2986 Software Development courses delivered Online

Introduction to Agile and Scrum: Virtual In-House Training This half-day course provides an overview of Agile principles and mindset, and the Scrum framework as a key Agile approach. It will provide you with the key benefits of an Agile approach, and its differences with the traditional Waterfall method. Lastly, as Agile is looked upon more frequently as an alternative delivery method, you will review situations where Agile can be adapted outside of software development, where it is most commonly used. What you will Learn At the end of this program, you will be able to: Explain the basics and benefits of using an Agile approach Describe the Scrum framework, its events, artifacts and roles and responsibilities Illustrate Agile approaches outside of Software Development Getting Started Introduction Course structure Course goals and objectives Agile Introduction What is Agile? Agile Benefits Agile Methods Overview of Scrum Scrum Overview Scrum Events Scrum Artifacts Scrum Roles Definition of Done Agile Approaches Outside of Software Development Agile in other environments Product Development Course Development Marketing Agile Project Candidates Summary What Agile is not... Concerns and Pitfalls

Introduction to Agile and Scrum: In-House Training This half-day course provides an overview of Agile principles and mindset, and the Scrum framework as a key Agile approach. It will provide you with the key benefits of an Agile approach, and its differences with the traditional Waterfall method. Lastly, as Agile is looked upon more frequently as an alternative delivery method, you will review situations where Agile can be adapted outside of software development, where it is most commonly used. What you will Learn At the end of this program, you will be able to: Explain the basics and benefits of using an Agile approach Describe the Scrum framework, its events, artifacts and roles and responsibilities Illustrate Agile approaches outside of Software Development Getting Started Introduction Course structure Course goals and objectives Agile Introduction What is Agile? Agile Benefits Agile Methods Overview of Scrum Scrum Overview Scrum Events Scrum Artifacts Scrum Roles Definition of Done Agile Approaches Outside of Software Development Agile in other environments Product Development Course Development Marketing Agile Project Candidates Summary What Agile is not... Concerns and Pitfalls

ISTQB® FOUNDATION TRAINING COURSE (2 persons minimum) The aim of this course is to provide you with the knowledge and skills to pass an exam certifying you as an ISTQB® Certified Tester - Foundation Level. Most organisations require this certification as a minimum skill requirement for software testers. In this course you will learn a standardized approach to software testing that will be immediately applicable to your projects. In order to get the certification you will be required to pass a 60-minute exam. Our trainers will fully prepare you by employing scenarios that mirror the exam questions, and by focusing course delivery with a balance of theory and practice. Target group: Functional Tester, Agile Tester, User Acceptance Tester, Test Automation Specialist, Performance Testing Specialist, Testing Team Lead, Test Manager, Business analyst Prerequisites: There are no specific prerequisites for this course. This course is suitable for anyone involved in software testing. Duration: 3 days. Training objectives: Learn aspects of test planning, estimation, monitoring and control. Understand and use international standards and terminology. Understand and implement effective testing techniques. Be well prepared for the exam. Identify the missing testing skills for the career development purposes. This course covers the following areas: Fundamentals of software testing Testing throughout the life cycle (software development models, test levels, test types) Test design techniques (e.g. specification-based or black-box techniques, structure-based or white-box techniques) Static testing (static testing techniques, review process, tool-assisted static analysis) Test management (test organisation, test planning and estimation, test progress monitoring and control, risks) Tools to support testing (types, benefits and risks) Language: English

Unlock Your Potential with the C# Coding & SQL Programming Bundle! Elevate your skills with this comprehensive bundle of 20 courses that dive deep into the realms of C# coding and SQL programming. With a focus on practical application, these courses are designed to equip you with the tools you need to succeed in today's tech-driven world. Learning Outcome: Master C# coding fundamentals for versatile software development. Develop advanced C# applications and programs with ease. Harness the power of SQL programming to manage and manipulate data. Create web GIS applications using C# ASP.NET CORE MVC and Leaflet. Build AutoCAD programs and integrate them with SQL databases. Gain expertise in LINQ, ADO.NET, and other essential coding techniques. Create Excel and Word Add-ins using C# for enhanced productivity. Develop a solid foundation in SQL for data science and analytics. Immerse yourself in the dynamic landscape of C# coding and SQL programming through this bundle of expertly crafted courses. Whether you're a beginner looking to establish a strong foundation or an experienced developer aiming to refine your skills, this bundle has something for everyone. Delve into interactive hands-on projects and gain practical insights that will set you apart in the competitive tech industry. CPD 190 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Aspiring software developers seeking proficiency in C# and SQL. Current developers aiming to expand their skill set. Tech enthusiasts who want to embark on a coding and programming journey. Career path Junior C# Developer: £30,000 - £45,000 SQL Database Administrator: £35,000 - £50,000 Web Application Developer: £40,000 - £55,000 Software Engineer: £45,000 - £65,000 Data Analyst with SQL Skills: £35,000 - £50,000 Certificates Digital certificate Digital certificate - Included Hard copy certificate Hard copy certificate - Included

Agile for Non-IT Practitioners - How Agile Project Management is Different and How It Can be Used for Non-IT Projects (On-Demand) As a Project Management Institute (PMI)®Registered Education Provider (R.E.P.), IIL has agreed to abide by PMI®-established quality assurance criteria. In today's world of fast paced technology, continually changing requirements and project scope, the need for Agile Project Management has greatly increased. Responding to this demand, the Project Management Institute (PMI®) launched the PMI Agile Certified Practitioner (PMI-ACP)®certification. A result of this certification is the creation of a new space where Project Management and Agile Practices for Software Development meet. The foundation of Agile is the Agile Manifesto for Software Development. Agile has been used for software development for a number of years, even prior to the creation of the Agile Manifesto in 2001. The success of Agile for software development projects has piqued interest in successfully employing Agile in many other fields. How can Agile practices be used for projects which are not software or IT in nature? This course will provide guidance on how Agile can be used beyond software development projects, including how it differs from traditional project management. The course also will provide an overview of the Agile Scrum framework, which is one of the most popular Agile methodologies used. This course provides practical skills, concepts, and principles you can take back to the job and use to implement Agile practices in projects, as applicable. The goal of this course is to acquaint participants with the concepts of agile development methods and the specifics of the Scrum management framework. At the end of this course, participants will understand: Agile Practices - what makes Agile projects 'agile' Scrum and how Scrum applies to the Agile Practices Specific Agile practices which you can use to improve the execution of your projects Practices which can be used in conjunction with Scrum for Non-IT projects Course goal and objectives Importance of Agile development and project management What Agile is and is not Faster, better, cheaper Delivers better fit for purpose Agile versus Waterfall and the big paradigm shift Agile characteristics, behaviors, approaches Agile concerns and pitfalls Introducing Agile Overview of Agile Agile values and principles Overview of Scrum Scrum methodology Scrum terminology Scrum Framework Scrum roles Scrum meetings Sprints Requirements and Product Definition User stories Product backlog Planning Agile Estimating in Scrum Sprint planning session Release planning Agile Practices Agile development Analysis practices Validation practices Other practices Running a Sprint Conducting a Sprint Negotiating changes Tracking progress End of Spring meetings Release planning Closing the project

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 1 Days 6 CPD hours This course is intended for To gain the most from attending this course you should possess the following incoming skills: Basic knowledge of programming concepts and syntax in Python. Familiarity with common data formats such as CSV, JSON, and XML. Experience using command-line interfaces and basic text editing tools. Understanding of basic machine learning concepts and algorithms. Overview Working in an interactive learning environment, led by our engaging expert, you will: Gain a solid understanding of prompt engineering concepts and their applications in software development and AI-driven solutions. Master the techniques for preprocessing and cleaning text data to ensure high-quality inputs for AI models like GPT-4. Develop expertise in GPT-4 tokenization, input formatting, and controlling model behavior for various tasks and requirements. Acquire the ability to design, optimize, and test prompts effectively, catering to diverse business applications and use cases. Learn advanced prompt engineering techniques, such as conditional text generation and multi-turn conversations, to create more sophisticated AI solutions. Practice creating prompts to generate, run, and test code in a chosen programming language using GPT-4 and OpenAI Codex. Understand the ethical implications and best practices in responsible AI deployment, ensuring fair and unbiased AI applications in software development. Prompt Engineering offers coders and software developers a competitive edge by empowering them to develop more effective and efficient AI-driven solutions in their projects. By harnessing the capabilities of cutting-edge AI models like GPT-4, coders can automate repetitive tasks, enhance natural language understanding, and even generate code suggestions, boosting productivity and creativity. In addition, mastering prompt engineering can contribute to improved job security, as professionals with these in-demand skills are highly sought after in the rapidly evolving tech landscape. Quick Start to Prompt Engineering for Coders and Software Developers is a one day course designed to get you quickly up and running with the prompting skills required to out AI to work for you in your development efforts. Guided by our AI expert, you?ll explore key topics such as text preprocessing, data cleansing, GPT-4 tokenization, input formatting, prompt design, and optimization, as well as ethical considerations in prompt engineering. In the hands-on labs you?ll explore tasks such as formatting inputs for GPT-4, designing and optimizing prompts for business applications, and implementing multi-turn conversations with AI. You?ll work with innovative tools like the OpenAI API, OpenAI Codex, and OpenAI Playground, enhancing your learning experience while preparing you for integrating prompt engineering into your professional toolkit. By the end of this immersive course, you?ll have the skills necessary to effectively use prompt engineering in your software development projects. You'll be able to design, optimize, and test prompts for various business tasks, integrate GPT-4 with other software platforms, and address ethical concerns in AI deployment. Introduction to Prompt Engineering Overview of prompt engineering and its importance in AI applications Major applications of prompt engineering in business Common challenges faced in prompt engineering Overview of GPT-4 and its role in prompt engineering Key terminology and concepts in prompt engineering Getting Things Ready: Text Preprocessing and Data Cleansing Importance of data preprocessing in prompt engineering Techniques for text cleaning and normalization Tokenization and n-grams Stop word removal and stemming Regular expressions and pattern matching GPT-4 Tokenization and Input Formatting GPT-4 tokenization and its role in prompt engineering Understanding and formatting GPT-4 inputs Context windows and token limits Controlling response length and quality Techniques for handling out-of-vocabulary tokens Prompt Design and Optimization Master the skills to design, optimize, and test prompts for various business tasks. Designing effective prompts for different tasks Techniques for prompt optimization GPT-4 system and user parameters for controlling behavior Importance of prompt testing and iteration Best practices for prompt engineering in business applications Advanced Techniques and Tools in Prompt Engineering Learn advanced techniques and tools for prompt engineering and their integration in business applications. Conditional text generation with GPT-4 Techniques for handling multi-turn conversations Overview of tools for prompt engineering: OpenAI API, OpenAI Codex, and OpenAI Playground Integration of GPT-4 with other software platforms and tools Monitoring and maintaining prompt performance Code Generation and Testing with Prompt Engineering Develop the skills to generate, integrate, and test AI-generated code effectively, enhancing productivity and creativity in software development projects. Introduction to code generation with AI models like GPT-4 Designing prompts for code generation across programming languages Techniques for specifying requirements and constraints in prompts Generating and interpreting code snippets using AI-driven solutions Integrating generated code into existing projects and codebases Best practices for testing and validating AI-generated code Ethics and Responsible AI Understand the ethical implications of prompt engineering and the importance of responsible AI deployment in business. Ethical considerations in prompt engineering Bias in AI systems and its impact on prompt engineering Techniques to minimize bias and ensure fairness Best practices for responsible AI deployment in business applications Monitoring and addressing ethical concerns in prompt engineering

Agile Practices for All Projects: On-Demand Agile methods are becoming increasingly prevalent, and have facilitated projects in reducing time to market, being adaptive to changing customer requirements, and increasing value to customers and organizations. These benefits have been implemented in both IT and non-IT environments to help all types of projects. This course will present key Agile techniques and processes that can be readily incorporated into your projects to enable greater flexibility and higher productivity, while maintaining the traditional project lifecycle framework. The overall goal of the course is for learners to be able to integrate appropriate Agile elements and/or techniques into any project in any environment. What you will Learn Course participants will understand the basic Agile approach, and the various methods for achieving agility and will be able to: Recall project management principles and methodologies Explain Agile practices and compare several Agile methods Apply Agile software development techniques in a project lifecycle framework Employ Agile processes in a project management framework Foundation Concepts Project Lifecycles What is Agile? Agile Benefits Agile Methods Agile Roles Agile Requirement Techniques Agile Requirements User Stories Just in Time (JIT) Requirements Agile Software Development Techniques Agile Design Agile Development Agile Testing Agile Deployment Agile Initiating & Planning Processes Agile Initiating Agile Planning Agile Delivery Processes Agile Execution Agile Monitoring & Control Agile Closing Implementing Agile Practices Agile Approaches Outside of Software Development Dispelling Agile Myths Applying Agile Techniques & Processes Summary and Next Steps What did we learn, and how can we implement this in our work environments?

Become free from Anxiety and say goodbye to managing your anxiety and start living a happy and content life. This masterclass will show you can change how your mind works to eliminate the negative and debilitating emotional impact of anxiety, once and for all!

Duration 3 Days 18 CPD hours This course is intended for This course is intended for solutions architects, solution-design engineers, developers seeking an understanding of AWS architecting and individuals seeking the AWS Solutions Architect-Associate certification. Overview Identify AWS architecting basic practices. Explore using the AWS management tools: The AWS Console, Command Line Interface (CLI), and CloudFormation in a lab environment. Examine the enforcement of accounts security using policies. Identify the elements that build an elastic, secure, virtual network that includes private and public subnets. Practice building an AWS core networking infrastructure. Determine strategies for a layered security approach to Virtual Private Cloud (VPC) subnets. Identify strategies to select the appropriate compute resources based on business use-cases. Practice building a VPC and adding an Elastic Cloud Compute (EC2) instance in a lab environment. Practice installing an Amazon Relational Database Service (RDS) instance and an Application Load Balancer (ALB) in the VPC you created. Compare and contrast AWS storage products and services, based on business scenarios. Compare and contrast the different types of AWS database services based on business needs. Practice building a highly available, auto-scaling database layer in a lab. Explore the business value of AWS monitoring solutions. Identify the role of monitoring, event driven load balancing, and auto scaling responses, based on usage and needs. Identify and discuss AWS automation tools that will help you build, maintain and evolve your infrastructure. Discuss network peering, VPC endpoints, gateway and routing solutions based on use-cases. Discuss hybrid networking configurations to extend and secure your infrastructure. Discuss the benefits of microservices as an effective decoupling strategy to power highly available applications at scale. Explore AWS container services for the rapid implementation of an infrastructure-agnostic, portable application environment. Identify the business and security benefits of AWS serverless services based on business examples. Practice building a serverless infrastructure in a lab environment. Discuss the ways in which AWS edge services address latency and security. Practice building a CloudFront deployment with an S3 backend in a lab environment. Explore AWS backup, recovery solutions, and best practices to ensure resiliency and business continuity. Build a highly available and secure cloud architecture based on a business problem, in a project-based facilitator-guided lab. Architecting on AWS is for solutions architects, solution-design engineers, and developers seeking an understanding of AWS architecting. In this course, you will learn to identify services and features to build resilient, secure and highly available IT solutions on the AWS Cloud. Architectural solutions differ depending on industry, types of applications, and business size. AWS Authorized Instructors emphasize best practices using the AWS Well-Architected Framework, and guide you through the process of designing optimal IT solutions, based on real-life scenarios. The modules focus on account security, networking, compute, storage, databases, monitoring, automation, containers, serverless architecture, edge services, and backup and recovery. At the end of the course, you will practice building a solution and apply what you have learned with confidence. Prerequisites AWS Cloud Practitioner Essentials classroom or digital training, or Working knowledge of distributed systems Familiarity with general networking concepts Familiarity with IP addressing Working knowledge of multi-tier architectures Familiarity with cloud computing concepts 0 - Introductions & Course Map review Welcome and course outcomes 1 - Architecting Fundamentals Review AWS Services and Infrastructure Infrastructure Models AWS API Tools Securing your infrastructure The Well-Architected Framework Hands-on lab: Explore Using the AWS API Tools to Deploy an EC2 Instance 2 - Account Security Security Principals Identity and Resource-Based Policies Account Federation Introduction to Managing Multiple Accounts 3 - Networking, Part 1 IP Addressing Amazon Virtual Private Cloud (VPC), Patterns and Quotas Routing Internet Access Network Access Control Lists (NACLs) Security Groups 4 - Compute Amazon Elastic Cloud Compute (EC2) EC2 Instances and Instance Selection High Performance Computing on AWS Lambda and EC2, When to Use Which Hands-On Lab: Build Your Amazon VPC Infrastructure 5 - Storage Amazon S3, Security, Versioning and Storage Classes Shared File Systems Data Migration Tools 6 - Database Services AWS Database Solutions Amazon Relational Database Services (RDS) DynamoDB, Features and Use Cases Redshift, Features, Use Cases and Comparison with RDS Caching and Migrating Data Hands-on Lab: Create a Database Layer in Your Amazon VPC Infrastructure 7 - Monitoring and Scaling Monitoring: CloudWatch, CloudTrail, and VPC Flow Logs Invoking Events 8 - Automation CloudFormation AWS Systems Manager 9 - Containers Microservices Monitoring Microservices with X-Ray Containers 10 - Networking Part 2 VPC Peering & Endpoints Transit Gateway Hybrid Networking Route 53 11 - Serverless Architecture Amazon API Gateway Amazon SQS, Amazon SNS Amazon Kinesis Data Streams & Kinesis Firehose Step Functions Hands-on Lab: Build a Serverless Architecture 12 - Edge Services Edge Fundamentals Amazon CloudFront AWS Global Accelerator AWS Web Application Firewall (WAF), DDoS and Firewall Manager AWS Outposts Hands-On Lab: Configure an Amazon CloudFront Distribution with an Amazon S3 Origin 13 - Backup and Recovery Planning for Disaster Recovery AWS Backup Recovery Strategie Additional course details: Nexus Humans Architecting 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 Architecting 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.