363 Programming courses in Borehamwood delivered Live Online

Duration 5 Days 30 CPD hours This course is intended for This class is targeted towards the professional developer new to HTML, self-taught HTML developers, graphics designers and those new to HTML development. Overview After completing this course, you will be able to: Create HTML5 compliant web pages. Test and validate HTML and CSS code. Create CSS for style pages. Work with experimental vendor prefixes. Work with fonts and CSS font effects. Work with color and color tools. Layout pages and content using DIVs, iFrames and Tables. Add and format images and CSS sprites. Create HTML5 forms. Embed and manage video and audio content. This course is an in-depth hands-on study of HTML5, CSS3 and modern web and mobile development. The course includes detailed hands-on labs and Q&A labs. The labs include multiple projects, including one beginning to end web site.This material updates and replaces course Microsoft course 20480 which was previously published under the title Programming in HTML5 with JavaScript and CSS3. Module 1: A Brief History of HTML and the Web Welcome! History Details, Details, Details? The Life of a Web Page HTTP Status Codes Definitions Most Important Things to Know as a Web Developer Module 2: Core HTML Elements HTML and CSS Editors Text, Spaces and Tabs Working with Tags Attributes Comments Non-Standard Tags Every Page Includes? File Extensions Core Page Elements Nesting Testing HTML HTML and Text Module 3: Cascading Style Sheets Before CSS With CSS Cascading Style Sheets (CSS) Adding CSS to a Page Order of CSS Processing Experimental Vendor Prefixes CSS Units The CSS Box Mode Module 4: Fonts and Text Fonts CSS for Text CSS Text Ticks! Working with Lists Upgrading and to Windows 7 Module 5: Colors and Backgrounds Specifying Colors Applying Colors Gradients Module 6: Anchors and Hyperlinks HTML and CSS Hyperlinks with Images and Other Objects Buttons Module 7: Page Layout Page Layout Options Tables for Data DIVs Float SPAN HTML 5 DIV-like Tags IFRAMES Module 8: Images Favicon Preparing Images Image Files The IMG Tag Background Images Image Best Practices CSS Sprites Module 9: HTML Forms A Basic Form POST vs. GET name vs. id Basic Form Elements Basic Form Attribute Select Uploading Files HTML 5 Form Enhancements DataList Module 10: Multimedia Video and Audio HTML 5 Video CSS JavaScript Audio Hosting Videos in the Cloud Working with Animated GIFs

Duration 4 Days 24 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 administrators Solutions designers System installers System integrators System administrators Overview After completing this course, you should be able to: Explain the transactional service activation and how it relates to business requirements Explain how Cisco NSO communicates with network devices Understand the NETCONF protocol and be able to read and write simple YANG models Understand the difference between devices that are fully NETCONF capable and those that are less or not NETCONF capable Understand the support for candidate configuration and confirmed commit support Use logs to troubleshoot the Cisco NSO deployment and check NSO communication with network devices Explain the YANG service model structure Design a real-world usable service Explain the mapping logic of service parameters to device models and consequently to device configurations Describe the use of different integration options and APIs Explain how to implement action with use of config-templates in NSO package Explain the use of Reactive FASTMAP in for manipulating and implementing advanced NFV components Describe the use of feature components and function packs Define and explain the ETSI MANO principles and solution Work with the alarm console, and understand the NSO alarm structure and how it conforms to modern network operations procedures Describe Cisco NSO 5.3 new features and changes in NSO The NSO Essentials for Programmers and Network Architects (NSO201) v4.1 course introduces you to Cisco Network Services Orchestrator (NSO). You will learn to install Cisco NSO and use it to manage devices and create services based on YANG templates with XPath. This course provides an overview of NSO as a network automation solution as well as introducing you to NETCONF, YANG, and XPath. You will learn about managing devices and creating device templates, service management and service package creation, network element drivers, interfacing with other systems using APIs, configuring and troubleshooting system settings, managing alarms and reporting, configuring NSO for scalability and performance, and capabilities that can be added to Cisco NSO. Course Outline Introducing Service Orchestration with Cisco NSO Exploring Cisco NSO Architecture Orchestrating Network Solutions Describing Cisco NSO Operation Installing Cisco NSO Exploring the Advantages of NETCONF Managing Devices Using the Device Manager Creating YANG Models Using Services Implementing Services with Model-to-Model Mapping Designing Services in Cisco NSO Managing the Service Lifecycle Programming with Python in Cisco NSO Configuring and Troubleshooting System Settings Discovering Cisco NSO Northbound APIs Managing Alarms and Reporting Configuring Cisco NSO for Scalability and Performance Describing Cisco NSO VNF Manager and Function Packs

Overcoming Anxiety with NLP is a three hour online workshop with Accredited Trainer of NLP and Clinical Hypnotherapist Paul McGowran of proactivenlp.com. During the workshop Paul will take delegates through understanding how to resolve their own anxiety using NLP thinking and techniques. You can live a life without anxiety, sign up now.

Duration 2 Days 12 CPD hours This course is intended for If you are a data analyst, data scientist, or a business analyst who wants to get started with using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of computer programming and data analytics is a must. Familiarity with mathematical concepts such as algebra and basic statistics will be useful. Overview By the end of this course, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from data. This course is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The course will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You?ll discover how to tune the algorithms to provide the best predictions on new and unseen data. As you delve into later sections, you?ll be able to understand the working and output of these algorithms and gain insight into not only the predictive capabilities of the models but also their reasons for making these predictions. Data Exploration and Cleaning Python and the Anaconda Package Management System Different Types of Data Science Problems Loading the Case Study Data with Jupyter and pandas Data Quality Assurance and Exploration Exploring the Financial History Features in the Dataset Activity 1: Exploring Remaining Financial Features in the Dataset Introduction to Scikit-Learn and Model Evaluation Introduction Model Performance Metrics for Binary Classification Activity 2: Performing Logistic Regression with a New Feature and Creating a Precision-Recall Curve Details of Logistic Regression and Feature Exploration Introduction Examining the Relationships between Features and the Response Univariate Feature Selection: What It Does and Doesn't Do Building Cloud-Native Applications Activity 3: Fitting a Logistic Regression Model and Directly Using the Coefficients The Bias-Variance Trade-off Introduction Estimating the Coefficients and Intercepts of Logistic Regression Cross Validation: Choosing the Regularization Parameter and Other Hyperparameters Activity 4: Cross-Validation and Feature Engineering with the Case Study Data Decision Trees and Random Forests Introduction Decision trees Random Forests: Ensembles of Decision Trees Activity 5: Cross-Validation Grid Search with Random Forest Imputation of Missing Data, Financial Analysis, and Delivery to Client Introduction Review of Modeling Results Dealing with Missing Data: Imputation Strategies Activity 6: Deriving Financial Insights Final Thoughts on Delivering the Predictive Model to the Client

Duration 2 Days 12 CPD hours This course is intended for This in an intermediate-level Java development course geared for students experienced with Java and Spring programming essentials. This course does not cover Java or Spring development basics. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in core Cucumber and web testing skills, coupling the most current, effective techniques with the soundest industry practices. Working within in an engaging, hands-on learning environment, guided by our expert team, attendees will: Learn the request-response cycle of REST requests Implement a REST controller using Spring Map URLs to service endpoints Use Spring's template class to develop a REST client Bootstrap a Spring REST applications Return different media types for a service Setting the response headers Discuss Exceptions and HTTP Status codes Handle exceptions thrown by a service Spring REST focuses on providing an understanding of the fundamental principles and technologies that are used in the development of RESTful services and clients. This understanding is critical to being able to diagnose, troubleshoot, tune, and perform other lifecycle activities.Working with Spring REST is a two-day, fast-paced coding course geared for experienced developers who have prior working knowledge of Java. Throughout the course students learn the best practices for writing Restful services in Java using Spring Boot. The course provides an in-depth view of the APIs provided by Spring to develop both the REST service and the REST client. Implementing REST with Spring REST principles Introduction to RESTful Services in Spring Introduction to REST Clients in Spring Bootstrapping the REST application Content Representation Implementing the REST Service Error Handling Security and RESTful Services Securing Untrusted Input Defending RESTful Services Additional course details: Nexus Humans Working with Spring REST (TT3358) 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 Working with Spring REST (TT3358) 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 This is an introductory-level course for Users new to Tableau who will be administering a Tableau Server installation, including managing content, users, and permissions. Overview This skills-focused course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment led by our expert facilitator, students will learn how to: User interactions with Tableau Server Tableau Server components Single-server installation Content administration Authorization and permissions Users, groups, and sites Data sources and extracts Schedules, tasks, and subscriptions Monitoring server status Command-line utilities and REST API Upgrading a single-server installation to a new version Modifying the authentication method This fast paced hands-on course provides in-depth coverage of Tableau Server administration. The knowledge and skills acquired are best geared toward those who will be administering a Tableau Server installation, including managing content, users, and permissions. Tableau Server Overview Tableau Product Line End-User Abilities Tableau Server Architecture Component Functions Server Diagrams Single Server Installation Technical Specifications Tableau Server Installation Checklist Configuration Options Resolutions for Common Installation Issues Installing Tableau Server Software User Experience Content Navigation, Searching, and Filtering Exploring Server Content Types and Objects Updating Account Settings Setting the Start Page Viewing Version Information Renaming a Project Adding a Workbook Description Authorization and Permissions Administrator Settings Authorization Overview Functional Security Model Site Roles Content Ownership and Permissions Permission Rules and Capabilities Permissions and the Default Project Creating Projects, Local Groups, and a Local User Importing Users and Adding Users to Groups Granting Permissions to Projects Creating a Project Leader Publishing and Changing Ownership of a Workbook Moving a Workbook Site Administration Data Sources, Extracts, Schedules, and Subscriptions Creating, Publishing, and Connecting to a Data Source Data Engine and File Store Creating and Publishing Extracts Backgrounder Schedules Subscriptions Enabling Subscriptions and Alerts Automating Server Tasks Automating and Programming Server Tasks Tabadmin Tabcmd Using the REST API Monitoring Server Viewing Server Status Admin Alerts Viewing Email Alerts and Admin Views Enabling Access to the Repository Custom Admin Views Licensing Information Performance Recording Upgrading Tableau Server Preparing to Upgrade Upgrading Software on the Same Machine Modifying the Authentication Method Importing AD Groups Log Files Administration Overview of Log Files Archiving Log Files Data Security Controlling What Users Can See User Filters

Duration 4 Days 24 CPD hours This course is intended for This course is for people who have on the job experience doing project management activities and running projects, regardless of their job title. It is for those who wish to become certified project managers, or those that want to build or reinforce a foundation in project management. This course is ideal for a person who wants to grow and formalize their project management skills on an industry neutral, global standard, the Project Management Institute. Overview After completing this course, students will be able to: Demonstrate an understanding of the various project life cycles and processes. Distinguish between predictive and adaptive approaches. Demonstrate an understanding of project management planning. Demonstrate an understanding of project roles and responsibilities. Explain the importance of the role the project manager plays. Determine how to follow and execute and respond to planned strategies or frameworks (e.g., communication, risks, etc.). Demonstrate an understanding of common problem-solving tools and techniques. Identify the suitability of a predictive, plan-based approach for the organizational structure (e.g., virtual, colocation, matrix structure, hierarchical, etc.). Determine and give examples of the activities within each process. Demonstrate an understanding of a project management plan schedule. Determine how to document project controls of predictive, plan-based projects. Explain when it is appropriate and sustainable to use an adaptive approach for the organizational structure. Compare the pros and cons of adaptive and predictive, plan-based projects. Identify the suitability of adaptive approaches for the organizational structure (e.g., virtual, colocation, matrix structure, hierarchical, etc.). Identify organizational process assets and environmental factors that facilitate the use of adaptive approaches. Determine how to plan project iterations. Determine how to document project controls for an adaptive project. Distinguish between the components of different adaptive methodologies (e.g., Scrum, Extreme Programming (XP), Scaled Adaptive Framework (SAFe), Kanban, etc.). Determine how to prepare and execute task management steps. Demonstrate an understanding of business analysis (BA) roles and responsibilities. Demonstrate the importance of communication for a business analyst between various teams and stakeholders. Determine how to gather requirements and using the best approach for a situation. Explain the application of a product roadmap. Determine how project methodologies influence business analysis processes. Validate requirements through product delivery. Every career in project management has a beginning and that is the purpose of this course. You will learn the fundamentals of project management. This includes project performance, when to use the predictive or adaptive methodologies, business analysis domains, and frameworks, as well as the proper use of one of the various adaptive frameworks. Every career in project management has a beginning and that is the purpose of this course. You will learn the fundamentals of project management. This includes project performance, when to use the predictive or adaptive methodologies, business analysis domains, and frameworks, as well as the proper use of one of the various adaptive frameworks.

Duration 5 Days 30 CPD hours This course is intended for Entry- to mid-level network engineers Network administrators Network support technicians Help desk technicians Overview After taking this training, you should be able to: Illustrate the hierarchical network design model and architecture using the access, distribution, and core layers Compare and contrast the various hardware and software switching mechanisms and operation while defining the Ternary Content Addressable Memory (TCAM) and Content Addressable Memory (CAM) along with process switching, fast switching, and Cisco Express Forwarding concepts Troubleshoot Layer 2 connectivity using VLANs and trunking Implement redundant switched networks using Spanning Tree Protocol Troubleshoot link aggregation using Etherchannel Describe the features, metrics, and path selection concepts of Enhanced Interior Gateway Routing Protocol (EIGRP) Implement and optimize Open Shortest Path First (OSPF)v2 and OSPFv3, including adjacencies, packet types and areas, summarization, and route filtering for IPv4 and IPv6 Implement External Border Gateway Protocol (EBGP) interdomain routing, path selection, and single and dual-homed networking Implement network redundancy using protocols such as Hot Standby Routing Protocol (HSRP) and Virtual Router Redundancy Protocol (VRRP) Implement internet connectivity within Enterprise using static and dynamic Network Address Translation (NAT) Describe the virtualization technology of servers, switches, and the various network devices and components Implement overlay technologies such as Virtual Routing and Forwarding (VRF), Generic Routing Encapsulation (GRE), VPN, and Location Identifier Separation Protocol (LISP) Describe the components and concepts of wireless networking, including Radio Frequency (RF) and antenna characteristics, and define the specific wireless standards Describe the various wireless deployment models available, including autonomous Access Point (AP) deployments and cloud-based designs within the centralized Cisco Wireless LAN Controller (WLC) architecture Describe wireless roaming and location services The Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.3 training gives you the knowledge and skills needed to install, configure, operate, and troubleshoot an enterprise network and introduces you to overlay network design by using SD-Access and SD-WAN solutions. You?ll also learn to understand and implement security principles and automation and programmability within an enterprise network. Course Outline Examining Cisco Enterprise Network Architecture Exploring Cisco Switching Paths Implementing Campus LAN Connectivity Building Redundant Switched Topology Implementing Layer 2 Port Aggregation Understanding EIGRP Implementing OSPF Optimizing OSPF Exploring EBGP Implementing Network Redundancy Implementing NAT Introducing Virtualization Protocols and Techniques Understanding Virtual Private Networks and Interfaces Understanding Wireless Principles Examining Wireless Deployment Options Understanding Wireless Roaming and Location Services Examining Wireless AP Operation Implementing Wireless Client Authentication Troubleshooting Wireless Client Connectivity Implementing Network Services Using Network Analysis Tools Implementing Infrastructure Security Implementing Secure Access Control Discovering the Basics of Python Programming Discovering Network Programmability Protocols Implementing Layer 2 Port Aggregation Discovering Multicast Protocols Understanding QoS Exploring Enterprise Network Security Architecture Exploring Automation and Assurance Using Cisco DNA Center Examining the Cisco SD-Access Solution Understanding the Working Principles of the Cisco SD-WAN Solution

Duration 5 Days 30 CPD hours This course is intended for This course is designed for business professionals who leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming. However, there is not necessarily a single organizational role that this course targets. A prospective student might be a programmer looking to expand their knowledge of how to guide business decisions by collecting, wrangling, analyzing, and manipulating data through code; or a data analyst with a background in applied math and statistics who wants to take their skills to the next level; or any number of other data-driven situations. Ultimately, the target student is someone who wants to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business. Overview In this course, you will learn to: Use data science principles to address business issues. Apply the extract, transform, and load (ETL) process to prepare datasets. Use multiple techniques to analyze data and extract valuable insights. Design a machine learning approach to address business issues. Train, tune, and evaluate classification models. Train, tune, and evaluate regression and forecasting models. Train, tune, and evaluate clustering models. Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance. For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, it can also inform?by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice Addressing Business Issues with Data Science Topic A: Initiate a Data Science Project Topic B: Formulate a Data Science Problem Extracting, Transforming, and Loading Data Topic A: Extract Data Topic B: Transform Data Topic C: Load Data Analyzing Data Topic A: Examine Data Topic B: Explore the Underlying Distribution of Data Topic C: Use Visualizations to Analyze Data Topic D: Preprocess Data Designing a Machine Learning Approach Topic A: Identify Machine Learning Concepts Topic B: Test a Hypothesis Developing Classification Models Topic A: Train and Tune Classification Models Topic B: Evaluate Classification Models Developing Regression Models Topic A: Train and Tune Regression Models Topic B: Evaluate Regression Models Developing Clustering Models Topic A: Train and Tune Clustering Models Topic B: Evaluate Clustering Models Finalizing a Data Science Project Topic A: Communicate Results to Stakeholders Topic B: Demonstrate Models in a Web App Topic C: Implement and Test Production Pipelines

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Developers responsible for developing Deep Learning applications Developers who want to understand concepts behind Deep Learning and how to implement a Deep Learning solution on AWS Overview This course is designed to teach you how to: Define machine learning (ML) and deep learning Identify the concepts in a deep learning ecosystem Use Amazon SageMaker and the MXNet programming framework for deep learning workloads Fit AWS solutions for deep learning deployments In this course, you?ll learn about AWS?s deep learning solutions, including scenarios where deep learning makes sense and how deep learning works. You?ll learn how to run deep learning models on the cloud using Amazon SageMaker and the MXNet framework. You?ll also learn to deploy your deep learning models using services like AWS Lambda while designing intelligent systems on AWS. Module 1: Machine learning overview A brief history of AI, ML, and DL The business importance of ML Common challenges in ML Different types of ML problems and tasks AI on AWS Module 2: Introduction to deep learning Introduction to DL The DL concepts A summary of how to train DL models on AWS Introduction to Amazon SageMaker Hands-on lab: Spinning up an Amazon SageMaker notebook instance and running a multi-layer perceptron neural network model Module 3: Introduction to Apache MXNet The motivation for and benefits of using MXNet and Gluon Important terms and APIs used in MXNet Convolutional neural networks (CNN) architecture Hands-on lab: Training a CNN on a CIFAR-10 dataset Module 4: ML and DL architectures on AWS AWS services for deploying DL models (AWS Lambda, AWS IoT Greengrass, Amazon ECS, AWS Elastic Beanstalk) Introduction to AWS AI services that are based on DL (Amazon Polly, Amazon Lex, Amazon Rekognition) Hands-on lab: Deploying a trained model for prediction on AWS Lambda Additional course details: Nexus Humans Deep Learning on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Deep Learning on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.