AI in Software Development Training in Cascais

GitHub Copilot is an AI-driven code completion tool designed to boost development speed while enhancing quality and productivity. When combined with Artificial Intelligence applications in projects, infrastructure, and software, managers can utilize AI to optimize resource allocation, streamline workflows, and improve decision-making.

This instructor-led live training (available online or on-site) is designed for advanced-level managers looking to deepen their expertise in GitHub Copilot while exploring practical AI applications in corporate environments, with examples relevant to large-scale projects and industries such as oil and gas.

Upon completion of this training, participants will be able to:

• Apply advanced Copilot functionalities in large-scale corporate projects.
• Integrate Copilot into multidisciplinary workflows for maximum efficiency.
• Leverage AI tools to optimize project management, infrastructure, and software acquisition.
• Implement AI-based strategies to improve planning, estimation, and time optimization.
• Identify practical AI applications in industry-specific scenarios such as oil and gas.

Course Format

• Interactive lecture and discussion.
• Hands-on exercises and case studies.
• Live-lab demonstrations of AI tools and Copilot workflows.

Course Customization Options

• To request customized training for this course, please contact us to make arrangements.

Artificial Intelligence (AI) comprises technologies that emulate human intelligence within machines and applications, facilitating the creation of smarter and more adaptable software.

This instructor-led live training, available either online or onsite, is designed for intermediate developers aiming to construct AI-driven applications using practical tools and platforms.

Upon completing this training, participants will be equipped to:

• Grasp fundamental AI and machine learning concepts.
• Create AI features utilizing Python and widely adopted libraries.
• Implement AI techniques within real-world software development projects.
• Assess models and deploy intelligent services.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical activities.
• Hands-on implementation in a live-lab environment.

Customization Options

• For customized training on this course, please contact us to make arrangements.

GitHub Copilot is an AI-driven coding assistant designed to automate development tasks, including DevOps operations such as creating YAML configurations, GitHub Actions, and deployment scripts.

This instructor-led live training (available online or on-site) is designed for beginner to intermediate professionals who wish to utilise GitHub Copilot to streamline DevOps tasks, enhance automation, and boost productivity.

By the end of this training, participants will be able to:

• Use GitHub Copilot to assist with shell scripting, configuration, and CI/CD pipelines.
• Leverage AI code completion in YAML files and GitHub Actions.
• Accelerate testing, deployment, and automation workflows.
• Apply Copilot responsibly with an understanding of AI limitations and best practices.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

Huawei Ascend constitutes a range of AI processors engineered for superior inference and training capabilities.

This instructor-led live training, available both online and onsite, targets intermediate-level AI engineers and data scientists eager to develop and fine-tune neural network models utilizing Huawei’s Ascend platform alongside the CANN toolkit.

Upon completion of this training, participants will be equipped to:

• Establish and configure the CANN development environment.
• Create AI applications leveraging MindSpore and CloudMatrix workflows.
• Enhance performance on Ascend NPUs through custom operators and tiling techniques.
• Deploy models across edge or cloud infrastructures.

Course Format

• Interactive lectures accompanied by group discussions.
• Practical application of Huawei Ascend and the CANN toolkit within sample projects.
• Guided exercises concentrating on model construction, training, and deployment.

Customization Options

• To arrange customized training tailored to your specific infrastructure or datasets for this course, please contact us.

This instructor-led live training in Cascais (online or onsite) is designed for intermediate-level software professionals who want to utilise AI and machine learning to boost efficiency and drive innovation in their development work.

Upon completion of this training, participants will be able to:

• Grasp the role of AI and machine learning in automating software development tasks.
• Deploy AI tools to generate code, tests, and documentation.
• Apply AI techniques for code optimization, quality assurance, and debugging.
• Integrate AI into DevOps and CI/CD pipelines to improve deployment strategies.
• Address ethical considerations and challenges associated with AI-augmented software engineering.

This instructor-led, live training in Cascais (online or onsite) is aimed at intermediate-level QA engineers, developers, and team leads who wish to leverage GitHub Copilot for more efficient debugging, code quality enhancement, and streamlined code review.

By the end of this training, participants will be able to:

• Set up GitHub Copilot for debugging and code review purposes.
• Use Copilot to identify and resolve bugs efficiently.
• Enhance code quality with AI-assisted suggestions.
• Streamline code review processes with Copilot's capabilities.
• Collaborate effectively using Copilot in team environments.

Course Customization Options

Format of the Course

By the end of this training, participants will be able to:

Prompt Engineering for Software Development is a practical course designed to equip developers with the skills to craft effective prompts that enhance the usefulness, precision, and safety of AI-generated outputs within software engineering tasks.

This instructor-led live training (available online or onsite) targets intermediate-level developers who wish to incorporate prompt engineering techniques into their use of AI coding assistants, code analyzers, and intelligent automation tools.

• Create precise prompts for code generation, review, and optimization tasks.
• Use prompt chaining and refinement to improve AI responses in iterative workflows.
• Generate structured outputs such as test cases, SQL queries, and documentation from minimal input.
• Mitigate hallucination and improve control over LLM behavior in technical environments.

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

• To request a customized training for this course, please contact us to arrange.

Responsible AI in Software Development is a foundational course that addresses the ethical, legal, and governance considerations when using AI tools in the software development process. The course emphasizes transparency, fairness, intellectual property concerns, and safe deployment of AI-generated code.

This instructor-led, live training (online or onsite) is aimed at beginner-level technical and non-technical professionals who wish to ensure ethical, compliant, and risk-aware use of AI in their software projects.

By the end of this training, participants will be able to:

• Identify and mitigate ethical and legal risks associated with AI-assisted development.
• Understand bias in AI-generated code and how to evaluate fairness.
• Manage software licenses and attribution related to AI-generated content.
• Establish governance, policy, and compliance frameworks for AI use in development teams.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This practical course explores the use of generative AI to convert stakeholder feedback into structured requirements, epics, user stories, and acceptance criteria tailored for Agile development environments.

Delivered as live instructor-led training (available online or onsite), it is designed for beginner-level product and project professionals aiming to utilise tools such as ChatGPT or Claude to enhance clarity, efficiency, and traceability during requirement gathering and refinement phases.

Upon completion, participants will be capable of:

• Employing AI prompts to collect and refine business requirements.
• Transforming feature requests into clearly structured user stories and epics.
• Producing acceptance criteria, edge cases, and definitions of done with the aid of AI.
• Collaborating with development teams using documentation structured by AI.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation within a live laboratory environment.

Customisation Options

• For a bespoke training version of this course, please contact us to make arrangements.

This instructor-led, live training in Cascais (online or onsite) is aimed at beginner-level to intermediate-level Python developers who wish to leverage GitHub Copilot for Python-specific tasks, debugging, and implementing machine learning workflows.

By the end of this training, participants will be able to:

• Set up and configure GitHub Copilot for Python development.
• Leverage Copilot to write efficient Python code.
• Debug Python applications using AI-generated suggestions.
• Automate repetitive coding tasks and improve workflow efficiency.
• Utilize Copilot for implementing machine learning projects in Python.

This instructor-led, live training in Cascais (online or onsite) is aimed at advanced-level participants who wish to customize GitHub Copilot for team projects, utilize its advanced features, and integrate it seamlessly into CI/CD pipelines for enhanced collaboration and productivity.

By the end of this training, participants will be able to:

• Customize GitHub Copilot for specific project needs and team workflows.
• Leverage advanced features of Copilot for complex coding tasks.
• Integrate GitHub Copilot into CI/CD pipelines and collaborative environments.
• Optimize team collaboration using AI-powered tools.
• Manage and troubleshoot Copilot settings and permissions effectively.

The 'Generative AI for Front-End Development' course investigates how large language models and AI-driven utilities can streamline front-end workflows. It focuses on prompt-based code generation, rapid layout prototyping, and user interface optimization.

Delivered as an instructor-led live training (available online or onsite), this programme targets beginner to intermediate front-end professionals seeking to leverage generative AI to construct and iterate user interfaces with greater speed and creativity.

Upon completion, participants will be equipped to:

• Utilize AI tools to produce HTML, CSS, and JavaScript from natural language instructions.
• Construct and refine UI components and layouts using generative models.
• Rapidly prototype responsive web designs without writing code entirely from scratch.
• Enhance front-end code through AI-driven suggestions and automated workflows.

Course Format

• Interactive lectures paired with group discussions.
• Extensive exercises and practical practice sessions.
• Hands-on implementation within a live-lab environment.

Course Customization Options

• To arrange customized training for this course, please contact us.

This instructor-led, live training in Cascais (online or onsite) is aimed at developers ranging from novices to experts who wish to leverage AI for code generation with Tabnine.

By the end of this training, participants will be able to:

• Understand the basics of AI-powered code generation.
• Install and configure Tabnine in their development environment.
• Utilize Tabnine for efficient code completion and error correction.
• Create and train custom AI models with Tabnine for specialized tasks.

AI-Enhanced Test Generation and Quality Engineering investigates how artificial intelligence tools and large language models (LLMs) can broaden test coverage, accelerate test creation, and refine quality assurance processes.

This instructor-led, live training (available online or onsite) is designed for intermediate-level QA professionals aiming to automate and upgrade their testing strategies using AI-driven tools and methodologies.

By the end of this training, participants will be able to:

• Generate unit, integration, and UI tests using AI tools and prompts.
• Utilise LLMs for exploratory testing, edge-case discovery, and regression analysis.
• Cluster and prioritise test failures and anomalies using AI-assisted triage.
• Integrate AI-based testing into CI/CD pipelines to improve release confidence.

Format of the Course

• Interactive lecture and discussion.
• Extensive exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training delivered in Cascais (online or onsite) caters to intermediate-level participants seeking to utilize GitHub Copilot for complex coding scenarios, enhance productivity, and integrate Copilot into their development workflows.

By the conclusion of this training, participants will be able to:

• Optimize their deployment of GitHub Copilot for advanced coding tasks.
• Craft more efficient, bug-free, and maintainable code using Copilot suggestions.
• Incorporate GitHub Copilot into their chosen IDEs and workflows.
• Apply Copilot for debugging and refactoring code.
• Comprehend the limitations and ethical aspects of using AI-assisted coding tools.

This instructor-led, live training in Cascais (online or onsite) is aimed at advanced-level developers and team leads who wish to master advanced features of Tabnine.

By the end of this training, participants will be able to:

• Implement Tabnine in complex software projects.
• Customize and train Tabnine's AI models for specific use cases.
• Integrate Tabnine into team workflows and development pipelines.
• Enhance code quality and accelerate development cycles using Tabnine's insights.

Devstral is an open-source framework engineered to build and operate coding agents capable of interacting with codebases, developer tools, and APIs to boost engineering productivity.

This instructor-led live training (available online or onsite) targets intermediate to advanced-level ML engineers, developer-tooling teams, and SREs who aim to design, implement, and optimize coding agents using Devstral.

Upon completion of this training, participants will be able to:

• Configure and set up Devstral for coding agent development.
• Design agentic workflows tailored for codebase exploration and modification.
• Integrate coding agents seamlessly with developer tools and APIs.
• Apply best practices for secure and efficient agent deployment.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live-lab environment.

Customization Options

• For personalized training requests, please contact us to arrange.

Cursor is an AI-powered code editor designed to enhance developer productivity through intelligent code completions, contextual edits, and adaptive assistance.

This instructor-led, live training (online or onsite) is aimed at beginner-level developers and engineering teams who wish to streamline their coding workflow and safely leverage AI suggestions for improved efficiency.

Upon completion of this training, participants will be able to:

• Install and configure Cursor for optimal use in development projects.
• Understand and apply AI-assisted code completion, in-editor chat, and refactoring tools.
• Evaluate, accept, or modify AI-generated code suggestions effectively and securely.
• Adopt best practices for team onboarding, collaboration, and version control integration.

Format of the Course

• Interactive lecture and discussion.
• Hands-on demonstrations and guided exercises.
• Real-world coding challenges and lab practice using Cursor.

Course Customization Options

• This course can be tailored to specific programming languages or frameworks used by your team.

This instructor-led, live training in Cascais (online or onsite) is aimed at beginner-level developers who wish to understand GitHub Copilot's capabilities, set it up, and use it effectively to enhance their coding experience.

By the end of this training, participants will be able to:

• Understand what GitHub Copilot is and how it works.
• Set up GitHub Copilot with a supported code editor.
• Use GitHub Copilot to write, refactor, and debug code faster.
• Leverage Copilot to explore coding techniques and solutions.
• Apply best practices for integrating GitHub Copilot into daily workflows.

This technical course explores how to leverage Large Language Models (LLMs) to enhance code quality, minimize technical debt, and automate documentation processes within software teams.

Delivered as an instructor-led live training (available online or on-site), this programme is designed for intermediate to advanced software professionals eager to utilise LLMs, such as GPT, to analyse, refactor, and document complex or legacy codebases more efficiently.

Upon completion of this training, participants will be equipped to:

• Utilise LLMs to elucidate code structures, dependencies, and logic within unfamiliar repositories.
• Spot and refactor anti-patterns to boost code readability.
• Automate the creation and upkeep of in-line comments, README files, and API documentation.
• Seamlessly integrate LLM-driven insights into existing CI/CD and code review workflows.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation in a live-lab environment.

Customisation Options

• To arrange bespoke training for this course, please get in touch with us.

The AI-Driven Software Development Lifecycle (SDLC) course provides a practical exploration of how artificial intelligence can elevate every stage of the software development process. Participants will learn to integrate AI tools and techniques throughout the entire lifecycle, ranging from automating requirement analysis to enabling intelligent test generation and optimizing deployment strategies.

This instructor-led training, available both online and onsite, is designed for intermediate-level software leaders seeking to modernize their SDLC practices by adopting AI-assisted workflows and tools.

Upon completion of this training, participants will be capable of:

• Utilizing AI to transform business input into structured requirements and user stories.
• Applying Large Language Models (LLMs) to enhance code documentation, review processes, and refactoring efforts.
• Automating the generation of test cases and conducting coverage analysis using AI-powered tools.
• Implementing AI-driven monitoring and deployment decision-making within CI/CD pipelines.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live-lab environment.

Course Customization Options

• For inquiries regarding customized training for this course, please contact us to arrange.

This instructor-led, live training (online or onsite) is aimed at intermediate-level software developers who wish to boost productivity and code quality using AI-assisted coding with Cursor.

By the end of this training, participants will be able to:

• Install and configure Cursor for AI-assisted software development.
• Integrate Cursor with Git repositories and development workflows.
• Use natural language to generate, debug, and optimize code.
• Leverage AI capabilities for refactoring, documentation, and testing.

This immersive, one-day workshop empowers software teams to integrate cutting-edge AI tools throughout the Software Development Lifecycle (SDLC). Structured as an interactive game with progressive "levels," this experience blends technical skill-building, creativity, and collaboration.

Participants will tackle real-world challenges across all stages of the SDLC — from requirement gathering and design to coding, testing, deployment, and monitoring — using AI-powered tools like ChatGPT, GitHub Copilot, and ML-based log analysis systems.

Designed for modern development environments, this workshop fosters AI fluency, team synergy, and a deep understanding of how to augment software delivery pipelines with generative AI and machine learning capabilities.

This instructor-led live training in Cascais (online or onsite) is aimed at beginner-to-intermediate-to-advanced product teams, developers, and technical business users who wish to leverage Lovable to build production-ready applications more efficiently, with improved structure, quality, and deployment practices.

By the end of this training, participants will be able to: plan and generate functional applications, optimise user flows and data handling, integrate key production features, and prepare applications for deployment and team collaboration.

This instructor-led, live training aims to equip professionals with no coding or technical background to confidently use Claude Code — Anthropic’s AI-powered coding and automation tool — to build real projects, automate workflows, and integrate their everyday tools using plain English.

Participants will utilize the Claude app (claude.ai and Claude Desktop) to complete hands-on tasks, progressing from their first interaction to connecting Claude with external services via MCP (Model Context Protocol) connectors. The 7-hour format includes a dedicated Live Build Session where the group collaboratively constructs workflows addressing real problems volunteered by participants — a high-energy segment that teaches prompt judgment in a way solo practice cannot replicate. By the end of the course, every participant will have built a working project and connected Claude to at least one external service.

Format of the Course

• Interactive lecture and live demonstration
• Guided hands-on exercises after every concept (participants follow along in real time)
• Collaborative Live Build Session with real participant-submitted workflow problems
• Cumulative capstone project with showcase

This instructor-led, live training aims to equip professionals without coding or technical expertise with the confidence to utilise Claude Code — Anthropic’s AI-driven coding and automation tool — to construct real-world projects, automate workflows, and integrate everyday tools using natural language.

Participants will engage with the Claude application (via claude.ai and Claude Desktop) to complete practical tasks, progressing from their initial interaction to linking Claude with external services through MCP (Model Context Protocol) connectors. Upon completion of the course, every participant will have developed a functional project and connected Claude to at least one external service.

Course Format

• Interactive lectures and live demonstrations
• Guided hands-on exercises following each concept (participants follow along in real time)
• A cumulative capstone project developed throughout the session

This instructor-led, live training in Cascais (online or onsite) is aimed at intermediate-level software engineers and technical leads who wish to use Claude Code to accelerate development workflows and improve team productivity with AI-assisted coding.

By the end of this training, participants will be able to install and configure Claude Code, navigate, generate and improve code using AI, integrate AI workflows with Git, and design scalable AI-assisted processes.

This instructor-led, live training in Cascais (online or onsite) is aimed at developers who wish to use GitHub Copilot Agent Mode to build features autonomously, run tests, and manage larger coding tasks.

By the end of this training, participants will be able to activate Agent Mode, plan and iterate within the agent loop, execute terminal commands, and implement enterprise governance.

Course objectives turn software / AI engineers into legal engineers — the people who can actually build AI for legal work (eDiscovery, review, investigations).

In two days, participants build the full core stack: ingest and extract messy real-world legal data, search and retrieve it, add retrieval-augmented generation (RAG) with citations, keep it private on a local model and prove it, run a defensible AI review with court-ready metrics, and package the result for deployment.

By the end of this training, participants will be able to:

• Master enterprise prompt architecture across six layers: Role, Context, Constraints, Domain Standards, Format, and Examples.
• Encode business, security, and compliance constraints (including GDPR, EU AI Act, and sector standards) directly into prompts.
• Co-build a prompt library that is validated, shared, and governed by all teams.
• Define sustainable governance mechanisms: Prompt Curator role, naming conventions, versioning, and quality metrics.
• Leave with concrete deliverables: Library v1.0, Governance Charter, and a 30-Day Deployment Plan.

Course format for participant assessment

• Interactive multi-profile workshops (Architects, Developers, QA, Team Leaders).
• Facilitated co-construction by an architect-consultant: participants build real, operational deliverables.
• All co-built deliverables belong entirely to the client organization.

Course customization options

• To request a customized version of this training, please contact us to make the
  necessary arrangements.