2686 Code courses in Birmingham delivered Online

Want to learn how to use Maven and SonarQube effectively for code building and code quality analysis as a DevOps engineer? Then you are in the right place. This learner-centered hands-on course will help you gain confidence in using important DevOps tools such as SVN, Maven, Jenkins, Chef, Puppet, Nagios, Splunk, Selenium, and more. Some basic knowledge of Linux, Git, and AWS EC2 will help you get the most out of this course.

Explore all the amazing things you can do with Google Apps Script with just a few lines of code, such as supercharge your Google Workspace apps, save time, and more. Learn how Google Apps Script allows you to interact with the Google Suite of products and create customized functionality within those products. You need to have prior coding experience to get started on this course.

Master Go programming with an in-depth course covering advanced topics such as authentication, authorization, JWT tokens, and refresh tokens. Learn how to write reliable code with effective unit testing techniques, while exploring concepts such as logging, error handling, and modularization. Build secure and scalable web applications with Go to take your coding expertise to the next level.

Duration 4 Days 24 CPD hours This course is intended for Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure. AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language. Prerequisites Before attending this course, students must have: Knowledge of Microsoft Azure and ability to navigate the Azure portal Knowledge of either C# or Python Familiarity with JSON and REST programming semantics Recommended course prerequisites AI-900T00: Microsoft Azure AI Fundamentals course 1 - Prepare to develop AI solutions on Azure Define artificial intelligence Understand AI-related terms Understand considerations for AI Engineers Understand considerations for responsible AI Understand capabilities of Azure Machine Learning Understand capabilities of Azure AI Services Understand capabilities of the Azure Bot Service Understand capabilities of Azure Cognitive Search 2 - Create and consume Azure AI services Provision an Azure AI services resource Identify endpoints and keys Use a REST API Use an SDK 3 - Secure Azure AI services Consider authentication Implement network security 4 - Monitor Azure AI services Monitor cost Create alerts View metrics Manage diagnostic logging 5 - Deploy Azure AI services in containers Understand containers Use Azure AI services containers 6 - Analyze images Provision an Azure AI Vision resource Analyze an image Generate a smart-cropped thumbnail 7 - Classify images Provision Azure resources for Azure AI Custom Vision Understand image classification Train an image classifier 8 - Detect, analyze, and recognize faces Identify options for face detection analysis and identification Understand considerations for face analysis Detect faces with the Azure AI Vision service Understand capabilities of the face service Compare and match detected faces Implement facial recognition 9 - Read Text in images and documents with the Azure AI Vision Service Explore Azure AI Vision options for reading text Use the Read API 10 - Analyze video Understand Azure Video Indexer capabilities Extract custom insights Use Video Analyzer widgets and APIs 11 - Analyze text with Azure AI Language Provision an Azure AI Language resource Detect language Extract key phrases Analyze sentiment Extract entities Extract linked entities 12 - Build a question answering solution Understand question answering Compare question answering to Azure AI Language understanding Create a knowledge base Implement multi-turn conversation Test and publish a knowledge base Use a knowledge base Improve question answering performance 13 - Build a conversational language understanding model Understand prebuilt capabilities of the Azure AI Language service Understand resources for building a conversational language understanding model Define intents, utterances, and entities Use patterns to differentiate similar utterances Use pre-built entity components Train, test, publish, and review a conversational language understanding model 14 - Create a custom text classification solution Understand types of classification projects Understand how to build text classification projects 15 - Create a custom named entity extraction solution Understand custom named entity recognition Label your data Train and evaluate your model 16 - Translate text with Azure AI Translator service Provision an Azure AI Translator resource Specify translation options Define custom translations 17 - Create speech-enabled apps with Azure AI services Provision an Azure resource for speech Use the Azure AI Speech to Text API Use the text to speech API Configure audio format and voices Use Speech Synthesis Markup Language 18 - Translate speech with the Azure AI Speech service Provision an Azure resource for speech translation Translate speech to text Synthesize translations 19 - Create an Azure AI Search solution Manage capacity Understand search components Understand the indexing process Search an index Apply filtering and sorting Enhance the index 20 - Create a custom skill for Azure AI Search Create a custom skill Add a custom skill to a skillset 21 - Create a knowledge store with Azure AI Search Define projections Define a knowledge store 22 - Plan an Azure AI Document Intelligence solution Understand AI Document Intelligence Plan Azure AI Document Intelligence resources Choose a model type 23 - Use prebuilt Azure AI Document Intelligence models Understand prebuilt models Use the General Document, Read, and Layout models Use financial, ID, and tax models 24 - Extract data from forms with Azure Document Intelligence What is Azure Document Intelligence? Get started with Azure Document Intelligence Train custom models Use Azure Document Intelligence models Use the Azure Document Intelligence Studio 25 - Get started with Azure OpenAI Service Access Azure OpenAI Service Use Azure OpenAI Studio Explore types of generative AI models Deploy generative AI models Use prompts to get completions from models Test models in Azure OpenAI Studio's playgrounds 26 - Build natural language solutions with Azure OpenAI Service Integrate Azure OpenAI into your app Use Azure OpenAI REST API Use Azure OpenAI SDK 27 - Apply prompt engineering with Azure OpenAI Service Understand prompt engineering Write more effective prompts Provide context to improve accuracy 28 - Generate code with Azure OpenAI Service Construct code from natural language Complete code and assist the development process Fix bugs and improve your code 29 - Generate images with Azure OpenAI Service What is DALL-E? Explore DALL-E in Azure OpenAI Studio Use the Azure OpenAI REST API to consume DALL-E models 30 - Use your own data with Azure OpenAI Service Understand how to use your own data Add your own data source Chat with your model using your own data 31 - Fundamentals of Responsible Generative AI Plan a responsible generative AI solution Identify potential harms Measure potential harms Mitigate potential harms Operate a responsible generative AI solution

Learn GitHub Actions in a weekend! This course covers all the important concepts to help you master GitHub Actions and its practical applications. Gain in-demand skills, design a CI/CD pipeline, and deploy infra as code with GitHub Actions. Boost your career with this essential skill for DevOps practices.

Master Python 3.10 from the experts with this course and demonstrate programming wizardry in Python. Go from a geek to a wizard in no time with this well-structured video course and write Python code like a pro. Learn about the often-forgotten basics and special features of programming and Python in general.

Advanced Python training course description This course caters to network engineers aiming to enhance both their Python proficiency and network automation skills. Delving deeper into key areas such as netmiko, Nornir, and ncclient, we also focus on automating network testing and validation. Participants gain greater confidence working with Python functions, classes, objects, and error handling. The course additionally introduces more libraries like Scrapli, TTP, pyATS, Genie, pybatfish, and Suzieq, which cover parsing strategies, automation testing, validation, network analysis, observability, and telemetry. The curriculum also encompasses concurrency techniques. What will you learn Write Python modules and functions. Evaluate techniques to parse unstructured data. Use NETCONF filters. Handle Python errors effectively (try, assert…). Use postman. Automate testing and validation of the network. Use scrapli, Genie, batfish and Suzieq. Advanced Python training course details Who will benefit: Network engineers. Prerequisites: Python for network engineers Duration 5 days Advanced Python training course contents Review CLI, NETCONF, RESTCONF, structured versus unstructured data, gNMI and when to use which. PEP 8. Naming conventions. Packages, modules, Classes and methods. The scrapli library. Netmiko versus scrapli. Hands on: scrapli, Dictionaries versus Regular Expressions. Modules and Functions Writing your own modules, containers versus packages, virtual environments. Best practices, calling functions, writing your own functions. Parameters, arguments. Named arguments, dictionaries as arguments. Builtins. Docstrings. Main. __name__, __main__ . Program arguments. Hands on: Getting interfaces, showing interface status using Netmiko and functions. Using dictionaries as arguments. Writing your own modules. Parsing strategies Turning unstructured data into structured data. textfsm, PyATS Genie parser, NAPALM getters, Template Text Parser. Hands on: Genie parser, TTP. Accessing structured data with lists and dictionaries. Classes, objects and Python Python classes in Genie, PyEZ and others . Hands on: studying network automation classes, objects, methods and attributes. Configuration management - more nornir, ncclient, requests Nornir tasks. Nornir results, Nornir functions, Nornir plugins. Nornir processors. YANG, YANG models, pyang. NETCONF hello. Capabilities. Schemas. Filters. Subtrees. XPATH. Exploring available YANG data models. NETCONF and network wide transactions. Asserting NETCONF capabilities. Configuration types. Locking configurations, commits. NETCONF data stores. Netconf-console. RESTCONF differences from NETCONF. URI construction. Postman. More XML and JSON. Git and configuration versions. Hands on: Nornir and Jinja2. Exploring available models, NETCONF filters. Using postman. Python error handling and debugging Context handlers, try, assert, logging, pdb, pytest, unit testing, chatgpt. Hands on: Writing code with each of the error handling methods, investigating what happens on an error. Use chatgpt to debug your code. Python Automation Testing Testing and validation. pyATS, Genie. Testbed file. Genie parse, genie learn, genie diff. Genie conf, Genie ops, Genie SDK, Genie harness. Xpresso. Hands on: Using Genie for state comparisons of the network. Network analysis Batfish, pybatfish, configuration analysis, analysing routing, analysing ACLs. Pandas. Pandas dataframe. Filtering and selecting values of interest. Hands on: Use Batfish to analyse network snapshots, find network adjacencies, flow path analysis. Network observability Suzieq, using docker, using as a package. Sqpoller, suzieq-gui, suzieq-cli, sq-rest-server. Namespaces and seeing devices, network state and Asserts. Time based analysis, snapshots and changes. Hands on: Suzieq: Gathering data from the network, analysing data from the network. Network state assertion. Telemetry gRPC, gNMI. CAP, GET, SET. Subscriptions. Model Driven telemetry. Hands on: Analysing telemetry data with Python. Concurrency asyncio, threads, processes. Nornir concurrency. Scrapli and netmiko concurrency. Hands on: Multiple SSH connections to devices at same time. Scarpli asyncio.

Duration 4 Days 24 CPD hours This course is intended for Students in this course are interested in designing and implementing DevOps processes or in passing the Microsoft Azure DevOps Solutions certification exam. This course provides the knowledge and skills to design and implement DevOps processes and practices. Students will learn how to plan for DevOps, use source control, scale Git for an enterprise, consolidate artifacts, design a dependency management strategy, manage secrets, implement continuous integration, implement a container build strategy, design a release strategy, set up a release management workflow, implement a deployment pattern, and optimize feedback mechanisms Prerequisites Successful learners will have prior knowledge and understanding of: Cloud computing concepts, including an understanding of PaaS, SaaS, and IaaS implementations. Both Azure administration and Azure development with proven expertise in at least one of these areas. Version control, Agile software development, and core software development principles. It would be helpful to have experience in an organization that delivers software. AZ-104T00 - Microsoft Azure Administrator AZ-204T00: Developing Solutions for Microsoft Azure 1 - Introduction to DevOps What is DevOps? Explore the DevOps journey Identify transformation teams Explore shared goals and define timelines 2 - Choose the right project Explore greenfield and brownfield projects Decide when to use greenfield and brownfield projects Decide when to use systems of record versus systems of engagement Identify groups to minimize initial resistance Identify project metrics and key performance indicators (KPIs) 3 - Describe team structures Explore agile development practices Explore principles of agile development Define organization structure for agile practices Explore ideal DevOps team members Enable in-team and cross-team collaboration Select tools and processes for agile practices 4 - Choose the DevOps tools What is Azure DevOps? What is GitHub? Explore an authorization and access strategy Migrate or integrate existing work management tools Migrate or integrate existing test management tools Design a license management strategy 5 - Plan Agile with GitHub Projects and Azure Boards Link GitHub to Azure Boards Configure GitHub Projects Manage work with GitHub Project boards Customize Project views Collaborate using team discussions Agile Plan and Portfolio Management with Azure Boards 6 - Introduction to source control Explore DevOps foundational practices What is source control? Explore benefits of source control Explore best practices for source control 7 - Describe types of source control systems Understand centralized source control Understand distributed source control Explore Git and Team Foundation Version Control Examine and choose Git Understand objections to using Git Describe working with Git locally 8 - Work with Azure Repos and GitHub Migrate from TFVC to Git Use GIT-TFS Develop online with GitHub Codespaces 9 - Structure your Git Repo Explore monorepo versus multiple repos Implement a change log 10 - Manage Git branches and workflows Explore branch workflow types Explore feature branch workflow Explore Git branch model for continuous delivery Explore GitHub flow Explore fork workflow Version Control with Git in Azure Repos 11 - Collaborate with pull requests in Azure Repos Collaborate with pull requests Examine GitHub mobile for pull request approvals 12 - Identify technical debt Examine code quality Examine complexity and quality metrics Measure and manage technical debt Integrate other code quality tools Plan effective code reviews 13 - Explore Git hooks Implement Git hooks 14 - Plan foster inner source Explore foster inner source Implement the fork workflow Describe inner source with forks 15 - Manage Git repositories Work with large repositories Purge repository data Manage releases with GitHub Repos Automate release notes with GitHub 16 - Explore Azure Pipelines Explore the concept of pipelines in DevOps Describe Azure Pipelines Understand Azure Pipelines key terms 17 - Manage Azure Pipeline agents and pools Choose between Microsoft-hosted versus self-hosted agents Explore job types Explore predefined agent pool Understand typical situations for agent pools Communicate with Azure Pipelines Communicate to deploy to target servers Examine other considerations Describe security of agent pools Configure agent pools and understanding pipeline styles 18 - Describe pipelines and concurrency Understand parallel jobs Estimate parallel jobs Describe Azure Pipelines and open-source projects Explore Azure Pipelines and Visual Designer Describe Azure Pipelines and YAML 19 - Explore continuous integration Learn the four pillars of continuous integration Explore benefits of continuous integration Describe build properties Enable Continuous Integration with Azure Pipelines 20 - Implement a pipeline strategy Configure agent demands Implement multi-agent builds Explore source control types supported by Azure Pipelines 21 - Integrate with Azure Pipelines Describe the anatomy of a pipeline Understand the pipeline structure Detail templates Explore YAML resources Use multiple repositories in your pipeline 22 - Introduction to GitHub Actions What are Actions? Explore Actions flow Understand workflows Describe standard workflow syntax elements Explore events Explore jobs Explore runners Examine release and test an action 23 - Learn continuous integration with GitHub Actions Describe continuous integration with actions Examine environment variables Share artifacts between jobs Examine Workflow badges Describe best practices for creating actions Mark releases with Git tags Create encrypted secrets Use secrets in a workflow Implement GitHub Actions for CI/CD 24 - Design a container build strategy Examine structure of containers Work with Docker containers Understand Dockerfile core concepts Examine multi-stage dockerfiles Examine considerations for multiple stage builds Explore Azure container-related services Deploy Docker containers to Azure App Service web apps 25 - Introduction to continuous delivery Explore traditional IT development cycle What is continuous delivery? Move to continuous delivery Understand releases and deployments Understand release process versus release 26 - Create a release pipeline Describe Azure DevOps release pipeline capabilities Explore release pipelines Explore artifact sources Choose the appropriate artifact source Examine considerations for deployment to stages Explore build and release tasks Explore custom build and release tasks Explore release jobs Configure Pipelines as Code with YAML 27 - Explore release recommendations Understand the delivery cadence and three types of triggers Explore release approvals Explore release gates Use release gates to protect quality Control Deployments using Release Gates 28 - Provision and test environments Provision and configure target environments Configure automated integration and functional test automation Understand Shift-left Set up and run availability tests Explore Azure Load Testing Set up and run functional tests 29 - Manage and modularize tasks and templates Examine task groups Explore variables in release pipelines Understand variable groups 30 - Automate inspection of health Automate inspection of health Explore events and notifications Explore service hooks Configure Azure DevOps notifications Configure GitHub notifications Explore how to measure quality of your release process Examine release notes and documentation Examine considerations for choosing release management tools Explore common release management tools 31 - Introduction to deployment patterns Explore microservices architecture Examine classical deployment patterns Understand modern deployment patterns 32 - Implement blue-green deployment and feature toggles What is blue-green deployment? Explore deployment slots Describe feature toggle maintenance 33 - Implement canary releases and dark launching Explore canary releases Examine Traffic Manager Understand dark launching 34 - Implement A/B testing and progressive exposure deployment What is A/B testing? Explore CI-CD with deployment rings 35 - Integrate with identity management systems Integrate GitHub with single sign-on (SSO) Explore service principals Explore Managed Identity 36 - Manage application configuration data Rethink application configuration data Explore separation of concerns Understand external configuration store patterns Examine Key-value pairs Examine App configuration feature management Integrate Azure Key Vault with Azure Pipelines Manage secrets, tokens and certificates Examine DevOps inner and outer loop Integrate Azure Key Vault with Azure DevOps Enable Dynamic Configuration and Feature Flags 37 - Explore infrastructure as code and configuration management Explore environment deployment Examine environment configuration Understand imperative versus declarative configuration Understand idempotent configuration 38 - Create Azure resources using Azure Resource Manager templates Why use Azure Resource Manager templates? Explore template components Manage dependencies Modularize templates Manage secrets in templates Deployments using Azure Bicep templates 39 - Create Azure resources by using Azure CLI What is Azure CLI? Work with Azure CLI 40 - Explore Azure Automation with DevOps Create automation accounts What is a runbook? Understand automation shared resources Explore runbook gallery Examine webhooks Explore source control integration Explore PowerShell workflows Create a workflow Examine checkpoint and parallel processing 41 - Implement Desired State Configuration (DSC) Understand configuration drift Explore Desired State Configuration (DSC) Explore Azure Automation State configuration (DSC) Examine DSC configuration file Explore hybrid management Implement DSC and Linux Automation on Azure 42 - Implement Bicep What is Bicep? Install Bicep Understand Bicep file structure and syntax 43 - Introduction to Secure DevOps Describe SQL injection attack Understand DevSecOps Explore Secure DevOps Pipeline Explore key validation points Explore continuous security validation Understand threat modeling 44 - Implement open-source software Explore how software is built What is open-source software Explore corporate concerns with open-source software components Explore common open-source licenses Examine license implications and ratings 45 - Software Composition Analysis Inspect and validate code bases for compliance Explore software composition analysis (SCA) Integrate Mend with Azure Pipelines Implement GitHub Dependabot alerts and security updates Integrate software composition analysis checks into pipelines Examine tools for assess package security and license rate Interpret alerts from scanner tools Implement security and compliance in an Azure Pipeline 46 - Static analyzers Explore SonarCloud Explore CodeQL in GitHub Manage technical debt with SonarCloud and Azure DevOps 47 - OWASP and Dynamic Analyzers Plan Implement OWASP Secure Coding Practices Explore OWASP ZAP penetration test Explore OWASP ZAP results and bugs 48 - Security Monitoring and Governance Implement pipeline security Explore Microsoft Defender for Cloud Examine Microsoft Defender for Cloud usage scenarios Explore Azure Policy Understand policies Explore initiatives Explore resource locks Explore Azure Blueprints Understand Microsoft Defender for Identity 49 - Explore package dependencies What is dependency management? Describe elements of a dependency management strategy Identify dependencies Understand source and package componentization Decompose your system Scan your codebase for dependencies 50 - Understand package management Explore packages Understand package feeds Explore package feed managers Explore common public package sources Explore self-hosted and SaaS based package sources Consume packages Publish packages Package management with Azure Artifacts 51 - Migrate consolidating and secure artifacts Identify existing artifact repositories Migrate and integrating artifact repositories Secure access to package feeds Examine roles Examine permissions Examine authentication 52 - Implement a versioning strategy Understand versioning of artifacts Explore semantic versioning Examine release views Promote packages Explore best practices for versioning 53 - Introduction to GitHub Packages Publish packages Install a package Delete and restore a package Explore package access control and visibility 54 - Implement tools to track usage and flow Understand the inner loop Explore Azure Monitor and Log Analytics Examine Kusto Query Language (KQL) Explore Application Insights Implement Application Insights Monitor application performance with Application Insights 55 - Develop monitor and status dashboards Explore Azure Dashboards Examine view designer in Azure Monitor Explore Azure Monitor workbooks Explore Power BI Build your own custom application 56 - Share knowledge within teams Share acquired knowledge within development teams Integrate with Azure Boards Share team knowledge using Azure Project Wiki 57 - Design processes to automate application analytics Explore rapid responses and augmented search Integrate telemetry Examine monitoring tools and technologies 58 - Manage alerts, blameless retrospectives and a just culture Examine when get a notification Explore how to fix it Explore smart detection notifications Improve performance Understand server response time degradation Reduce meaningless and non-actionable alerts Examine blameless retrospective Develop a just culture

Registration starts at 7:30 AM. The training will begin promptly at 8:00 AM. Please plan your arrival accordingly to ensure you don't miss any important information. Reduce Emissions, Save Costs, Earn a CPC Hours, and Ensure Full Compliance Topics Covered: FORS Lo-CITY Driver Training (3.5 hours): • Relationship between driving style, fuel consumption, and environmental impact • Benefits of regular vehicle maintenance and checks • Fuel-efficient driving techniques • Utilising in-vehicle technology for fuel economy • Benefits of journey planning • Alternative fuels for commercial vehicles Highway Code Training Content: Course introduction, objectives, and expectations. Introduction to the Highway Code and its relevance. Types of road users and training for various groups. Respecting and understanding the risks to different road user categories. Confirmation of knowledge quizzes covering all aspects of the Highway Code and traffic regulations. Course Details: Format: Remote Session (7 hours) CPC Hours: Yes Cost: £89.50 - Includes course fee, Driver CPC Upload fee, VAT This award-winning program (awarded the prestigious Education in Transport award at the 2017 National Courier Awards) is perfect for any fleet operator looking to: Meet FORS Gold accreditation requirements. Improve driver performance and fuel efficiency. Reduce their environmental footprint. Enhance corporate social responsibility. Please note that this course is delivered online and provides 7 hours of Driver CPC training. Ready to get started? Book online or feel free to contact our training department at training@totalcompliance.co.uk or call 0345 9001312 to register for this valuable course. Please review our Terms and Conditions for more information.

Software development training course description This three-day MTA Training course helps you prepare for Microsoft Technology Associate Exam 98-361, and build an understanding of these topics: Core programming, Object-Oriented programming, general software development, web applications, desktop applications, and databases. This course leverages the same content as found in the Microsoft Official Academic Course (MOAC) for this exam. What will you learn Describe core programming. Explain Object Oriented programming. Describe general software development. Describe Web applications. Describe desktop applications. Explain how databases work. Software development training course details Who will benefit: Anyone looking to learn the fundamentals of software. Prerequisites: None. Duration 3 days Software development training course contents Core programming Computer storage and data types How a computer stores programs and the instructions in computer memory, memory stacks and heaps, memory size requirements for the various data storage types, numeric data and textual data. Computer decision structures Various decision structures used in all computer programming languages; If decision structures; multiple decision structures, such as If…Else and switch/Select Case; reading flowcharts; decision tables; evaluating expressions. Handling repetition For loops, While loops, Do...While loops and recursion. Understand error handling Structured exception handling. Object-oriented programming Classes Properties, methods, events and constructors; how to create a class; how to use classes in code. Inheritance Inheriting the functionality of a base class into a derived class. Polymorphism Extending the functionality in a class after inheriting from a base class, overriding methods in the derived class. Encapsulation Creating classes that hide their implementation details while still allowing access to the required functionality through the interface, access modifiers. General software development Application life cycle management Phases of application life cycle management, software testing. Interpret application specifications Application specifications, translating them into prototypes, code, select appropriate application type and components. Algorithms and data structures Arrays, stacks, queues, linked lists and sorting algorithms; performance implications of various data structures; choosing the right data structure. Web applications Web page development HTML, CSS, JavaScript. ASP.NET web application development Page life cycle, event model, state management, client-side versus server-side programming. Web hosting Creating virtual directories and websites, deploying web applications, understanding the role of Internet Information Services. Web services Web services that will be consumed by client applications, accessing web services from a client application, SOAP, WSDL. Desktop applications Windows apps UI design guideline categories, characteristics and capabilities of Store Apps, identify gestures. Console-based applications Characteristics and capabilities of console- based applications. Windows Services Characteristics and capabilities of Windows Services. Databases Relational database management systems Characteristics and capabilities of database products, database design, ERDs, normalisation concepts. Database query methods SQL, creating and accessing stored procedures, updating and selecting data. Database connection methods Connecting to various types of data stores, such as flat file; XML file; in-memory object; resource optimisation.