using DataSafe Targeting Elements of Application Delivery Exploiting the Document Object Model Protecting Applications Using DataSafe The Order of Operations for URL Classification Lesson 21: Review and Final Labs Review and Final Labs
Duration 2.5 Days 15 CPD hours This course is intended for This course is designed for administrators who configure and manage web-based applications on WebSphere Application Server. Web administrators, application developers and deployers, security specialists, and application architects can also benefit from this course.Prerequisite(s) Overview After completing this course, you should be able to:Relate WebSphere Application Server to the WebSphere family of productsDescribe the features and standards in WebSphere Application Server V9Describe the use of WebSphere Application Server in cloud, hybrid cloud, and on-premises environmentsDescribe the architectural concepts that are related to WebSphere Application ServerAssemble and install server-side Java enterprise applicationsUse WebSphere administrative tools to configure and manage enterprise applicationsUse wsadmin scriptingConfigure WebSphere Application Server securityView performance information about server and application componentsTroubleshoot problems by using problem determination tools and log files In this course, you learn how to configure and maintain IBM WebSphere Application Server V9 in a single-server environment. Course Outline Course introduction WebSphere product family overview WebSphere Application Server architecture - stand-alone Exercise: Profile creation WebSphere Application Server administrative console Exercise: Exploring the administrative console Introduction to the PlantsByWebSphere application Application assembly Exercise: Assembling an application Application installation Exercise: Installing an application Problem determination Exercise: Problem determination Introduction to wsadmin and scripting Exercise: Using wsadmin WebSphere security Exercise: Configuring WebSphere Application Server security Exercise: Configuring application security Performance monitoring Exercise: Using the performance monitoring tools Course summary Additional course details: Nexus Humans WA590 IBM WebSphere Application Server V9 Administration 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 WA590 IBM WebSphere Application Server V9 Administration 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 intended for solution architects, developers, business analysts, system administrators, or anyone who works as a solution builder within their company. Overview Build and deploy a solution Create properties and document classes Create roles and in-baskets Create a case type and tasks Create a workflow Use preconditions and sets Automate case packaging Add case stages Apply solution design principles In this course you will create basic case management solutions with IBM Case Manager Builder and Process Designer. Using an iterative solution development process, you will create, deploy, test, and revise your solutions, adding complexity and functionality to your solutions as you gain skills. You will create properties and document classes, configure roles and in-baskets, and define case stages. You will work with case types, tasks, and workflows. This course includes some guidelines on solution design principles. After completing this course, you can build on these skills by taking more advanced or specialized courses in security, user-interface customization, and solution deployment. Build and Deploy a Solution Build a solution Deploy a solution Test a solution Manage roles Redeploy a solution Create Properties and Document Classes Create case properties Create task properties Create a business object Create document classes Create Roles and In-Baskets Create roles Create in-baskets Create Tasks Create a to-do task Create a container task Add the to-do list widget to the Case Details pag Create a Step Map Open a task in Step Designer Create a step map Add a workgroup to a step map Add an attachment to a step map Use Preconditions and Sets Organize tasks with preconditions Organize tasks with inclusive sets Organize tasks with exclusive sets Automate Case Packaging Open a task in Process Designer Add a component step to a task Use a component step to package a case Add Case Stages Add case stages to a solution Use a system step to perform a case stage operation Use a case stage as a task precondition Solution Design Principles Describe solution design principles
Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brandnew version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative dversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions
Duration 3 Days 18 CPD hours This course is intended for This intermediate course is for all computer professionals who will use z/OS UNIX. Overview Discuss the role of z/OS in an open systems environmentIdentify the basic terms used in z/OS UNIXDefine the components of z/OS UNIXExplain major functions provided in z/OS UNIXDiscuss opportunities for applications in a z/OS UNIX environmentIdentify z/OS base elements and optional features that make up z/OS UNIXUse the two interactive interfaces available to access the services This course describes how open standards are implemented in a z/OS system by z/OS UNIX. UNIX System Services are introduced, and the role of z/OS as a server in the open systems environment is discussed. Day 1 Welcome and introduction Unit 1. z/OS UNIX overview Unit 2. Introduction to z/OS UNIX Unit 3. Hierarchical file system Exercises Day 2 Unit 4. z/OS UNIX shell and utilities Unit 5. z/OS UNIX shell commands Unit 6. Working with the shell Unit 7. Functions in z/OS UNIX Exercises Day 3 Unit 8. Working with the z/OS UNIX environment Exercises
Duration 3 Days 18 CPD hours This course is intended for This advanced course is for IT professionals tasked with administering a Spectrum Scale system. Overview Please see Overview This course is intended for IT professionals tasked with administering a Spectrum Scale system. It includes information on installing, configuring and monitoring a Spectrum Scale cluster. Migrating to IBM Spectrum Scale 4.2Spectrum Scale 4.2 GUIMulti-clusterClustered NFSCluster Export Services for multi-protocol supportSMB Protocol SupportNFS Support in CES; Ganesha overview/performanceActive File ManagementAFM-Based Disaster Recovery (DR) and Asynchronous DRPlanning LTFS and GPFS environment for data archivingFile Placement OptimizerIBM© GPFS-FPO and integration with GPFS Hadoop connectorIBM© Spectrum Scale Call HomeMonitoring and performance tuningFlash Cache metadata migration
Duration 3 Days 18 CPD hours This course is intended for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary. Overview By the end of this course, you will be able to build your own marketing reporting and interactive dashboard solutions. The course starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation.As you make your way through the course, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding sections, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. Data Preparation and Cleaning Data Models and Structured Data pandas Data Manipulation Data Exploration and Visualization Identifying the Right Attributes Generating Targeted Insights Visualizing Data Unsupervised Learning: Customer Segmentation Customer Segmentation Methods Similarity and Data Standardization k-means Clustering Choosing the Best Segmentation Approach Choosing the Number of Clusters Different Methods of Clustering Evaluating Clustering Predicting Customer Revenue Using Linear Regression Understanding Regression Feature Engineering for Regression Performing and Interpreting Linear Regression Other Regression Techniques and Tools for Evaluation Evaluating the Accuracy of a Regression Model Using Regularization for Feature Selection Tree-Based Regression Models Supervised Learning: Predicting Customer Churn Classification Problems Understanding Logistic Regression Creating a Data Science Pipeline Fine-Tuning Classification Algorithms Support Vector Machine Decision Trees Random Forest Preprocessing Data for Machine Learning Models Model Evaluation Performance Metrics Modeling Customer Choice Understanding Multiclass Classification Class Imbalanced Data Additional course details: Nexus Humans Data Science for Marketing Analytics 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 Data Science for Marketing Analytics 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.