61 Ecosystem courses in Cardiff delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This course is intended for system administrators, network administrators and application developers responsible for the customization of traffic flow through a BIG-IP system. This course provides networking professionals a functional understanding of iRules development. The course builds on the foundation of the Administering BIG-IP or Configuring LTM course, demonstrating how to logically plan and write iRules to help monitor and manage common tasks involved with processing traffic on the BIG-IP system. Extensive course labs consist of writing, applying and evaluating the effect of iRules on local traffic. This hands-on course includes lectures, labs, and discussions. Module 1: Setting Up the BIG-IP System Introducing the BIG-IP System Initially Setting Up the BIG-IP System Archiving the BIG-IP System Configuration Leveraging F5 Support Resources and Tools Module 2: Getting Started with iRules Customizing Application Delivery with iRules Triggering an iRule Leveraging the DevCentral Ecosystem Creating and Deploying iRules Module 3: Exploring iRule Elements Introducing iRule Constructs Understanding iRule Events and Event Context Working with iRule Commands Logging from an iRule Using SYSLOG-NG (LOG Command) Working with User-Defined Variables Working with Operators and Data Types Working with Conditional Control Structures (IF and SWITCH) Incorporating Best Practices in iRules Module 4: Developing and Troubleshooting iRules Mastering Whitespace and Special Symbols Grouping Strings Developing and Troubleshooting Tips Using Fiddler to Test and Troubleshoot iRules Module 5: Optimizing iRule Execution Understanding the Need for Efficiency Measure iRule Runtime Efficiency Using Timing Statistics Modularizing iRules for Administrative Efficiency Using Procedures to Modularize Code Optimizing Logging Using High-Speed Logging Commands in an iRule Implementing Other Efficiencies Using Looping Control Structures (WHILE, FOR, FOREACH Commands) Module 6: Securing Web Applications with iRules Integrating iRules into Web Application Defense Mitigating HTTP Version Attacks Mitigating Path Traversal Attacks Using iRules to Defends Against Cross-Site Request Forgery (CSRF) Mitigating HTTP Method Vulnerabilities Securing HTTP Cookies with iRules Adding HTTP Security Headers Removing Undesirable HTTP Headers Module 7: Working with Numbers and Strings Understanding Number Forms and Notation Working with Strings (STRING and SCAN Commands) Combining Strings (Adjacent Variables, CONCAT and APPEND Commands) Using iRule String Parsing Functions (FINDSTR, GETFIELD, and SUBSTR Commands) Module 8: Processing the HTTP Payload Reviewing HTTP Headers and Commands Accessing and Manipulating HTTP Headers (HTTP::header Commands) Other HTTP commands (HTTP::host, HTTP::status, HTTP::is_keepalive, HTTP::method, HTTP::version, HTTP::redirect, HTTP::respond, HTTP::uri) Parsing the HTTP URI (URI::path, URI::basename, URI::query) Parsing Cookies with HTTP::cookie Selectively Compressing HTTP Data (COMPRESS Command) Module 9: Working with iFiles and Data Groups Working with iFiles Introducing Data Groups Working with Old Format Data Groups (MATCHCLASS, FINDCLASS) Working with New Format Data Groups (CLASS MATCH, CLASS SEARCH) Module 10: Using iRules with Universal Persistence, Stream, and Statistics Profiles Implementing Universal Persistence (PERSIST UIE Command) Working with the Stream Profile (STREAM Command) Collecting Statistics Using a Statistics Profile (STATS Command) Collecting Statistics Using iStats (ISTATS Command) Module 11: Incorporating Advanced Variables Reviewing the Local Variable Namespace Working with Arrays (ARRAY Command) Using Static and Global Variables Using the Session Table (TABLE Command) Processing Session Table Subtables Counting ?Things? Using the Session Table

Duration 5 Days 30 CPD hours This course is intended for This course provides an immersive learning experience for business and technical professionals who need a thorough understanding of the CMMC program. It does this by taking the point of view of a CMMC Certified Professional. Students might consider taking this course to learn more about the overall CMMC program, how DoD contractors are assessed, and how to help their organizations prepare for a CMMC Assessment. Overview In this course, you will learn about the CMMC Model, framework, context, and application within the DoD, as well as the expectations and requirements imposed upon organizations that do business with the DoD. You will: Identify the threats to the Defense Supply Chain and the established regulations and standards for managing the risk. Identify the sensitive information that needs to be protected within the Defense Supply Chain and how to manage it. Describe how the CMMC Model ensures compliance with federal acquisitions regulations. Identify responsibilities of the Certified CMMC Professional, including appropriate ethical behavior. Establish the Certification and Assessment scope boundaries for evaluating the systems that protect regulated information. Prepare the OSC for an Assessment by evaluating readiness. Use the CMMC Assessment Guides to determine and assess the Evidence for practices. Implement and evaluate practices required to meet CMMC Level 1. Identify the practices required to meet CMMC Level 2. Work through the CMMC Assessment process. The Cybersecurity Maturity Model Certification (CMMC), managed by The Cyber AB (formerly known as the CMMC Accreditation Body or the CMMC-AB), is a program through which an organization's cybersecurity program maturity is measured by their initial and ongoing compliance with applicable cybersecurity practices, as well as their integration of corresponding policies and plans into their overall business operations. Once rule-making has concluded and CMMC 2.0 has been implemented, all organizations providing products or services to the United States Department of Defense (DoD) must comply with the requirements of their applicable CMMC Level. This course provides a complete review of the key elements of this important program. Lesson 1: Managing Risk within the Defense Supply Chain Topic A: Identify Threats to the Defense Supply Chain Topic B: Identify Regulatory Responses against Threats Lesson 2: Handling Sensitive Information Topic A: Identify Sensitive Information Topic B: Manage the Sensitive Information Lesson 3: Ensuring Compliance through CMMC Topic A: Describe the CMMC Model Architecture Topic B: Define the CMMC Program and Its Ecosystem Topic C: Define Self-Assessments Lesson 4: Performing CCP Responsibilities Topic A: Identify Responsibilities of the CCP Topic B: Demonstrate Appropriate Ethics and Behavior Lesson 5: Scoping Certification and Assessment Boundaries Topic A: Use the CMMC Assessment Scope Documentation Topic B: Get Oriented to the OSC Environment Topic C: Determine How Sensitive Information Moves Topic D: Identify Systems in Scope Topic E: Limit Scope Lesson 6: Preparing the OSC Topic A: Foster a Mature Cybersecurity Culture Topic B: Evaluate Readiness Lesson 7: Determining and Assessing Evidence Topic A: Determine Evidence Topic B: Assess the Practices Using the CMMC Assessment Guides Lesson 8: Implementing and Evaluating Level 1 Topic A: Identify CMMC Level 1 Domains and Practices Topic B: Perform a CMMC Level 1 Gap Analysis Topic C: Assess CMMC Level 1 Practices Lesson 9: Identifying Level 2 Practices Topic A: Identify CMMC Level 2 Practices Lesson 10: Working through an Assessment Topic A: Identify Assessment Roles and Responsibilities Topic B: Plan and Prepare the Assessment Topic C: Conduct the Assessment Topic D: Report the Assessment Results Topic E: Conduct the CMMC POA&M Close-Out Assessment

There is a lot to learn in Power BI, this course takes a comprehensive look at the fundamentals of analysing data and includes a balanced look at the four main components that make up Power BI Desktop: Report view, Data view, Model view, and the Power Query Editor. It also demonstrates how to utilise the online Power BI service. It looks at authoring tools that enable you to connect to and transform data from a variety of sources, allowing you to produce detailed reports through a range of visualisations, in an interactive and dynamic way. It also includes a detailed look at formulas by writing both M functions in Power Query, and DAX functions in Desktop view. This knowledge will allow you to take your reports to the next level. The aim of this course is to provide a complete introduction to understanding the Power BI analysis process, by working hands-on with examples that will equip you with the necessary skills to start applying your learning straight away. 1 Getting Started The Power BI ecosystem Opening Power BI Desktop Power BI's four views Introduction to Dashboards 2 Importing Files Importing data sources Importing an Excel file Importing a CSV file Importing a database Connect to an SQL Server Database Import vs. Direct Query Importing from the web Importing a folder of files Managing file connections 3 Shape Data in the Query Editor The process of shaping data Managing data types Keeping and removing rows Add a custom column Appending tables together Hiding queries in reports Fixing error issues Basic maths operations 4 The Data Model Table relationships Relationship properties 5 Merge Queries Table join kinds Merging tables 6 Inserting Dashboard Visuals Things to keep in mind Inserting maps Formatting Maps Inserting charts Formatting Charts Inserting a tree map Inserting a table, matrix, and card Controlling number formats About report themes Highlighting key points Filter reports with slicers Sync slicers across dashboards Custom web visuals 7 Publish and share Reports Publishing to Power BI service Editing online reports Pinning visuals to a dashboard What is Q&A? Sharing dashboards Exporting reports to PowerPoint Exporting reports as PDF files 8 The Power Query Editor Fill data up and down Split column by delimiter Add a conditional column More custom columns Merging columns 9 The M Functions Inserting text functions Insert an IF function Create a query group 10 Pivoting Tables Pivot a table Pivot and append tables Pivot but don't aggregate Unpivot tables Append mismatched headers 11 Data Modelling Expanded Understanding relationships Mark a date table 12 DAX New Columns New columns and measures New column calculations Insert a SWITCH function 13 Introduction to DAX Measures Common measure functions Insert a SUM function Insert a COUNTROWS function Insert a DISTINCTCOUNT function Insert a DIVIDE function DAX rules 14 The CALCULATE Measure The syntax of CALCULATE Insert a CALCULATE function Control field summarisation Things of note 15 The SUMX measure X iterator functions Anatomy of SUMX Insert a SUMX function When to use X functions 16 Time Intelligence Measures Importance of a calendar table Insert a TOTALYTD function Change financial year end date Comparing historical data Insert a DATEADD function 17 Hierarchies and Groups Mine data using hierarchies Compare data in groups

Duration 3 Days 18 CPD hours This course is intended for This course is designed for network and software engineers who hold the following job roles: Network engineer Systems engineer Wireless engineer Consulting systems engineer Technical solutions architect Network administrator Wireless design engineer Network manager Site reliability engineer Deployment engineer Sales engineer Account manager Overview After taking this course, you should be able to: Leverage the tools and APIs to automate Cisco ACI powered data centers. Demonstrate workflows (configuration, verification, healthchecking, monitoring) using Python, Ansible, and Postman. Leverage the various models and APIs of the Cisco Nexus OS platform to perform day 0 operations, improve troubleshooting methodologies with custom tools, augment the CLI using scripts, and integrate various workflows using Ansible and Python. Describe the paradigm shift of Model Driven Telemetry and understand the building blocks of a working solution. Describe how the Cisco Data Center compute solutions can be managed and automated using API centric tooling, by using the Python SDK, PowerTool, and Ansible modules to implement various workflows on Cisco UCS, Cisco IMC, Cisco UCS Manager, Cisco UCS Director, and Cisco Intersight. The Implementing Automation for Cisco Data Center Solutions (DCAUI) v1.1 course teaches you how to implement Cisco© Data Center automated solutions including programming concepts, orchestration, and automation tools. Through a combination of lessons and hands-on practice, you will manage the tools and learn the benefits of programmability and automation in the Cisco-powered Data Center. You will examine Cisco Application Centric Infrastructure (Cisco ACI©), Software-Defined Networking (SDN) for data center and cloud networks, Cisco Nexus© (Cisco NX-OS) platforms for device-centric automation, and Cisco Unified Computing System (Cisco UCS©) for Data Center compute. You will study their current ecosystem of Application Programming Interfaces (APIs), software development toolkits, and relevant workflows along with open industry standards, tools, and APIs, such as Python, Ansible, Git, JavaScript Object Notation (JSON), Yaml Ain't Markup Language (YAML), Network Configuration Protocol (NETCONF), Representational State Transfer Configuration Protocol (RESTCONF), and Yet Another Generation (YANG).This course prepares you for the 300-635 Automating Cisco Data Center Solutions (DCAUTO) certification exam. Introducing Automation for Cisco Solutions (CSAU) is required prior to enrolling in Implementing Automation for Cisco Data Center Solutions (DCAUI) because it provides crucial foundational knowledge essential to success. This course also earns you 24 Continuing Education (CE) credits towards recertification. Course Outline Describing the Cisco ACI Policy Model Describing the Cisco APIC REST API Using Python to Interact with the ACI REST API Using Ansible to Automate Cisco ACI Introducing Cisco NX-OS Programmability Describing Day-Zero Provisioning with Cisco NX-OS Implementing On-Box Programmability and Automation with Cisco NX-OS Implementing Off-Box Programmability and Automation with Cisco NX-OS Automating Cisco UCS Using Developer Tools Implementing Workflows Using Cisco UCS Director Describing Cisco DCNM Describing Cisco Intersight Additional course details: Nexus Humans Cisco Implementing Automation for Cisco Data Center Solutions (DCAUI) v1.1 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 Automation for Cisco Data Center Solutions (DCAUI) v1.1 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 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 5 Days 30 CPD hours This course is intended for To fully benefit from this course, you should have three to five years of experience designing and implementing applications that are built on top of Cisco platforms. This course is appropriate for: Network engineers expanding their skill-base to include software and automation Developers expanding expertise in automation and DevOps Solution architects moving to the Cisco ecosystem Infrastructure developers designing hardened production environments The job roles best suited to the material in this course are: Senior network automation engineer Senior software developer Senior system integration programmer Additional job roles that could find this course useful are: Senior infrastructure architect Senior network designer Senior test development engineer Students preparing for Cisco Certified DevNet Professional and Cisco Certified DevNet Specialist - Core certification will also find this material useful. Overview After taking this course, you should be able to: Describe the architectural traits and patterns that improve application maintainability Describe the architectural traits and patterns that improve application serviceability Identify steps to design and build a ChatOps application Implement robust Representational State Transfer (REST) API integrations with network error handling, pagination, and error flow control Describe the necessary steps for securing user and system data in applications Describe the necessary steps for securing applications Identify common tasks in automated application release process Describe best practices for application deployment Describe methodologies for designing distributed systems Describe the concepts of infrastructure configuration management and device automation Utilize Yet Another Next Generation (YANG) data models to describe network configurations and telemetry Compare various relational and nonrelational database types and how to select the appropriate type based on requirements In this course, you will learn how to implement network applications using Cisco© platforms as a base, from initial software design to diverse system integration, as well as testing and deployment automation. The course gives you hands-on experience solving real world problems using Cisco Application Programming Interfaces (APIs) and modern development tools. This course helps you prepare for Cisco DevNet Professional certification and for professional-level network automation engineer roles. COURSE OUTLINE DESIGNING FOR MAINTAINABILITY (SELF-STUDY) DESIGNING FOR SERVICEABILITY (SELF-STUDY) IMPLEMENTING CHATOPS APPLICATION DESCRIBING ADVANCED REST API INTEGRATION SECURING APPLICATION DATA (SELF-STUDY) SECURING WEB AND MOBILE APPLICATIONS (SELF-STUDY) AUTOMATING APPLICATION-RELEASE DEPLOYING APPLICATIONS UNDERSTANDING DISTRIBUTED SYSTEMS ORCHESTRATING NETWORK AND INFRASTRUCTURE MODELING DATA WITH YANG USING RELATIONAL AND NON-RELATIONAL DATABASES (SELF-STUDY) PLEASE NOTE:This class includes lecture sections and self-study sections. In instructor-led classes, lectures are delivered in real-time, either in person or via video conferencing. In e-learning courses, the lectures are on recorded videos. In both versions, you will need to review self-study sections on your own before taking the certification exam. Additional course details: Nexus Humans Cisco Developing Applications Using Cisco Core Platforms and APIs v1.0 (DEVCOR) 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 Developing Applications Using Cisco Core Platforms and APIs v1.0 (DEVCOR) 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 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 brand-new 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 adversarial 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 Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform Overview This course teaches participants the following skills: Use best practices for application development. Choose the appropriate data storage option for application data. Implement federated identity management. Develop loosely coupled application components or microservices. Integrate application components and data sources. Debug, trace, and monitor applications. Perform repeatable deployments with containers and deployment services. Choose the appropriate application runtime environment; use Google Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine flexible environment. Learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. This course uses lectures, demos, and hands-on labs to show you how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications. Best Practices for Application Development Code and environment management. Design and development of secure, scalable, reliable, loosely coupled application components and microservices. Continuous integration and delivery. Re-architecting applications for the cloud. Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK. Lab: Set up Google Client Libraries, Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials. Overview of Data Storage Options Overview of options to store application data. Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner. Best Practices for Using Cloud Firestore Best practices related to using Cloud Firestore in Datastore mode for:Queries, Built-in and composite indexes, Inserting and deleting data (batch operations),Transactions,Error handling. Bulk-loading data into Cloud Firestore by using Google Cloud Dataflow. Lab: Store application data in Cloud Datastore. Performing Operations on Cloud Storage Operations that can be performed on buckets and objects. Consistency model. Error handling. Best Practices for Using Cloud Storage Naming buckets for static websites and other uses. Naming objects (from an access distribution perspective). Performance considerations. Setting up and debugging a CORS configuration on a bucket. Lab: Store files in Cloud Storage. Handling Authentication and Authorization Cloud Identity and Access Management (IAM) roles and service accounts. User authentication by using Firebase Authentication. User authentication and authorization by using Cloud Identity-Aware Proxy. Lab: Authenticate users by using Firebase Authentication. Using Pub/Sub to Integrate Components of Your Application Topics, publishers, and subscribers. Pull and push subscriptions. Use cases for Cloud Pub/Sub. Lab: Develop a backend service to process messages in a message queue. Adding Intelligence to Your Application Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API. Using Cloud Functions for Event-Driven Processing Key concepts such as triggers, background functions, HTTP functions. Use cases. Developing and deploying functions. Logging, error reporting, and monitoring. Managing APIs with Cloud Endpoints Open API deployment configuration. Lab: Deploy an API for your application. Deploying Applications Creating and storing container images. Repeatable deployments with deployment configuration and templates. Lab: Use Deployment Manager to deploy a web application into Google App Engine flexible environment test and production environments. Execution Environments for Your Application Considerations for choosing an execution environment for your application or service:Google Compute Engine (GCE),Google Kubernetes Engine (GKE), App Engine flexible environment, Cloud Functions, Cloud Dataflow, Cloud Run. Lab: Deploying your application on App Engine flexible environment. Debugging, Monitoring, and Tuning Performance Application Performance Management Tools. Stackdriver Debugger. Stackdriver Error Reporting. Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting. Stackdriver Logging. Key concepts related to Stackdriver Trace and Stackdriver Monitoring. Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance.

Duration 4.375 Days 26.25 CPD hours This course is intended for This course provides a jump start on learning material that relates to the CMMC program, and to the planned Certified Professional (CP) certification in particular. It discusses the CMMC program, the current CMMC Model, and other CMMC materials as they exist today. The course may be of interest to individuals who wish to pursue the CMMC-CP certification when it is released. It may also be useful to stakeholders in organizations who will be involved in CMMC assessments, and who wish to gain a general understanding of the program and its requirements for their business planning purposes Overview In this course, you will examine the current CMMC model (Version 1.02), framework, context, and application within the DoD, as well as the expectations and requirements that will be imposed upon organizations that do business with the DoD. It will also help you to identify threats to cybersecurity and privacy within an IoT ecosystem and implement appropriate countermeasures. You will gain the skills to: · Identify risks within the defense supply chain and the established standards for managing them. · Describe how the CMMC model ensures compliance with federal acquisition regulations. · Identify responsibilities of the CMMC Certified Professional, including appropriate ethics and behavior. · Identify regulated information and establish the Certification and Assessment scope boundaries for evaluating the systems that protect that regulated information. · Evaluate OSC readiness and determine the objective evidence you intend to present to the assessor. · Use the NIST 800-171A and CMMC Assessment Guide to assess objective evidence for processes and practices. · Implement and evaluate practices required to meet CMMC maturity level 1. · Implement and evaluate processes and practices required to meet CMMC maturity level 2. · Implement and evaluate processes and practices required to meet CMMC maturity level 3. · Identify processes and practices required to meet CMMC maturity levels 4 and 5. · Work through the logistics of a CMMC assessment, including planning for and conducting the assessment, as well as any follow-up processes, such as remediation and adjudication. The Cybersecurity Maturity Model Certification (CMMC), managed by the CMMC Accreditation Body (CMMC-AB), is a program through which an organization's cybersecurity program is measured by their initial and ongoing compliance with applicable cybersecurity practices as well as their integration of corresponding policies and plans into their overall business operations. By Fiscal Year 2026, all organizations providing products or services to the United States Department of Defense (DoD) must obtain at least a Maturity Level 1 certification under this program. Managing Risk within the Defense Supply Chain Topic A: Identify Threats to the Defense Supply Chain Topic B: Identify Regulatory Responses Against Threats Ensuring Compliance through CMMC Topic A: Identify Limitations of Self-Certification Topic B: Identify Benefits of CMMC Topic C: Describe the CMMC Model Architecture Performing the General Responsibilities of a CMMC CP Topic A: Identify Responsibilities of the CMMC CP Topic B: Demonstrate Appropriate Ethics and Behavior Identifying and Scoping Regulated Information Topic A: Identify Regulated Information Topic B: Establish the Certification and Assessment Scope Boundaries Initiating the Assessment Process Topic A: Evaluate Readiness Topic B: Determine Objective Evidence Assessing Objective Evidence Topic A: Assess the Practices Using the CMMC Assessment Guides Topic B: Assess the Processes Using the CMMC Assessment Guide Level 3 Implementing and Evaluating CMMC Level 1 TTopic A: Maturity Level 1 Domains and Practices Topic B: Determine Scope Boundaries at Maturity Level 1 Topic C: Perform a Maturity Level 1 Gap Analysis Topic D: Perform a Maturity Level 1 Evidence Validation Implementing and Evaluating CMMC Levels 2 and 3 Topic A: Process Maturity Requirements for CMMC Levels 2 and 3 Topic B: Maturity Level 2 Practices Topic C: Maturity Level 3 Practices Identifying CMMC Levels 4 and 5 Topic A: Maturity Level 4 Processes and Practices Topic B: Maturity Level 5 Processes and Practices Working Through a CMMC Assessment Topic A: Define the Assessment Logistics Topic B: Resolve Assessment Related Issues Appendix A: Additional Documentation the CP Should Study

Duration 3 Days 18 CPD hours This course is intended for This course is designed primarily for network and software engineers who are interested in learning about automation and programmability and hold the following job roles: Network engineer Systems engineer Wireless engineer Consulting systems engineer Technical solutions architect Network administrator Wireless design engineer Network manager Sales engineer Account manager Overview Upon completing this course, the learner will be able to meet these overall objectives: Get familiar with different API styles (REST, RPC) and synchronous and asynchronous API requests Learn how to use Postman software development tool in order to test the API calls Learn how to automate repetitive tasks using Ansible automation engine Explore a Python programming language, Python libraries and Python virtual environments and learn how can they be used for automation of network configuration tasks Get introduced to GIT version control system and its common operations Learn how to leverage the various models and APIs of the Cisco IOS XE platform to perform day-zero operations, improve troubleshooting methodologies with custom tools, augment the CLI using scripts, and integrate various workflows using Ansible and Python Learn about the paradigm shift of model-driven telemetry and the building blocks of a working solution Learn how to leverage the tools and APIs to automate Cisco DNA infrastructure managed by Cisco DNA Center™ Demonstrate workflows (configuration, verification, health checking, and monitoring) using Python, Ansible, and Postman Understand Cisco SD-WAN solution components, implement a Python library that works with the Cisco SD-WAN APIs to perform configuration, inventory management, and monitoring tasks, and implement reusable Ansible roles to automate provisioning new branch sites on an existing Cisco SD-WAN infrastructure Learn how to leverage the tools and APIs to automate Cisco Meraki managed infrastructure and demonstrate workflows (configuration, verification, health checking, monitoring) using Python, Ansible, and Postman Implementing Automation for Cisco Enterprise Solutions (ENAUI) v.1.2 teaches you how to implement Cisco Enterprise automated solutions, including programming concepts, orchestration, telemetry, and automation tools. This course highlights the tools and the benefits of leveraging programmability and automation in the Cisco-powered Enterprise Campus and WAN. You will also examine platforms including IOS XE software for device-centric automation, Cisco DNA Center for the intent-based enterprise network, Cisco Software-Defined WAN, and Cisco Meraki. Their current ecosystem of APIs, software development toolkits, and relevant workflows are studied in detail together with open industry standards, tools, and APIs, such as Python, Ansible, Git, JSON/YAML, NETCONF/RESTCONF, and YANG. The course qualifies for 24 Cisco Continuing Education credits (CE) towards recertification. This course will help you:Gain high-demand skills using modern programming languages, APIs, and systems such as Python, Ansible, and Git to automate, streamline, and enhance business operationsAcquire the skills and knowledge to customize tools, methods, and processes that improve network performance and agilityPrepare for the 300-435 ENAUTO exam Course Outline Network Programmability Foundation Automating APIs and Protocols Managing Configuration with Python and Ansible Implementing On-Box Programmability and Automation with Cisco IOS XE Software Implementing Model-Driven Telemetry Day 0 Provisioning with Cisco IOS-XE Software Implementing Automation in Enterprise Networks Building Cisco DNA Center Automation with Python Automating Operations using Cisco DNA Center Introducing Cisco SD-WAN Programmability Building Cisco SD-WAN Automation with Python Building Cisco SD-WAN Automation with Ansible Automating Cisco Meraki Implementing Meraki Integration APIs Additional course details: Nexus Humans Cisco Implementing Automation for Cisco Enterprise Solutions v1.2 (ENAUI) 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 Automation for Cisco Enterprise Solutions v1.2 (ENAUI) 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.