AI for Software Development Training in Patras

GitHub Copilot serves as an AI-driven code completion solution designed to boost development speed while enhancing both quality and efficiency. When combined with artificial intelligence applications across projects, infrastructure, and software, managers can utilize AI to optimize resource distribution, streamline processes, and improve decision-making capabilities.

This instructor-led, live training (available online or onsite) targets advanced-level managers seeking to deepen their understanding of GitHub Copilot while exploring practical AI applications within corporate settings. The course includes examples relevant to large-scale projects and industries such as oil and gas.

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

• Utilize advanced Copilot features 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.
• Recognize practical AI applications in industry-specific scenarios such as oil and gas.

Format of the Course

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

Course Customization Options

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

Artificial Intelligence (AI) encompasses a suite of technologies designed to emulate human intelligence within machines and applications, fostering more intelligent and adaptive software solutions.

This instructor-led live training, available online or on-site, targets intermediate developers looking to construct AI-driven applications using practical tools and platforms.

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

• Grasp fundamental AI and machine learning concepts.
• Create AI features leveraging Python and widely-used libraries.
• Integrate AI techniques into real-world software development projects.
• Assess models and deploy intelligent services effectively.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Practical implementation within a live-lab environment.

Customization Options

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

GitHub Copilot is an AI-driven coding assistant designed to streamline development tasks, including key DevOps operations such as drafting YAML configurations, crafting GitHub Actions, and building deployment scripts.

This instructor-led live training (available online or onsite) is tailored for beginner to intermediate professionals aiming to harness GitHub Copilot to simplify DevOps workflows, enhance automation capabilities, and increase overall productivity.

Upon completing this training, participants will be equipped to:

• Utilize GitHub Copilot to support shell scripting, configuration management, and CI/CD pipelines.
• Harness AI-powered code completion within YAML files and GitHub Actions.
• Speed up testing, deployment, and automation processes.
• Apply Copilot responsibly, with a clear understanding of AI limitations and industry best practices.

Course Format

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

Customization Options

• For customized training arrangements, please contact us directly.

Huawei Ascend comprises a series of AI processors engineered for superior inference and training performance.

This instructor-led training, available both online and on-site, is tailored for intermediate AI engineers and data scientists aiming to create and optimize neural network models leveraging Huawei's Ascend platform alongside the CANN toolkit.

Upon completing this training, participants will be equipped to:

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

Course Format

• Engaging lectures coupled with interactive discussions.
• Practical application of Huawei Ascend and the CANN toolkit in sample projects.
• Supervised exercises concentrating on model construction, training, and deployment.

Customization Opportunities

• For bespoke training aligned with your specific infrastructure or datasets, please get in touch with us to arrange.

This instructor-led, live training held in Patras (either online or onsite) targets intermediate-level software professionals who aim to leverage AI and machine learning to enhance efficiency and innovation in software development.

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

• Comprehend the role of AI and machine learning in automating software development tasks.
• Implement AI tools for generating 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 in AI-augmented software engineering.

This instructor-led, live training in Patras (online or onsite) is designed for intermediate to advanced participants who aim to optimize team workflows, enhance collaborative coding techniques, and effectively manage Copilot usage within multi-developer settings.

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

• Configure GitHub Copilot for team-based environments.
• Employ Copilot to strengthen collaborative coding practices.
• Enhance team workflows through Copilot’s capabilities.
• Oversee Copilot’s integration in projects with multiple developers.
• Sustain consistent code quality and standards across all teams.
• Apply advanced Copilot features to meet specific team requirements.
• Integrate Copilot with other collaborative tools for greater efficiency.

This instructor-led, live training in Patras (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

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

Prompt Engineering for Software Development is a practical course aimed at teaching developers how to design effective prompts that enhance the utility, accuracy, and safety of AI-generated outputs within software engineering contexts.

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

• Design precise prompts for code generation, review, and optimization tasks.
• Utilize prompt chaining and refinement to enhance AI responses in iterative workflows.
• Produce structured outputs such as test cases, SQL queries, and documentation from minimal input.
• Reduce hallucinations and improve control over LLM behavior in technical environments.

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

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

This instructor-led, live training in Patras (online or onsite) is aimed at intermediate-level front-end developers who wish to use GitHub Copilot to automate repetitive coding tasks, improve UI/UX design, and streamline front-end workflows.

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

• Set up GitHub Copilot for front-end development projects.
• Leverage Copilot to generate HTML, CSS, and JavaScript code efficiently.
• Improve UI/UX design processes using AI-generated code suggestions.
• Enhance front-end workflows with practical Copilot integration strategies.
• Troubleshoot and debug front-end code using Copilot assistance.

Responsible AI in Software Development is a foundational course that explores the ethical, legal, and governance aspects of integrating AI tools into software development workflows. The curriculum highlights the importance of transparency, fairness, intellectual property rights, and the secure deployment of code generated by AI.

This instructor-led live training, available either online or onsite, is designed for technical and non-technical professionals at a beginner level who aim to implement ethical, compliant, and risk-aware AI practices within their software projects.

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

• Recognize and mitigate ethical and legal risks linked to AI-assisted development.
• Understand bias within AI-generated code and learn how to assess fairness.
• Handle software licenses and attribution for content produced by AI.
• Establish governance structures, policies, and compliance frameworks for AI usage within development teams.

Course Format

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

Customization Options

• For customized training requests, please contact us to arrange accordingly.

AI for Software Requirements and User Story Generation is a hands-on course designed to teach you how to use generative AI to convert stakeholder feedback into structured requirements, epics, user stories, and acceptance criteria tailored for Agile development processes.

This instructor-led live training (available online or onsite) is ideal for product and project professionals at the beginner level who want to utilize tools such as ChatGPT or Claude to enhance clarity, efficiency, and traceability during the requirement gathering and refinement phases.

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

• Employing AI prompts to collect and refine business requirements.
• Transforming feature requests into well-structured user stories and epics.
• Utilizing AI to generate acceptance criteria, edge cases, and definitions of done.
• Collaborating effectively with development teams through AI-structured documentation.

Course Format

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

Customization Options

• For a customized training session for this course, please contact us to make arrangements.

Cursor is an AI-driven development environment designed to boost productivity and reliability across data and machine learning workflows through intelligent code generation, context-aware suggestions, and streamlined documentation.

This instructor-led, live training (available online or onsite) targets intermediate-level data and ML professionals who want to integrate Cursor into their daily workflows for faster prototyping, scalable pipeline development, and improved model operations.

After completing this training, participants will be able to:

• Use Cursor to accelerate notebook development and code exploration.
• Generate, refactor, and document ETL and feature engineering pipelines.
• Leverage AI-assisted code for model training, tuning, and evaluation.
• Enhance reproducibility, collaboration, and operational consistency in ML workflows.

Format of the Course

• Interactive lectures and demonstrations.
• Practical, hands-on exercises in live coding environments.
• Case studies integrating Cursor with ML pipelines and model ops tools.

Course Customization Options

• This training can be tailored to specific frameworks such as TensorFlow, PyTorch, or scikit-learn, or to organizational MLOps platforms.

This instructor-led, live training in Patras (online or onsite) is tailored for beginner to intermediate Python developers who want to utilize GitHub Copilot for Python-specific tasks, debugging, and implementing machine learning workflows.

Upon completion 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.

Graphite serves as a comprehensive platform for code review and developer productivity, designed to optimize pull request processes, boost team collaboration, and seamlessly integrate with tools like GitHub and AI-powered code review assistants.

This instructor-led live training, available online or on-site, is tailored for intermediate-level software engineering teams looking to streamline their development workflows, increase review efficiency, and effectively deploy Graphite within enterprise DevOps pipelines.

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

• Deploying and configuring Graphite for large-scale enterprise development environments.
• Automating pull request management to enhance code review throughput.
• Integrating Graphite with GitHub, CI/CD systems, and AI assistants including OpenAI, Deepseek, LlaMA, Qwen, and Mistral Small.
• Assessing developer productivity through Graphite's analytics and dashboards.

Course Format

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

Course Customization Options

• For a customized training experience, please reach out to us to arrange your requirements.

Cursor is a sophisticated AI-driven development environment enabling engineers to extend, fine-tune, and customize its coding intelligence for specialized applications and enterprise workflows.

This instructor-led, live training (available online or onsite) targets advanced developers and AI engineers looking to design tailored prompt systems, refine model behavior, and construct custom extensions for internal development automation.

Upon completing this training, participants will be able to:

• Design and test sophisticated prompt templates to achieve precise AI responses.
• Integrate Cursor with internal APIs and knowledge bases for context-aware code generation.
• Create fine-tuned or domain-adapted AI models for specific tasks.
• Build and deploy secure custom tools or adapters that expand Cursor’s capabilities.

Course Format

• Technical presentations and guided demonstrations.
• Hands-on development and prompt optimization labs.
• Practical projects integrating Cursor with real-world enterprise systems.

Customization Options

• This course can be tailored to align with specific internal architectures, AI frameworks, or security compliance requirements.

This instructor-led, live training in Patras (online or onsite) is designed for advanced-level learners aiming to customize GitHub Copilot for team projects, leverage its sophisticated features, and integrate it smoothly into CI/CD pipelines to improve collaboration and productivity.

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

• Customize GitHub Copilot to align with specific project needs and team workflows.
• Harness advanced Copilot features for complex coding assignments.
• Integrate GitHub Copilot into CI/CD pipelines and collaborative environments.
• Enhance team collaboration through AI-enabled tools.
• Manage and troubleshoot Copilot configurations and permissions efficiently.

Generative AI for Front-End Development explores how large language models and AI-powered tools can accelerate front-end development through prompt-based code generation, layout prototyping, and UI optimization.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level front-end professionals who wish to use generative AI to build and iterate user interfaces more quickly and creatively.

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

• Leverage AI tools to produce HTML, CSS, and JavaScript from natural language prompts.
• Design and refine UI components and layouts using generative models.
• Rapidly prototype responsive web designs without writing all code from scratch.
• Enhance front-end code quality using AI suggestions and automation workflows.

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 instructor-led, live training conducted in Patras (online or on-site) is designed for developers from novice to expert levels who wish to utilize AI for code generation through Tabnine.

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

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

Vibe coding is an emerging paradigm where developers collaborate with large language models to generate, refine, and optimize code through natural language interactions.

This instructor-led, live training (online or onsite) is aimed at intermediate-level developers and technical leads who wish to master the use of AI coding assistants and open-source LLMs to improve productivity, creativity, and workflow automation.

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

• Understand the principles and philosophy of vibe coding and its impact on software development.
• Implement LLM-assisted coding environments using tools such as Replit, DeepSeek, LlaMA, Qwen, Mistral, and GitHub Copilot.
• Design and execute prompt engineering strategies for effective AI collaboration.
• Integrate vibe coding workflows into enterprise CI/CD pipelines and governance frameworks.

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 course explores how artificial intelligence tools and large language models (LLMs) can optimize test coverage, accelerate test creation, and elevate quality assurance processes.

Designed as an instructor-led, live training session (available online or onsite), it targets intermediate-level QA professionals seeking to automate and enhance their testing strategies through AI-driven tools and practices.

Upon completion, participants will be able to:

• Generate unit, integration, and UI tests using AI tools and effective prompting techniques.
• Leverage LLMs for exploratory testing, edge-case identification, and regression analysis.
• Cluster and prioritize test failures and anomalies utilizing AI-assisted triage methods.
• Integrate AI-based testing into CI/CD pipelines to boost release confidence.

Course Format

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

Customization Options

• For customized training arrangements, please contact us directly.

Cursor is an AI-enhanced development environment designed to boost team collaboration, automate code reviews, and integrate smoothly into contemporary CI/CD workflows.

This live, instructor-led training, available online or onsite, targets intermediate technical professionals seeking to incorporate Cursor into their team environments to foster better collaboration, streamline review processes, and uphold quality standards across automated pipelines.

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

• Configure and manage team environments in Cursor to facilitate collaborative development.
• Utilize AI-driven tools for automated code reviews, pull request creation, and merge validation.
• Enforce code governance, review policies, and security protocols using Cursor's features.
• Connect Cursor with CI/CD systems to guarantee continuous delivery and consistent quality.

Course Format

• Instructor-led sessions combined with team-based discussions.
• Practical labs simulating real-world team collaboration scenarios.
• Live integration exercises involving CI/CD and version control tools.

Customization Options

• The curriculum can be tailored to specific CI/CD platforms, repository management tools, or enterprise security needs.

This trainer-led, live training in Patras (online or onsite) is designed for beginner to intermediate programmers and developers who wish to leverage DeepSeek Coder to enhance coding efficiency and productivity.

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

• Understand the capabilities and limitations of DeepSeek Coder.
• Generate high-quality code snippets using AI assistance.
• Utilize DeepSeek Coder for debugging and optimizing code.
• Automate repetitive programming tasks using AI tools.

This instructor-led, live training in Patras (online or onsite) targets intermediate-level participants seeking to leverage GitHub Copilot for advanced coding scenarios, boost productivity, and seamlessly integrate Copilot into their development workflows.

Upon completing this training, participants will be able to:

• Optimize their utilisation of GitHub Copilot for complex coding tasks.
• Compose more efficient, error-free, and maintainable code by leveraging Copilot's suggestions.
• Integrate GitHub Copilot into their chosen IDEs and workflows.
• Utilise Copilot for debugging and code refactoring.
• Understand the limitations and ethical considerations of using AI-powered coding tools.

This instructor-led, live training in Patras (online or onsite) is designed for advanced developers and team leads aiming to master the advanced features of Tabnine.

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

• Deploy Tabnine within complex software projects.
• Customize and train Tabnine's AI models for specific use cases.
• Integrate Tabnine into team workflows and development pipelines.
• Improve code quality and accelerate development cycles leveraging Tabnine's insights.

This instructor-led, live training in Patras (online or onsite) is aimed at beginner-level to intermediate-level software developers who wish to integrate AI coding assistants into their development workflow.

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

• Understand the role and capabilities of AI coding assistants in software development.
• Utilize various AI coding assistant tools to automate routine coding tasks.
• Integrate AI coding assistants into their software development lifecycle.
• Enhance their productivity and focus on more complex and creative programming tasks.
• Address ethical considerations and responsible use of AI in software development.

Devstral is an open-source framework designed for building and running coding agents that can interact with codebases, developer tools, and APIs to enhance engineering productivity.

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

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

• Set up and configure Devstral for coding agent development.
• Design agentic workflows for codebase exploration and modification.
• Integrate coding agents with developer tools and APIs.
• Implement best practices for secure and efficient agent deployment.

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.

Cursor is an AI-enhanced code editor crafted to elevate developer productivity via intelligent code completions, context-sensitive edits, and adaptive assistance.

This instructor-led, live training (available online or onsite) targets beginner-level developers and engineering teams aiming to streamline their coding workflow and safely utilise AI suggestions for improved efficiency.

Upon completing 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.

Course Format

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

Course Customisation Options

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

This guided, live training in Patras (online or in-person) is designed for beginner developers aiming to understand GitHub Copilot's potential, set it up, and utilize it effectively to boost their coding experience.

Upon completing this training, attendees will be capable of:

• Gaining insight into what GitHub Copilot is and its operational mechanics.
• Installing GitHub Copilot on a compatible code editor.
• Utilizing GitHub Copilot to accelerate code writing, refactoring, and debugging.
• Employing Copilot to investigate new coding methods and potential solutions.
• Implementing best practices for seamlessly integrating GitHub Copilot into everyday workflows.

This technical course, "LLMs for Code Comprehension, Refactoring, and Documentation," focuses on applying large language models (LLMs) to enhance code quality, minimize technical debt, and automate documentation processes for software teams.

Delivered by an expert instructor, this live training (available online or onsite) targets intermediate to advanced software professionals who want to utilize LLMs, such as GPT, to more effectively analyze, refactor, and document complex or legacy codebases.

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

• Utilize LLMs to clarify code logic, dependencies, and structure within unfamiliar repositories.
• Spot and refactor anti-patterns, thereby enhancing code readability.
• Automatically generate and sustain inline comments, README files, and API documentation.
• Embed LLM-derived insights into current CI/CD and code review workflows.

Course Structure

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

Customization Options

• To arrange a tailored version of this course, please get in touch with us.

This instructor-led, live training in Patras (online or on-site) is designed for intermediate Python developers and data scientists who wish to enhance their productivity with the assistance of Tabnine.

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

• Install and set up Tabnine within their Python development environment.
• Utilize Tabnine’s autocomplete capabilities to write Python code more efficiently.
• Customize Tabnine’s behavior to align with their personal coding style and project requirements.
• Gain insight into how Tabnine’s AI model processes and supports Python code.

This instructor-led, live training in Patras (online or onsite) is targeted at beginner-level participants who wish to understand AI coding assistants, their capabilities, how they can enhance the development process, and the ethical considerations surrounding their use.

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

• Understand the purpose and capabilities of AI coding assistants.
• Identify different AI coding assistant tools and their features.
• Utilize AI coding assistants for basic coding tasks.
• Address basic ethical considerations and responsible use of AI in development.

The AI-Driven Software Development Lifecycle (SDLC) is a hands-on course designed to demonstrate how artificial intelligence can optimize every stage of the software development process. Participants will discover how to integrate AI tools and techniques throughout the entire lifecycle, from automating requirement analysis to intelligent test generation and deployment optimization.

This instructor-led live training, available online or onsite, is tailored for intermediate-level software leaders seeking to modernize their SDLC through AI-assisted workflows and tools.

Upon completing this training, participants will be equipped to:

• Utilize AI to transform business input into structured requirements and user stories.
• Employ Large Language Models (LLMs) to enhance code documentation, review, and refactoring.
• Automate test case generation and coverage analysis using AI-driven tools.
• Implement 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 in a live-lab environment.

Course Customization Options

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

This instructor-led live training, available online or on-site, is designed for intermediate software developers looking to enhance their productivity and code quality through AI-assisted coding with Cursor.

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

• Install and set up Cursor for AI-assisted software development.
• Connect Cursor with Git repositories and integrate it into existing development workflows.
• Utilize natural language prompts to generate, debug, and optimize code.
• Apply AI features for refactoring, creating documentation, and running tests.

This instructor-led, live training in Patras (online or onsite) is designed for beginner to intermediate-level developers who wish to learn how to effectively utilize the capabilities of GitHub Copilot within modern development workflows.

This instructor-led, live training in Patras (online or onsite) targets beginner-level developers who wish to boost their coding efficiency with the help of Tabnine.

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

• Install and configure Tabnine in their preferred IDE.
• Leverage Tabnine's autocomplete capabilities to expedite the coding process.
• Customize Tabnine's settings to achieve optimal support.
• Grasp how Tabnine's AI analyzes their code to deliver more accurate suggestions.

This immersive, one-day workshop that 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 Patras (online or onsite) is designed for beginner-level professionals who wish to use Replit AI to build, test, and deploy simple applications faster.

By the end of this training, participants will be able to: create an app from a prompt, improve code with AI assistance, manage configuration securely, and deploy a working application.

This instructor-led, live training in Patras (online or onsite) targets beginner, intermediate, or advanced-level product teams, developers, and technical business users who wish to use Lovable to build production-ready applications faster, with better structure, quality, and deployment practices.

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

The primary goal of this instructor-led live training is to equip professionals without coding or technical backgrounds to confidently utilize Claude Code — Anthropic’s AI-driven coding and automation platform — for constructing real-world projects, streamlining workflows, and integrating everyday tools using simple English.

Attendees will leverage the Claude application (accessible via claude.ai and Claude Desktop) to execute practical tasks, starting from their initial interaction through to linking Claude with external services via MCP (Model Context Protocol) connectors. This 7-hour program includes a dedicated Live Build Session where participants collaboratively develop workflows addressing real issues they have submitted. This dynamic segment fosters prompt evaluation skills in a manner that solitary practice cannot achieve. Upon completion, every attendee will have created a functional project and linked Claude to at least one external service.

Course Structure

• Interactive lectures accompanied by live demonstrations
• Guided hands-on exercises following each concept (participants engage in real-time)
• Collaborative Live Build Session focusing on real workflow challenges submitted by participants
• Cumulative capstone project with a presentation

This instructor-led, live training aims to equip professionals without coding or technical backgrounds to confidently utilize Claude Code — Anthropic’s AI-driven coding and automation tool — for building tangible projects, automating workflows, and integrating daily tools using simple English.

Attendees will use the Claude application (claude.ai and Claude Desktop) to perform practical tasks, ranging from their initial interaction to linking Claude with external services via MCP (Model Context Protocol) connectors. Upon completion, 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)
• Cumulative capstone project developed throughout the session

This instructor-led, live training in Patras (online or onsite) is designed for intermediate software engineers and technical leads who want to use Claude Code to speed up development workflows and improve team productivity through AI-assisted coding.

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

This instructor-led, live training in Patras (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.

This instructor-led live training in Patras (online or onsite) is targeted at beginner, intermediate, and advanced-level professionals who wish to use Bolt.new to rapidly create and enhance web app prototypes.

By the end of this training, participants will be able to generate prototypes from prompts, refine features and interface flows, test and troubleshoot application behavior, and publish prototypes for review.

This instructor-led live training in Patras (online or on-site) targets developers who want to use Windsurf to build features conversationally, execute terminal workflows within the IDE, and refactor across the codebase.

By the end of this training, participants will be able to use Cascade for navigation, execute terminal commands inside the editor, leverage predictive edits, and customize Windsurf for proprietary stacks.

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

• Master enterprise prompt architecture across six layers (Role, Context, Constraints, Domain Standards, Format, Examples).
• Encode business, security, and compliance constraints (GDPR, EU AI Act, sector standards) directly into prompts.
• Co-build a prompt library that is validated, shared, and governed by all teams.
• Define sustainable governance, including the 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.