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Duration 3 Days 18 CPD hours This course is intended for This course is designed for Service Provider networking professionals in job roles such as: Network administrators Network architects Network designers Network engineers Network managers Network Operations Center (NOC) personnel Network supervisors Overview After taking this course, you should be able to: Use NETCONF and RESTCONF programmability protocols on Cisco devices Describe and use tools to validate YANG data models on Cisco devices Describe and configure model-driven telemetry on Cisco devices Describe and configure network traffic automation with Cisco XTC Describe and use network automation tools that utilize SSH Automate service provider network configuration with Cisco NSO Describe how to automate virtualized resources with Cisco ESC Describe how to automate service provider WAN with Cisco WAE This course prepares you to implement and support automation solutions in a Service Provider network infrastructure, using network programmability principles, protocols, tools, and mechanisms. Through a combination of lessons and hands-on labs, you will learn to deploy, configure, monitor, and operate Service Provider network environments using modern data models. These models allow you to represent operational data and new network management protocols in order to administer hundreds or thousands of devices in a single operation, replacing traditional, time-consuming, error prone, device-by-device Command Line Interface (CLI) management. The course also introduces powerful automation solutions that can streamline network operations. This course also prepares you for the CCNP-Service Provider concentration exam 300-535. Implementing Network Device Programmability Interfaces with NETCONF and RESTCONF Implement NETCONF Protocol Implement RESTCONF Protocol Implementing Model-Driven Programmability with YANG YANG Data Models YANG Tools YANG Development Kit Implementing Model-Driven Telemetry Implementing Model-Driven Telemetry with gRPC Implementing Model-Driven Telemetry with gNMI Automating Service Provider Network Traffic with Cisco XTC Cisco XTC Fundamentals Configure Cisco XTC Automating Networks with Tools That Utilize SSH Implement Device Configurations with Python Netmiko Library Implement Device Configurations with Ansible Playbooks Orchestrating Network Services with Cisco NSO Cisco NSO Fundamentals Cisco NSO Device Manager Cisco NSO Services Implement Device Configurations with Python Automating Virtualized Resources with Cisco Elastic Services Controller Cisco ESC Architecture Cisco ESC Resource Management Automating the WAN with Cisco WAE Describe the Cisco WAE Components Additional course details: Nexus Humans Cisco Implementing Automation for Cisco Service Provider Solutions v1.0 (SPAUI) 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 Service Provider Solutions v1.0 (SPAUI) 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 Students in this course are experienced AWS developers interested in Azure development. A three-day course designed to teach AWS (Amazon Web Services) developers how to prepare end-to-end solutions in Microsoft Azure. In this course you will construct Azure App Service Web App solutions and Azure Functions, use blob or Cosmos DB storage in solutions, implement secure cloud solutions that include user authentication and authorization, implement API management, and develop event- and message-based solutions, and monitor, troubleshoot, and optimize your Azure solutions. You will learn how developers use Azure services, with additional focus on features and tasks that differ from AWS, and what that means for you as you develop applications that will be hosted by using Azure services Create Azure App Service Web Apps Azure App Service core concepts Creating an Azure App Service Web App Configuring and Monitoring App Service apps Scaling App Service apps Azure App Service staging environments Implement Azure functions Azure Functions overview Developing Azure Functions Implement Durable Functions Develop solutions that use blob storage Azure Blob storage core concepts Managing the Azure Blob storage lifecycle Working with Azure Blob storage Create an Azure Resource Manager Template Develop solutions that use Cosmos DB storage Azure Cosmos DB overview Azure Cosmos DB data structure Working with Azure Cosmos DB resources and data Create and deploy ARM templates Implement user authentication and authorization Microsoft Identity Platform v2.0 Authentication using the Microsoft Authentication Library Using Microsoft Graph Authorizing data operations in Azure Storage Implement secure cloud solutions Manage keys, secrets, and certificates by using the KeyVault API Implement Managed Identities for Azure resources Secure app configuration data by using Azure App Configuration Implement API Management API Management overview Defining policies for APIs Securing your APIs Develop event-based solutions Implement solutions that use Azure Event Grid Implement solutions that use Azure Event Hubs Implement solutions that use Azure Notification Hubs Develop message-based solutions Implement solutions that use Azure Service Bus Implement solutions that use Azure Queue Storage queues Monitor and optimize Azure solutions Overview of monitoring in Azure Instrument an app for monitoring Analyzing and troubleshooting apps Implement code that handles transient faults Additional course details: Nexus Humans AZ-020T00 - Microsoft Azure solutions for AWS Developers 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 AZ-020T00 - Microsoft Azure solutions for AWS Developers 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 Learners who will find this course applicable to their work include: Solutions architects Cloud practitioners Data engineers Data scientists Developers Overview In this course, you will explore: Workload definition and key concepts The AWS Well-Architected Framework Review phases, process, best practices, and antipatterns High and medium risks Prioritizing improvements to the AWS Well-Architected workflow Locating and using the AWS Well-Architected Framework white paper, labs, prebuilt solutions in the AWS solutions library, AWS Well-Architected independent software vendors (ISVs), and AWS Well-Architected Partner Program (WAPP) This interactive course provides a deep dive into Amazon Web Services (AWS) best practices to help you perform effective and efficient AWS Well-Architected Framework Reviews. The course covers the phases of a review, including how to prepare, run, and get guidance after a review has been performed. Attendees should have familiarity with the AWS concepts, terminology, services, and tools that are covered in the intermediate, 200-levelAWS Well-Architected Best Practices.This course provides an AWS Well-Architected Framework Review simulation and instructor-led group exercises and discussions regarding prioritizing and solutioning risks. The content focuses on teaching learners how to prepare proposals on high and medium risk issues using the AWS Well-Architected Tool. Module 1: AWS Well-Architected Framework Reviews Workload definition Key concepts of a workload AWS Well-Architected Review phases AWS Well-Architected Review approach, lessons learned, and use case AWS Well-Architected Review best practices AWS Well-Architected Review anti-patterns Module 2: Customer Scenario Group Sessions Demonstration of a Review question and answer example Operational excellence Group role-play exercise Two questions in this pillar Security Group role-play exercise Three questions in this pillar Reliability Group role-play exercise Three questions in this pillar Performance efficiency Group role-play exercise Three questions in this pillar Cost optimization Group role-play exercise Three questions in this pillar Module 3: Risk Solutions and Priorities AWS Well-Architected workflow Defining and solutioning high risk issues (HRIs) and medium risk issues (MRIs) Identifying significant risks and solutioning group discussion for: Operational excellence Security Reliability Performance efficiency Cost optimization Prioritizing improvements Module 4: Resources Resource pages AWS Well-Architected ISVs Module 5: Course Summary Objective recap Debrief What?s next? Additional course details: Nexus Humans Advanced AWS Well-Architected Best Practices 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 Advanced AWS Well-Architected Best Practices 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 Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Supporting people managers The flagship CAPE programme is different to other management development programmes. We offer people management training that supports managers to feel equipped, enabled and empowered to make an immediate and lasting impact. You will benefit from learning how conversation styles, self-belief and authenticity matter and practice your skills with one of our many charity partners towards the end of your training. 12 month multi-element programme Learn new coaching skills Work with charities to utilise your skills Limited spaces £1,795 plus VAT per person Our mission is to help you become a brilliant manager.

Duration 4 Days 24 CPD hours This course is intended for This course is intended for the person who has responsibility for daily system operations. Overview Send, display, and respond to messages Use the online help and reference materials Monitor and control job queues, active jobs, and output queues Create and change user profiles Use authorization lists and group profiles Start and stop Power Systems with IBM i Manage system devices, user display stations, and printers Save and restore objects and libraries Monitor job and history logs Diagnose a system problem Order, receive, and install PTFs This course enables a new system operator to develop basic to intermediate level skills needed for day-to-day operations of the Power System with IBM i Power Systems and IBM i concepts and overview . Reference material and support . Overview of 5250 emulation and help . Overview of System i Navigator . Overview of IBM Navigator for i . Messaging concepts . Messaging with 5250 emulation . Messaging with System i Navigator . Messaging with IBM Navigator for i . CL command concepts . CL commands with 5250 emulation . Concepts: Object, library, and the IFS . Object management with 5250 emulation . Object management with System i Navigator . Object management with IBM Navigator for i . Introduction to work management . Work management with 5250 emulation . Job control with 5250 emulation . Job control with System i Navigator . Job control with IBM Navigator for i . Print concepts . Print control with 5250 emulation . Print control with System i Navigator . Print control with IBM Navigator for i . Starting and stopping the system . System security concepts . System security with 5250 emulation . System security with System i Navigator . System security with IBM Navigator for i . System configuration overview . Configuration with 5250 emulation . Configuration with System i Navigator . Configuration with IBM Navigator for i . Save concepts . Save with 5250 emulation . Save with System i Navigator . Save with IBM Navigator for i . Restore concepts and overview . Problem determination with 5250 emulation . Problem determination with System i Navigator . Overview of the PTF process . PTFs with 5250 Emulation . Class summary . Additional course details: Nexus Humans AS24 IBM System Operator Workshop for IBM i 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 AS24 IBM System Operator Workshop for IBM i 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.

3 Months Subscription Up to 45 mock tests Detailed feedback and scoring on all skills Progress report Model Answer Library on Writing Four free one-to-one sessions with an IELTS Expert

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 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

Read and discuss this novel of what it is to be human Highlights Join this book club and gain extra motivation to read in English 7 hours of live classes to help you develop fluent speaking in English Read this contemporary novel and discuss love, emotional intelligence and humanity Be corrected by an expert English teacher to remove errors and mistakes Practise and develop your English online in this course featuring Matt Haig's The Humans. Each week you read some chapters, discuss them in class and improve specific areas of vocabulary or grammar while also examining aspects of the novel. Personalised feedback improves your grammar, vocabulary and pronunciation. The Book Club book From the writer of The Midnight Library and How to Stop Time comes The Humans - a funny novel about alien abduction, mathematics, and what it is to be human. It combines hilarious moments with thought-provoking insights into how we interact. Maths professor Andrew Martin, is dead. His body is now taken over by an alien, who discovers that the professor wasn't very nice. The alien finds himself learning more about the professor, his family, and “the humans”. When he starts to feel for his own wife and son - who have no clue he’s not the real Andrew- the alien has a decision to make - complete his mission or abandon it and start a new life with the humans. Geoff says: "I laughed out loud reading this - but it also addresses serious themes. It shines a light on what it means to be human, and gaining emotional intelligence."