458 Code courses in Bristol delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This course is primarily designed for students who want to gain the skills necessary to use VBA to automate tasks in Excel such as collecting data from external sources, cleaning, and manipulating data. The target student may also want to learn how to create custom worksheet functions to streamline worksheet formulas and make complex worksheets easier to support, maintain, and understand. Overview In this course, you will develop and deploy VBA modules to solve business problems. You will: Identify general components of VBA and their appropriate use in solving business solutions. Record VBA macros to automate repetitive tasks. Use reference tools built into Excel to get help on VBA programming language and objects used in the Excel VBA environment. Write VBA code to create a custom worksheet function. Eliminate, avoid, or handle errors in VBA code, and optimize its performance. Control how and when macros run. Develop UserForm objects to create custom dialog boxes and windows. Use VBA to read and write data from local files and cloud services. Use VBA to clean and transform data. Run programs and commands outside of Excel and share VBA projects with other users VBA (Visual Basic for Applications) enables you to enhance and extend the capabilities of Microsoft© Excel© and other applications in the Microsoft© Office application suite. You can use VBA to perform tasks that would be difficult or impossible to do using only worksheet functions, and you can automate a wide range of tasks involving the collection, processing, analysis, and visualization of data. This course will give you a good foundation for understanding, creating, and using VBA in your own Excel workbooks, show you how to work with data across different applications, and how to package the macros and functions you create so you can back them up, move them to other computers, and share them with other users Prerequisites To ensure your success in this course, you should be an experienced Excel user who is comfortable creating and working with Excel workbooks, including tasks such as entering worksheet formulas, using absolute and relative addressing, formatting cells, and creating pivot tables and charts. This level of skill could be acquired by taking the Microsoft Excel for Office 365? (Desktop or Online) courses, Parts 1, 2, and 3 1 - Using VBA to Solve Business Problems Topic A: Use Macros to Automate Tasks in Excel Topic B: Identify Components of Macro-Enabled Workbooks Topic C: Configure the Excel VBA Environment 2 - Automating Repetitive Tasks Topic A: Use the Macro Recorder to Create a VBA Macro Topic B: Record a Macro with Relative Addressing Topic C: Delete Macros and Modules Topic D: Identify Strategies for Using the Macro Recorder 3 - Getting Help on VBA Topic A: Use VBA Help Topic B: Use the Object Browser to Discover Objects You Can Use in VBA Topic C: Use the Immediate Window to Explore Object Properties and Methods 4 - Creating Custom Worksheet Functions Topic A: Create a Custom Function Topic B: Make Decisions in Code Topic C: Work with Variables Topic D: Perform Repetitive Tasks 5 - Improving Your VBA Code Topic A: Debug VBA Errors Topic B: Deal with Errors Topic C: Improve Macro Performance 6 - Controlling How and When Macros Run Topic A: Prompt the User for Information Topic B: Configure Macros to Run Automatically 7 - Developing Custom Forms Topic A: Display a Custom Dialog Box Topic B: Program Form Events 8 - Using VBA to Work with Files Topic A: Use VBA to Get File and Directory Structure Topic B: Use VBA to Read Text Files Topic C: Use VBA to Write Text Files 9 - Using VBA to Clean and Transform Data Topic A: Automate Power Query Topic B: Transform Data Using VBA and Workbook Functions Topic C: Use Regular Expressions Topic D: Manage Errors in Data 10 - Extending the Programming Environment Beyond the Workbook Topic A: Run Other Programs and Commands Topic B: Share Your VBA Projects

Duration 1 Days 6 CPD hours This course is intended for The audience for this course includes software developers and data scientists who need to use large language models for generative AI. Some programming experience is recommended, but the course will be valuable to anyone seeking to understand how the Azure OpenAI service can be used to implement generative AI solutions. Note Generative AI is a fast-evolving field of artificial intelligence, and the Azure OpenAI service is subject to frequent changes. The course materials are maintained to reflect the latest version of the service at the time of writing. Azure OpenAI Service provides access to OpenAI's powerful large language models such as GPT; the model behind the popular ChatGPT service. These models enable various natural language processing (NLP) solutions to understand, converse, and generate content. Users can access the service through REST APIs, SDKs, and Azure OpenAI Studio. In this course, you'll learn how to provision Azure OpenAI service, deploy models, and use them in generative AI applications. Prerequisites Familiarity with Azure and the Azure portal. Experience programming with C# or Python. 1 - 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 2 - Build natural language solutions with Azure OpenAI Service Integrate Azure OpenAI into your app Use Azure OpenAI REST API Use Azure OpenAI SDK 3 - Apply prompt engineering with Azure OpenAI Service Understand prompt engineering Write more effective prompts Provide context to improve accuracy 4 - Generate code with Azure OpenAI Service Construct code from natural language Complete code and assist the development process Fix bugs and improve your code 5 - 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 6 - 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 Additional course details: Nexus Humans AI-050T00: Develop Generative AI Solutions with Azure OpenAI Service 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 AI-050T00: Develop Generative AI Solutions with Azure OpenAI Service 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.

About this training course Business Impact: The main aim is to provide insight and understanding of data analytics and machine learning principles through applications. Field data is used to explain data-analysis workflows. Using easy to follow solution scripts, the participants will assess and extract value from the data sets. Hands-on solution approach will give them confidence to try out applicable techniques on data from their field assets. Data analysis means cleaning, inspecting, transforming, and modeling data with the goal of discovering new, useful information and supporting decision-making. In this hands-on 2-day training course, the participants learn some data analysis and data science techniques and workflows applied to petroleum production (specifically artificial lift) while reviewing code and practicing. The focus is on developing data-driven models while keeping our feet closer to the underlying oil and gas production principles. Unique Features: Eight business use cases covering their business impact, code walkthroughs for most all and solution approach. Industry data sets for participants to practice on and take home. No software or complicated Python frameworks required. Training Objectives After the completion of this training course, participants will be able to: Understand digital oil field transformation and its impact on business Examine machine learning methods Review workflows and code implementations After completing the course, participants will have a set of tools and some pathways to model and analyze their data in the cloud, find trends, and develop data-driven models Target Audience This training course is suitable and will greatly benefit the following specific groups: Artificial lift, production and facilities engineers and students to enhance their knowledge base, increase technology awareness, and improve the facility with different data analysis techniques applied on large data sets Course Level Intermediate Advanced Training Methods The course discusses several business use-cases that are amenable to data-driven workflows. For each use case, the instructor will show the solution using a data analysis technique with Python code deployed in the Google cloud. Trainees will solve a problem and tweak their solution. Course Duration: 2 days in total (14 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: Understanding of petroleum production concepts Knowledge of Python is not a must but preferred to get the full benefit. The training will use the Google Collaboratory environment available in Google-Cloud for hands-on exercises Trainees will need to bring a computer with a Google Chrome browser and a Google email account (available for free) Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. Developed a workshop on digital oilfield approaches for production engineers. Patents: Principal inventor: 'Smarter Slug Flow Conditioning and Control' Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations

Complete C# programming training course description This training course teaches developers the programming skills that are required for developers to create Windows applications using the C# language. Students review the basics of C# program structure, language syntax, and implementation details, and then consolidate their knowledge throughout the week as they build an application that incorporates several features of the .NET Framework. What will you learn Use the syntax and features of C#. Create and call methods, catch and handle exceptions, and describe the monitoring requirements of large-scale applications. Implement a typical desktop application. Create class, define and implement interfaces, and create and generic collections. Read and write data to/from files. Build a GUI using XAML. Complete C# programming training course details Who will benefit: Programmers wishing to learn C#. Prerequisites: Developers attending this course should already have gained some limited experience using C# to complete basic programming tasks. Duration 5 days Complete C# programming training course contents Review of C# Syntax Overview of Writing Applications using C#, Datatypes, Operators, and Expressions. C# Programming Language Constructs. Hands on Developing the Class Enrolment Application. Methods, exceptions and monitoring apps Creating and Invoking Methods. Creating Overloaded Methods and Using Optional and Output Parameters. Handling Exceptions. Monitoring Applications. Hands on Extending the Class Enrolment Application Functionality. Developing a graphical application Implementing Structs and Enums. Organizing Data into Collections. Handling Events. Hands on Writing the Grades Prototype Application. Classes and Type-safe collections Creating Classes. Defining and Implementing Interfaces. Implementing Type-safe Collections. Hands on Adding Data Validation and Type-safety to the Grades Application. Class hierarchy using Inheritance Class hierarchies. Extending .NET framework classes. Creating generic types. Hands on Refactoring common functionality into the User Class. Reading and writing local data Reading and Writing Files. Serializing and Deserializing Data. Performing I/O Using Streams. Hands on Generating the Grades Report. Accessing a Database Creating and using entity data models. Querying and updating data by using LINQ. Hands on Retrieving and modifying grade data. Accessing remote data Accessing data across the web and in the cloud. Hands on Modifying grade data in the Cloud. Designing the UI for a graphical applicatione Using XAML to design a User Interface. Binding controls to data. Styling a UI. Hands on Customizing Student Photographs and Styling the Application. Improving performance and responsiveness Implementing Multitasking by using tasks and Lambda Expressions. Performing operations asynchronously. Synchronizing concurrent data access. Hands on Improving the responsiveness and performance of the application. Integrating with unmanaged code Creating and using dynamic objects. Managing the Lifetime of objects and controlling unmanaged resources. Hands on Upgrading the grades report. Creating reusable types and assemblies Examining Object Metadata. Creating and Using Custom Attributes. Generating Managed Code. Versioning, Signing and Deploying Assemblies. Hands on Specifying the Data to Include in the Grades Report. Encrypting and Decrypting Data Implementing Symmetric Encryption. Implementing Asymmetric Encryption. Hands on Encrypting and Decrypting Grades Reports.

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

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

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.

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.

Objective-C programming training course description A hands on introduction that will allow you to master Objective-C and start using it to write powerful native applications for even the newest Macs and iOS devices! Using The step-by-step approach, will let you get comfortable with Objective-C's unique capabilities and Apple's Xcode 5 development environment. Make the most of Objective-C objects and messaging. Work effectively with design patterns, collections, blocks, foundation classes, threading, Git and a whole lot more. Every session builds on what you've already learned, giving a rock-solid foundation for real-world success! What will you learn Use Xcode 5. Declare classes, instance variables, properties, methods, and actions. Use arrays, dictionaries, and sets. Expand and extend classes with protocols, delegates, categories, and extensions. Use Apple's powerful classes and frameworks. Objective-C programming training course details Who will benefit: Developers wanting to learn Objective-C. Prerequisites: Software development fundamentals. Duration 5 days Objective-C programming training course contents PART 1: GETTING STARTED WITH OBJECTIVE-C The Developer Program: Objective-C, enrolling as an Apple Developer, setting up the development environment, Xcode. Your first project. OO programming with Objective-C: OO projects, Frameworks, classes and instances, encapsulation, accessors, Inheritance. OO features in Objective-C: Messages, methods, working with id, nesting messages, method signatures and parameters. allocating and initializing objects. Using Xcode: Xcode, source code control, git and Xcode, Using a Remote Repository. Compiler Directives: Projects, Compiler Directives, Prefix headers, main.m, .h files. PART 2: OBJECTIVE-C BASICS Messaging in a Testbed App: Setting Up the Testbed Apps, Adding a Text Field and Connecting It to Your Code, Sending a Message to the Text Field, Reviewing the Message Syntax. Declaring a Class in an Interface File: Context, Creating an Instance Variable with id, What Happens When Execution Stops, dynamic binding, Creating an Instance Variable for with the Class Name and with a Superclass Name, instance variable visibility. Properties in an Interface File: Interface Variables vs Properties, Declared Properties, Using Attributes. Implementing Properties. @synthesize, @dynamic. Methods in an Interface File: Methods in a Class, class and instance methods, Method declaration, returning complex data structures from Methods. Actions in an Interface File: Actions, Actions in OS X and iOS, disconnecting actions. Routing messages with selectors: Receiver and selector objects in messages, Objective-C Runtime, SEL and @selector (), performSelector, NSInvocation, testing whether an Instance can respond to a selector. Building on the Foundation: The Foundation Framework, Foundation Classes, Foundation Paradigms and Policies; Mutability, class clusters, notifications. Defining a Class in Implementation Files: Projects, dynamic typing, creating a new App, implementing a method, expanding Classses with init Methods. Organizing Data with Collections: Collecting Objects, Property Lists, Runtime, comparing the Collection Classes, Creating a Collection, Objective-C Literal Syntax, Enumerating collections, Testing Membership in a Collection, Accessing an Object in a Collection. Managing Memory and Runtime Objects: Managing objects in memory, managing reference counts manually and with ARC, variable qualifiers, variable autorelease. PART 3: EXPANDING AND EXTENDING CLASSES Protocols and Delegates: Subclassing, Protocols, Delegates, Looking Deeper Inside Protocols. Categories and Extensions: Comparing categories and protocols, categories vs subclasses, working with categories, class extensions, informal protocols. Associative References and Fast Enumeration: Objective-C 2.0 Time-Saving Features, Extending Classes by Adding Instance Variables (Sort of), Using Fast Enumeration. Blocks: Revisiting Blocks, Callbacks, Blocks, Exploring Blocks in Cocoa, Cocoa Blocks and Memory. PART 4: BEYOND THE BASICS Handling Exceptions and Errors: Exception and Error classes: NSException, NSError, Identifying exceptions, throwing exceptions, catching exceptions. Queues and Threading: Getting Started with Concurrency, Introducing Queues, Dispatch Sources, Using Dispatch Queues. Working with the Debugger: Logging Information, Console Logs, NSLog, Smart Breakpoints, enhancing breakpoints with messages. Using Xcode Debug Gauges for Analysis: Debug Gauges, Monitoing CPU and memory utilization, monitoring energy, Using Instruments. PART 5: OPTIONAL TOPICS C Syntax Summary: Data Types, Control Structures. Apps, Packages, and Bundles: Project Bundles, lproj Files, Asset Catalogs, plist Files, Precompiled Header Files (.pch). Archiving and Packaging Apps for Development and Testing: Archiving.