108 Courses in Birmingham delivered Live Online

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 5 Days 30 CPD hours This course is intended for Students in this course are interested in Azure development or in passing the Microsoft Azure Developer Associate certification exam. This course teaches developers how to create end-to-end solutions in Microsoft Azure. Students will learn how to implement Azure compute solutions, create Azure Functions, implement and manage web apps, develop solutions utilizing Azure storage, implement authentication and authorization, and secure their solutions by using KeyVault and Managed Identities. Students will also learn how to connect to and consume Azure services and third-party services, and include event- and message-based models in their solutions. The course also covers monitoring, troubleshooting, and optimizing Azure solutions. Prerequisites To be successful in this course, learners should have the following: Hands-on experience with Azure IaaS and PaaS solutions, and the Azure Portal. Experience writing in an Azure supported language at the intermediate level. (C#, JavaScript, Python, or Java) Ability to write code to connect and perform operations on, a SQL or NoSQL database product. (SQL Server, Oracle, MongoDB, Cassandra or similar) Experience writing code to handle authentication, authorization, and other security principles at the intermediate level. A general understanding of HTML, the HTTP protocol and REST API interfaces. 1 - Explore Azure App Service Examine Azure App Service Examine Azure App Service plans Deploy to App Service Explore authentication and authorization in App Service Discover App Service networking features 2 - Configure web app settings Configure application settings Configure general settings Configure path mappings Enable diagnostic logging Configure security certificates 3 - Scale apps in Azure App Service Examine autoscale factors Identify autoscale factors Enable autoscale in App Service Explore autoscale best practices 4 - Explore Azure App Service deployment slots Explore staging environments Examine slot swapping Swap deployment slots Route traffic in App Service 5 - Explore Azure Functions Discover Azure Functions Compare Azure Functions hosting options Scale Azure Functions 6 - Develop Azure Functions Explore Azure Functions development Create triggers and bindings Connect functions to Azure services 7 - Explore Azure Blob storage Explore Azure Blob storage Discover Azure Blob storage resource types Explore Azure Storage security features Discover static website hosting in Azure Storage 8 - Manage the Azure Blob storage lifecycle Explore the Azure Blob storage lifecycle Discover Blob storage lifecycle policies Implement Blob storage lifecycle policies Rehydrate blob data from the archive tier 9 - Work with Azure Blob storage Explore Azure Blob storage client library Create a client object Manage container properties and metadata by using .NET Set and retrieve properties and metadata for blob resources by using REST 10 - Explore Azure Cosmos DB Identify key benefits of Azure Cosmos DB Explore the resource hierarchy Explore consistency levels Choose the right consistency level Explore supported APIs Discover request units 11 - Work with Azure Cosmos DB Explore Microsoft .NET SDK v3 for Azure Cosmos DB Create stored procedures Create triggers and user-defined functions Explore change feed in Azure Cosmos DB 12 - Manage container images in Azure Container Registry Discover the Azure Container Registry Explore storage capabilities Build and manage containers with tasks Explore elements of a Dockerfile 13 - Run container images in Azure Container Instances Explore Azure Container Instances Run containerized tasks with restart policies Set environment variables in container instances Mount an Azure file share in Azure Container Instances 14 - Implement Azure Container Apps Explore Azure Container Apps Explore containers in Azure Container Apps Implement authentication and authorization in Azure Container Apps Manage revisions and secrets in Azure Container Apps Explore Dapr integration with Azure Container Apps 15 - Explore the Microsoft identity platform Explore the Microsoft identity platform Explore service principals Discover permissions and consent Discover conditional access 16 - Implement authentication by using the Microsoft Authentication Library Explore the Microsoft Authentication Library Initialize client applications 17 - Implement shared access signatures Discover shared access signatures Choose when to use shared access signatures Explore stored access policies 18 - Explore Microsoft Graph Discover Microsoft Graph Query Microsoft Graph by using REST Query Microsoft Graph by using SDKs Apply best practices to Microsoft Graph 19 - Implement Azure Key Vault Explore Azure Key Vault Discover Azure Key Vault best practices Authenticate to Azure Key Vault 20 - Implement managed identities Explore managed identities Discover the managed identities authentication flow Configure managed identities Acquire an access token 21 - Implement Azure App Configuration Explore the Azure App Configuration service Create paired keys and values Manage application features Secure app configuration data 22 - Explore API Management Discover the API Management service Explore API gateways Explore API Management policies Create advanced policies Secure APIs by using subscriptions Secure APIs by using certificates 23 - Explore Azure Event Grid Explore Azure Event Grid Discover event schemas Explore event delivery durability Control access to events Receive events by using webhooks Filter events 24 - Explore Azure Event Hubs Discover Azure Event Hubs Explore Event Hubs Capture Scale your processing application Control access to events Perform common operations with the Event Hubs client library 25 - Discover Azure message queues Choose a message queue solution Explore Azure Service Bus Discover Service Bus queues, topics, and subscriptions Explore Service Bus message payloads and serialization Explore Azure Queue Storage Create and manage Azure Queue Storage and messages by using .NET 26 - Monitor app performance Explore Application Insights Discover log-based metrics Instrument an app for monitoring Select an availability test Troubleshoot app performance by using Application Map 27 - Develop for Azure Cache for Redis Explore Azure Cache for Redis Configure Azure Cache for Redis Interact with Azure Cache for Redis by using .NET 28 - Develop for storage on CDNs Explore Azure Content Delivery Networks Control cache behavior on Azure Content Delivery Networks Interact with Azure Content Delivery Networks by using .NET

Course Overview This comprehensive course offers a deep dive into three essential technologies for data science: Python, JavaScript, and Microsoft SQL. Learners will gain foundational knowledge and practical skills in each of these key areas, which are crucial for handling data, creating interactive websites, and working with databases. By the end of the course, students will be proficient in writing Python code for data analysis, creating dynamic web content with JavaScript, and managing data with Microsoft SQL. The course is designed to equip learners with the technical skills needed to succeed in data science, making it a valuable investment for anyone looking to excel in this growing field. Course Description In this course, learners will explore the core principles of Python, JavaScript, and Microsoft SQL, all tailored to the needs of data science professionals. The curriculum covers Python’s data structures, functions, and libraries essential for data analysis, while JavaScript introduces students to web development skills, including client-side validation and data visualisation. The Microsoft SQL section focuses on data management, including filtering, joining, and structuring queries. Learners will develop a solid understanding of these technologies, which will enable them to manipulate data, automate processes, and design interactive applications. The course also includes real-world applications, ensuring learners are well-prepared for future opportunities in data science and web development. Course Modules: Module 01: JavaScript Getting Started Module 02: JavaScript Fundamentals Module 03: JavaScript Strings Module 04: JavaScript Operators Module 05: JavaScript Conditional Statements Module 06: JavaScript Control Flow Statements Module 07: JavaScript Functions Module 08: Data Visualization (Google Charts) Module 09: JavaScript Error Handling Module 10: JavaScript Client-Side Validations Module 11: Python Introduction Module 12: Python Basic Module 13: Python Strings Module 14: Python Operators Module 15: Python Data Structures Module 16: Python Conditional Statements Module 17: Python Control Flow Statements Module 18: Python Core Games Module 19: Python Functions Module 20: Python Args, KW Args for Data Science Module 21: Python Project Module 22: Publish Your Website for Live Module 23: MS SQL Statements Module 24: MS SQL Filtering Data Module 25: MS SQL Functions Module 26: MS SQL Joins Module 27: MS SQL Advanced Commands Module 28: MS SQL Structure and Keys Module 29: MS SQL Queries Module 30: MS SQL Structure Queries Module 31: MS SQL Constraints Module 32: MS SQL Backup and Restore (See full curriculum) Who is this course for? Individuals seeking to enhance their skills in data science. Professionals aiming to expand their knowledge in programming and database management. Beginners with an interest in Python, JavaScript, and SQL. Anyone looking to enter the field of data science or web development. Career Path Data Scientist Web Developer Database Administrator Data Analyst Front-End Developer Full Stack Developer Data Engineer

Duration 4 Days 24 CPD hours This course is intended for The primary audience for this course is system installers, system integrators, system administrators, network administrators, and solutions designers. Overview At the end of this course, you will be able to: Describe the NSO's transactional application framework and mapping model options Describe the Reactive Fastmap design pattern and the NSO Configuration Database (CDB) subscriber in the NSO Transaction model Simplify packages to remove the need for subscriber applications, scale orchestration solutions, and integrate NSO with external systems (east-west integration)Describe the Cisco ESC architecture and integration with NSO, and how the NSO VNF Orchestration (VNFO) Release 2 bundle interacts with ESC for orchestration This course explores how to create advanced services using the NSO application framework and Python scripting with both new and existing Layer 3 Multiprotocol Label Switching (MPLS) VPN services. Students will also learn how to manage and scale these services, and how to use NSO Network Functions Virtualization (NFV) orchestration features and Cisco Elastic Services Controller (ESC) to manage Virtualized Network Functions (VNFs). Cisco NSO Programmability NSO Application Framework NSO Python Scripting NSO Python and Template-Based Services Resources Augmenting Cisco NSO Service Service Lifecycle and Integration Options Overview Greenfield Layer 3 MPLS VPN Service Brownfield Layer 3 MPLS VPN Service Managed Services Managed Services Overview Stacked Service Design Overview Design-Managed Network Services Scaling Service Orchestration Cisco NSO Network Functions Virtualization (NFV) Orchestration ETSI MANO Cisco ESC Cisco NSO Orchestration Additional course details: Nexus Humans Cisco Network Services Orchestrator Advanced Design (NSO300) 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 Network Services Orchestrator Advanced Design (NSO300) 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.

Course Overview This comprehensive course on Coding (HTML, C++, Python, JavaScript & IT) offers a structured introduction to the world of coding and information technology. It covers an expansive array of programming languages and technologies, including HTML, CSS, JavaScript, C++, Python, and PHP, alongside key IT concepts such as cybersecurity, cloud computing, and network security. Learners will develop a deep understanding of programming logic, software development, web development, and essential IT operations. Whether you're aiming to explore programming for the first time or expand your technical skill set, this course equips you with the knowledge required to navigate modern computing systems and coding environments. Upon completion, learners will be better prepared to pursue roles in web development, programming, system administration, and IT support across various industries. Course Description This course delivers an in-depth exploration of both coding and IT fundamentals, offering a diverse curriculum that spans core programming languages such as HTML, C++, Python, JavaScript, and R. It extends into cybersecurity, Linux scripting, ethical hacking, and computer networking—creating a well-rounded foundation for digital fluency. Learners are introduced to the design and development of web applications, front-end and back-end technologies, and essential tools such as GitHub, Heroku, and MySQL. The course further includes IT administration, encryption methods, cloud infrastructure, and system troubleshooting, ensuring coverage of key concepts necessary in today’s tech-driven world. With a focus on conceptual clarity and structured progression, learners will gain valuable knowledge aligned with current industry needs and expectations. Course Modules Module 01: Introduction to Coding With HTML, CSS, & Javascript Module 02: C++ Development: The Complete Coding Guide Module 03: Python Programming: Beginner To Expert Module 04: Learn Ethical Hacking From A-Z: Beginner To Expert Module 05: Bash Scripting, Linux and Shell Programming Module 06: JavaScript Project – Game Development with JS Module 07: R Programming for Data Science Module 08: Secure Programming of Web Applications Module 09: Advanced Diploma in PHP Web Development with MySQL, GitHub & Heroku Module 10: The Complete Front-End Web Development Course! Module 11: The Complete MySQL Server from Scratch: Bootcamp Module 12: Cyber Security Awareness Training Module 13: Cloud Computing / CompTIA Cloud+ (CV0-002) Module 14: CompTIA A+ (220-1001) Module 15: Building Your Own Computer Module 16: Computer Networks Security from Scratch to Advanced Module 17: IT Administration and Networking Module 18: Encryption Module 19: Advance Windows 10 Troubleshooting for IT HelpDesk Module 20: Microsoft Excel Complete Course (See full curriculum) Who is this course for? Individuals seeking to understand programming languages and IT fundamentals. Professionals aiming to transition into coding or expand their IT knowledge. Beginners with an interest in computing, programming, or digital technologies. Students or career changers preparing for roles in the tech sector. Career Path Web Developer Software Programmer IT Support Technician Network Administrator Cybersecurity Analyst Cloud Computing Technician Data Analyst Systems Engineer Helpdesk Specialist IT Consultant

This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.

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.

Duration 2 Days 12 CPD hours This course is intended for DevOps Engineers Software Developers Telecommunications Professionals Architects Quality Assurance & Site Reliability Professionals Overview Automate basic freestyle projects Jenkins Pipelines and Groovy Programming Software lifecycle management with Jenkins Popular plugins Scaling options Integrating Jenkins with Git and GitHub (as well as other Software Control Management platforms) Triggering Jenkins with Webhooks Deploying into Docker and Kubernetes CI / CD with Jenkins This course covers the fundamentals necessary to deploy and utilize the Jenkins automation server. Jenkins enables users to immediately begin automating both their individual and collaborative workflows. Jenkins is a proven solution for a wide variety of tasks ranging from the helpful automation of scripts (such as Python and Ansible) to creating complex pipelines that govern the technical parts of not only Continuous Integration, but Continuous Delivery (CI/CD) as well. Jenkins is free, open source, and easily controlled with a simple web- based UI- it can be expanded by third party plugins and is deployable on nearly any on-site (Linux, Windows and Mac) or cloud platform. Overview of Jenkins Overview of Continuous Integration and Continuous Deployment (CI/CD) Understanding Git and GitHub Git Branching Methods for Installing Jenkins Jenkins Dashboard Jenkins Jobs Getting Started with Freestyle Jobs Triggering builds HTTP Web Hooks Augmenting Jenkins with Plugins Overview of Docker and Dockerfile for Building and Launching Images Pipeline Jobs for Continuous Integration and Continuous Deployment Pipeline Build Stage Pipeline Testing Stage Post Build actions SMTP and Other Notifications Programming Pipelines with Groovy More Groovy Programming Essentials Extracting Jenkins Data Analytics to Support Project Management Troubleshooting Failures Auditing stdout and stderr with Jenkins Jenkins REST API Controlling Jenkins API with Python Jenkins Security Scaling Jenkins Jenkins CLI Building a Kubernetes Cluster and Deploying Jenkins How to start successfully using Jenkins to automate aspects of your job the moment this course ends.

Duration 4 Days 24 CPD hours This course is intended for The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview Overview of data science and machine learning at scale Overview of the Hadoop ecosystem Working with HDFS data and Hive tables using Hue Introduction to Cloudera Data Science Workbench Overview of Apache Spark 2 Reading and writing data Inspecting data quality Cleansing and transforming data Summarizing and grouping data Combining, splitting, and reshaping data Exploring data Configuring, monitoring, and troubleshooting Spark applications Overview of machine learning in Spark MLlib Extracting, transforming, and selecting features Building and evaluating regression models Building and evaluating classification models Building and evaluating clustering models Cross-validating models and tuning hyperparameters Building machine learning pipelines Deploying machine learning models Spark, Spark SQL, and Spark MLlib PySpark and sparklyr Cloudera Data Science Workbench (CDSW) Hue This workshop covers data science and machine learning workflows at scale using Apache Spark 2 and other key components of the Hadoop ecosystem. The workshop emphasizes the use of data science and machine learning methods to address real-world business challenges. Using scenarios and datasets from a fictional technology company, students discover insights to support critical business decisions and develop data products to transform the business. The material is presented through a sequence of brief lectures, interactive demonstrations, extensive hands-on exercises, and discussions. The Apache Spark demonstrations and exercises are conducted in Python (with PySpark) and R (with sparklyr) using the Cloudera Data Science Workbench (CDSW) environment. The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview of data science and machine learning at scaleOverview of the Hadoop ecosystemWorking with HDFS data and Hive tables using HueIntroduction to Cloudera Data Science WorkbenchOverview of Apache Spark 2Reading and writing dataInspecting data qualityCleansing and transforming dataSummarizing and grouping dataCombining, splitting, and reshaping dataExploring dataConfiguring, monitoring, and troubleshooting Spark applicationsOverview of machine learning in Spark MLlibExtracting, transforming, and selecting featuresBuilding and evauating regression modelsBuilding and evaluating classification modelsBuilding and evaluating clustering modelsCross-validating models and tuning hyperparametersBuilding machine learning pipelinesDeploying machine learning models Additional course details: Nexus Humans Cloudera Data Scientist Training training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Cloudera Data Scientist Training course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 2 Days 12 CPD hours This course is intended for Experienced security administrators and security analysts who are already familiar with VMware Carbon Black Cloud Overview By the end of the course, you should be able to meet the following objectives: Describe and determine use cases for integrating with VMware Carbon Black Cloud Configure, automate, and troubleshoot the VMware Carbon Black Cloud Syslog Integration Use VMware Carbon Black Cloud APIs to pull data with Postman Install and use the VMware Carbon Black Cloud Python SDK Automate operations using the VMware Carbon Black Cloud SDK and APIs Identify and troubleshoot VMware Carbon Black Cloud sensor installations Gather troubleshooting data within the browser to remediate or escalate problems Identify and resolve sensor usage, networking, and performance problems with the VMware Carbon Black Cloud sensor This two-day, hands-on training course provides you with the advanced knowledge, skills, and tools to achieve competency in performing advanced operations and troubleshooting of VMware Carbon Black Cloud. This course will go into integrating VMware Carbon Black Cloud with other third-party components and utilizing the API and the SDK to automate operations within the product and your security stack. This course will also enable you to troubleshoot common problems during sensor installation, operations, and within the VMware Carbon Black Cloud console with hands-on lab problems. Course Introduction Introductions and course logistics Course objectives VMware Carbon Black Cloud Integrations Describe the integration capabilities with VMware Carbon Black Cloud Determine integration use cases for VMware Carbon Black Cloud Identify required components for integrating VMware Carbon Black Cloud Differentiate VMware Carbon Black Cloud integration vendors VMware Carbon Black Cloud Syslog Integration Describe the function of the Syslog Connector Generate API and SIEM keys from the Cloud console Validate a successful Syslog integration Describe how to automate the Syslog Connector Troubleshoot problems with the Syslog integration Using Postman Explain the concept and purpose of an API Interpret common REST API Status codes Recognize the difference between platform and product APIs Using the Postman Client to initiate API calls Create a custom access level and respective API key Create a valid API request Using the VMware Carbon Black Cloud Python SDK Install the VMware Carbon Black Cloud Python SDK Describe the different authentication methods Evaluate the best authentication method for a given task Automating Operations Automate basic Incident Response tasks using the VMware Carbon Black Cloud SDK and API Automate basic watchlist interactions using the VMware carbon Black Cloud SDK and API Sensor Installation Troubleshooting Describe sensor install log collection process Identify sensor install log parameters Create a detailed sensor install log Locate sensor install logs on an endpoint Interpret sensor install success from an install log Determine likely cause for install failure using sensor logs Propose resolution steps for a given sensor install failure VMware Carbon Black Cloud Console Troubleshooting Identify sensor bypass status reasons Simplify console data exports using search Describe differences in Audit Log detail levels Locate built-in browser tools Gather console diagnostics logs from a browser Review console diagnostics logs Sensor Operations Troubleshooting Identify available types of diagnostic logs Gather appropriate diagnostic logs for a given issue Identify steps for resolving software interoperability problems Identify steps for resolving resource problems Identify steps for resolving network problems Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware Carbon Black Cloud:Advanced Operations and Troubleshooting 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 Carbon Black Cloud:Advanced Operations and Troubleshooting 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.